●

A national laboratory of the U.S. Department of Energy 

Office of Energy Efficiency & Renewable Energy 

National Renewable Energy Laboratory 

Innovation for Our Energy Future 

Preliminary Technical Risk Technical Report 

NREL/TP-640-41156 Analysis for the Geothermal March 2007 

Technologies Program 

J. McVeigh and J. Cohen 

Princeton Energy Resources International 

M. Vorum, G. Porro, and G. Nix 

National Renewable Energy Laboratory 

NREL is operated by Midwest Research Institute Battelle Contract No. DE-AC36-99-GO10337 
Technical Report

NREL/TP-640-41156 

March 2007 

Preliminary Technical Risk 

Analysis for the Geothermal 

Technologies Program

J. McVeigh and J. Cohen 

Princeton Energy Resources International 

M. Vorum, G. Porro, and G. Nix 

National Renewable Energy Laboratory

Prepared under Task No. GT04.1101 

National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401-3393 

303-275-3000 • www.nrel.gov

Operated for the U.S. Department of Energy

Office of Energy Efficiency and Renewable Energy

by Midwest Research Institute • Battelle 

Contract No. DE-AC36-99-GO10337
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Table of Contents

Page

Executive Summary 1 

Introduction 4 

Summary of Method 5 

Consistency With Other DOE Risking Efforts 5 

Challenges and Benefits of Risk Estimation and Interpretation 5 

Conclusions 7 

Recommendations 8 

Risk Assessment Participants 9 

The Geothermal Risk Analysis Team 9 

The Geothermal Expert Team 9 

GETEM Reference Cases and Input Organization 11 

The GETEM Model Reference Cases 11 

The GETEM Model Input Variables 11 

Geothermal Technology Improvement Opportunities 13 

Risk Cases Considered 19 

Geothermal Expert Team Scoring Matrices 19 

Suggested Scoring Process for the Expert Team 27 

MYPP Cases Scoring 27 

Changes Made to Experts Inputs 28 

 iii
Summary of Results 30 

Case-Specific Results 32 

Hydrothermal Binary 2010 Experts Case 33 

Hydrothermal Flash 2010 Experts Case 35 

EGS Binary 2010 Experts Case 37 

EGS Flash 2010 Experts Case 39 

EGS Binary 2040 Evolutionary Experts Case 41 

Hydrothermal Binary 2010 MYPP Case 43 

EGS Binary 2010 MYPP Case 45 

Appendix A: Hydrothermal Binary Power System Case – Inputs A-1 

Appendix B: Hydrothermal Flashed-Steam Power System Case – Inputs B-1 

Appendix C: EGS Binary Power System Case – Inputs C-1 

Appendix D: EGS Flashed-Steam Power System Case – Inputs D-1 

Appendix E: Consensus Expert Team Scoring Matrices E-1 

Appendix F: Cumulative Probability Distribution Functions of LCOE by Case F-1 

 iv
Executive Summary 

This report introduces the development and first use of a management tool for risk analysis for 

the Geothermal Technologies Program (GTP, “the Program”) of the U.S. Department of Energy 

(DOE). These first eight pages are an overview of a technical risk analysis task, leading into a 

presentation of comprehensive details of the task and its outcomes. 

The analysis task developed a probabilistic, quantitative risk assessment of potential success of 

research goals for the Program. The goals are outlined in the Program’s 2005 Multiyear Program 

Plan (MYPP). 

As context, the focus here is on technical risk analysis. This sets a stage for a necessary 

evolution of Program risk analysis into other areas. Risk can be considered in forms such as: 

3⁄4 Technical risk 3⁄4 Management risk 

3⁄4 Market risk 3⁄4 Financial risk 

3⁄4 Political risk 

Technical risk analysis estimates a degree and a certainty to which research and development 

(R&D) work may fulfill goals of achieving technology improvements. Improvements may fall 

below, at, or above the goals. The approach used here expresses risk as pairs of values: a 

probability of success and a magnitude of technical effect or impact compared to a goal. The 

technical impact can be measured in terms of technology performance or its cost of utilization; 

and the probability is estimated as a percent likelihood of achieving the impact. Risk can further 

comprise one pair of values as a point estimate of risk, or be defined as a probability distribution 

function (PDF) comprising a range of varying impacts with respective probabilities of 

occurrence. 

Across the DOE offices, efforts are under way to integrate methods for analyzing, managing, and 

communicating risk. This technical risk analysis task for the Geothermal Program can evolve 

toward adding capabilities – for example, in the aspect of management risk – to include risk 

analysis of Program budgets and schedules. Those topics would address needs such as 

predicting variations of outcomes that may result from R&D work as functions of changes in 

budget or of schedules; and assessing tradeoffs in R&D results due to competition among 

research lines for constrained budget resources. These are topics of future risk analyses. 

Finally, each risk analysis task is one step in an iterative, ongoing cycle of progress management. 

This initial technical risk analysis has established a starting point as a template, which can be 

progressively filled in and expanded in risk-based reassessments of performance and goals. 

1
The technical risk analysis approach examines estimates of variable risks assigned to 

performance and economic benefits that may be achieved via Program research work. Risk 

results are expressed in terms of a key Program metric: levelized cost of energy

1

 (LCOE), and 

associated statistical information. This first analysis assumes a flat budget trend over the term of 

future performance estimates, at funding levels sufficient to accomplish the work scope projected 

in the Program’s MYPP. That means that the risk team has considered technical challenges on 

the merits of being able to succeed in meeting goals in the projected time frames, but not on 

availability of R&D resources. 

This preliminary analysis indicates that the Program is on course toward meeting its portfolio of 

economic and performance goals for the near-term target in 2010. For the longer-term goals, 

projected improvements in technology cost and performance present a narrow window of 

probability for success. Very important, the analysis provides data with which to prioritize 

performance levels that are critical to reach long-term success with improved certainty. 

Specifically, the analysis employs a statistical sampling method using Monte Carlo simulation to 

drive a spreadsheet-based model named the Geothermal Electric Technology Evaluation Model 

(GETEM). GETEM is a techno-economic systems analysis tool for evaluating and comparing 

geothermal project cases. By itself, GETEM is a deterministic model; it computes LCOE values 

for a set of user-specified input variables that address about four dozen project criteria. A 

particular baseline geothermal project case is defined by allocating a profile of values to the 

input variables. A complementary feature of GETEM is an ability to examine “improved 

technology” cases derived from the baseline by applying potential benefits of research in terms 

of improvements to the baseline input variables. Each set of baseline and improvement data 

defines a profile of two related development cases. It compares the “present” with a conditional 

“future.” By combining Monte Carlo sampling with GETEM as a risk model, it evaluates 

multiple ranges of potential impacts of R&D, coupled with corresponding levels of probability of 

the occurrence of those impacts. The evaluation computes probability distributions of LCOE for 

geothermal power projects, rapidly assessing complex risk profiles for cases in great detail. 

The R&D impacts and probability distributions for this task were estimated by a risk team 

including independent experts, DOE laboratory researchers, and laboratory subcontractors. This 

GETEM-based risk analysis uses baseline data from the GTP Multiyear Program Plan (MYPP), 

and ranges of values of technology improvement opportunities2 (TIOs). The baseline values of 

GETEM input variables were adjusted to define cases for “improved technology” that reflect the 

risk team’s estimates of improvements derived from the TIO values. Associated probabilities 

were proposed by the risk team. Combining the TIO inputs and probabilities enables the risk 

model to examine probabilistic implications of uncertain outcomes of technology R&D on the 

1

 The LCOE is a present value of a producer’s cost of electricity for commercial and industrial power systems, 

usually named “busbar cost.” It covers exploration, development, construction, and operating phases of a project. 

LCOE accounts for time-dependent values of equity, borrowed capital, operation and maintenance costs, and 

discounted values of other cash-flow terms such as taxes, insurance, escalation, etc. 2

 A TIO is simply a specific capacity, characteristic, component, or function of a technology that may be improved 

by R&D. For the GTP context, it can be a remote exploration technique, a way of interpreting geologic data, a hightemperature electronics design for downhole drilling instruments, new materials for well casings, enhanced heat 

transfer surfaces for a power plant, a design of steam turbines to better withstand wet steam, etc. Project TIOs can 

be rolled up into higher-level TIOs as packaged, program-level research subjects. 

2
LCOE of generated electrical power. The calculated results give management a picture of the 

likelihood of achieving GTP research goals. 

Starting with the MYPP baseline data, the team created profiles for seven risk cases. Table E1 

summarizes the seven cases on their baseline LCOE values, the improved LCOE ranges (i.e., the 

minimum, mean, and maximum LCOEs determined by the risk analysis model), and the 

probabilities of meeting reduced LCOE values for each case. The “case year” identifies the year 

by which the improvements are expected to be achieved. 

Table E1. Summary of LCOE Range and Probability of Meeting 5¢/kWh Goal by Case 

Case and Year 

Baseline 

2005 

LCOE 

Improved-Case 

LCOE Range3 Probability of Meeting 

Min Mean Max 5¢/kWh 

Goal 

Mean LCOE 

by Case Year 

Results of Expert Team Estimates 

HT Binary 2010 8.54 3.80 4.73 6.13 75% 54% 

HT Flash 2010 4.73 2.94 3.43 4.13 100% 54% 

EGS Binary 2010 28.5 5.71 11.5 18.9 N/A4 51% 

EGS Flash 2010 29.3 8.39 15.6 23.0 N/A 53% 

Evolutionary EGS Binary 2040 28.5 3.85 6.29 13.8 14% 59% 

Results of MYPP Estimates 

HT Binary 2010 8.54 4.35 4.74 5.10 99% 52% 

EGS Binary 2010 28.5 12.5 14.3 17.8 N/A 52% 

The “Min” and “Max” values of the calculated LCOE ranges correspond to 5% and 95% probabilities 

of occurrence, respectively. 

To summarize some general conclusions from these numbers, the Program has good potential of 

achieving research goals to attain cost-effective power for hydrothermal systems in the 2010 

time frame. This means that goals for hydrothermal technology development could be increased, 

in order to increase a scope of potential for growth in that industry sector. 

EGS technologies have an almost 60% probability of achieving an LCOE of 6.3¢/kWh by 2040, 

closely approaching a Program goal of 5¢/kWh. Therefore, the R&D plans should be examined 

to increase the composite probability of reaching the goal. 

3

 The LCOE mean values in Table E1 are calculated as probability-weighted averages. 4

 Three EGS entries in Table 2 are labeled “N/A” (not applicable). This is because Program goals project that 

technology improvements under DOE research will make it possible for new, greenfield power development 

projects to attain LCOE values of 5¢/kWh. This goal is further scheduled to occur by 2010 for hydrothermal 

resource power systems, and by 2040 for EGS power systems. Therefore, the EGS cases would not meet the 

5¢/kWh threshold by 2010. 

3
Introduction 

This report explains the goals, methods, and results of a probabilistic analysis of technical risk 

for a portfolio of R&D projects in the DOE Geothermal Technologies Program (The “Program”). 

The analysis is a task by Princeton Energy Resources International, LLC (PERI), in support of 

the National Renewable Energy Laboratory (NREL) on behalf of the Program. 

The main challenge in the analysis lies in translating R&D results to a quantitative reflection of 

technical risk for a key Program metric: levelized cost of energy (LCOE). This requires both 

computational development (i.e., creating a spreadsheet-based analysis tool) and a synthesis of 

judgments by a panel of researchers and experts of the expected results of the Program’s R&D. 

For the computational development, NREL requested that PERI develop a probabilistic risk 

analysis method to evaluate ranges of potential impacts of R&D on LCOE for geothermal power 

development projects. The method uses Monte Carlo simulation in conjunction with GETEM, a 

recently developed systems analysis tool. GETEM is a deterministic model set up to evaluate 

one set of conditions at a time, comparing one baseline profile to one pattern of technology 

improvements as a case study. Each case study represents a development project with unique 

geologic, technical, and economic conditions. Adding a risk analysis capability to GETEM 

involves using a range (probability distribution) of input estimates to calculate probabilistic 

results for potential improvements to a case study baseline. For each risk case study, the Monte 

Carlo routines successively drive GETEM through the ranges of risk values for all 

improvements, called technology improvement opportunities (TIOs), that are considered. The 

model statistically tracks and integrates the calculated case outcomes as probability distribution 

functions (PDFs). 

To estimate risk parameters, the Program invited a team of laboratory and independent, privatesector experts to guide a group of DOE researchers in a task of quantifying potential impacts and 

success probabilities of R&D activities in geothermal technology. The task addresses 

technologies ranging from exploration, to geology and resource assessment, to well drilling and 

energy conversion. 

Program success is measured, in part, on R&D results that enable industry to reduce LCOE by 

using improved geothermal technologies to generate electrical power. This new risk analysis 

activity provides the Program a capability to assess and manage “risk” inherent in its unique 

work. This is achieved by quantifying and integrating the discrete potentials – i.e., probabilities 

– that specific lines of R&D may succeed, and the ranges of impacts that success may entail. 

Those values are used as inputs by the Monte Carlo/GETEM risk model to compute PDFs 

expressing LCOE vs. probability of occurrence. 

As a result, this task provides the Program with a capability to examine research work and 

associated risk, as it is currently known. Furthermore, that capability will enable the Program to 

progressively track work success and work risk. It enables staff at all levels of the Program to 

quickly and consistently adjust future analyses of risk, based on evolving estimates of research 

impacts and corresponding success probabilities. 

4
Summary of Method 

GETEM is a system model for analysis of performance and economics of geothermal power 

projects. It enables users to quickly examine variables that characterize complex geothermal 

power systems, and quantify profiles of project phases from exploration through operation. 

Applying GETEM as a computation engine in risk analysis, the subject of this activity, requires 

adding statistical sampling features to GETEM to implement Monte Carlo simulation. This 

computer programming task is coupled with profiling a particular set of cases and risk 

probability characteristics as the bases for a preliminary technical risk analysis. 

This task is developmental by virtue of creating a GTP-specific risk analysis tool (i.e., GETEM 

coded with the Monte Carlo method integrated). For this development, the risk modeling uses a 

set of profiles for geothermal binary energy conversion case studies that are defined in the 2005 

GTP Multiyear Program Plan (MYPP). Those cases, along with additional flashed-steam 

conversion cases defined for this analysis, serve as benchmarks from which to assess potential 

effectiveness of GTP research work. 

This developmental process is being done specifically to provide data and analyses to the 

Program management team for the annual DOE budget process. More generally, the risk 

methods and tools resulting from this task will serve ongoing Program oversight work. 

Consistency With Other DOE Risking Efforts 

The method of assigning risk parameters to a program’s R&D work – ranges of estimated degree 

of change in project cost and performance, and the likelihood of it occurring – is a high-profile 

topic within the evolving DOE approach to risk. The approach taken in this GTP-specific risk 

analysis study is consistent with the current state of DOE methods except as noted below. 

Challenges and Benefits of Risk Estimation and Interpretation 

The practice of assigning risk parameters is a critical step in examining individual and integrated 

risks across Program disciplines. Assigning risk probabilities combines science, analysis, and 

judgment. The team of experts for this task was asked to judge potential successes of Program 

research at project levels, and to also estimate how to roll up those judgments to higher-level 

performance metrics that comprise the GETEM input variables. This approach poses a dual 

challenge of, first, estimating unknown research outcomes and, second, translating those 

outcomes into composite improvements and probabilities of success for the GETEM inputs. 

While this dual challenge is well recognized for its difficulty, it offers a prospect of highly 

effective insight for Program management. In particular, this approach equips any management 

team with an ability to assess and manage tasks down their administrative chain with 

consistency, and to evaluate and communicate Program performance up the chain. 

5
Specification of risk parameters in this type of study enables comprehensive comparison of the 

prospective effectiveness of different research activities under a set of assumptions concerning 

funding. This comparison can shed light on the weight of each technical subject’s relative risk 

compared to other discipline-specific successes or shortfalls. 

This study does not completely address all aspects of uncertainty associated with geothermal 

electricity generation. Rather, the study is focused on understanding the impact of the 

uncertainty associated with the effectiveness of Program R&D on lowering the levelized cost of 

electricity generation. Significant uncertainty is associated with the characterization of 

geothermal resources. This is a unique aspect of geothermal development when compared to 

other renewable technologies. Resource supply uncertainty is being reviewed in a separate, 

comprehensive study of geothermal technology. It would be fruitful to integrate the findings of 

that study, using this risk analysis methodology to provide a holistic understanding of all the 

major sources of uncertainty for geothermal electricity generation. As one example, a high level 

of uncertainty and consequent risk pertains to the assessment of geothermal resources that can be 

reliably and economically engineered to create Enhanced Geothermal Systems (EGS). These 

systems are characterized as heat reservoirs within geologic formations that may be artificially 

stimulated to increase naturally low permeabilities, resulting in fracture pathways that combine 

high flow rates and high energy recoveries using water circulation. 

While the uncertainty of successful EGS reservoir stimulation should be considered in 

comparison to other technology disciplines (e.g., the wellfield construction and energy 

conversion subprograms), the uncertainty associated with the abundance of EGS-type 

geothermal resources was not considered in this study. 

6
Conclusions 

The following conclusions are observations about the development of the risk methodology and 

its quantitative results. The results are particular outcomes of the case studies of this analysis, 

which was set up to specifically examine implications of the current GTP Multiyear Program 

Plan. Changing the input profiles for the cases would change the computed results and may lead 

to alternative conclusions. However, without this first step of evaluating MYPP risk, the results 

of other cases cannot logically be used to suggest changes to the MYPP. That reflects both the 

purpose and the consistency of the statistical risk analysis methods here. For details explaining 

and supplementing these general conclusions and the following recommendations, review the 

“Case-Specific Results” section on Page 32. In particular, the plots in Figures 2-15 give 

informative breakouts of discrete TIO impacts on LCOE. 

C-1. The Program has good potential of achieving research goals of attaining cost-effective 

power for hydrothermal systems in the near-term 2010 time frame. This means that 

goals for hydrothermal technology development could be increased, in order to increase 

a scope of technical and economic potential for growth in that industry sector. 

C-2. TIO levels that yield a mean LCOE of 6.3¢/kWh for EGS technologies in 2040 have 

almost 60% probability of success. Further examination of modeling results indicates 

that, while outcomes from currently planned R&D have a probability of resulting in 

LCOE close to the 5¢/kWh Program goal, the probability may be lower than desired. 

Therefore, the R&D plans should be closely examined to target objectives that increase 

the composite probability of reaching the goal. This illustrates a key benefit of 

quantifying probabilistic risk – developing data with which to rate and focus goals and 

tasks by uncertainties. 

C-3. This preliminary risk analysis focuses on what is technologically possible for planned 

activities under future budgets with level funding, assuming that level of funding is 

adequate to complete the work. This protocol may complement future methods to 

address budget and schedule risk; the technical risk analysis can be expanded to look at 

variable funding and schedule scenarios. Such refined analysis will require additional 

data and model development to incorporate R&D deliverables, effort, and budget. 

C-4. The TIOs for EGS and exploration technologies contribute a small portion of projected 

improvements for Hydrothermal 2010 cases, but they become important for EGS 2010 

cases and even more important for EGS 2040 cases. By 2040, the EGS and exploration 

TIO contributions to LCOE reductions are noticeably greater than drilling cost 

reductions, and also much greater than conversion impacts. Their value warrants strong 

consideration of focused research and resource allocations. 

C-5. Energy conversion TIOs are important in the 2010 cases, but become less important in 

the 2040 cases, because EGS and exploration TIOs become more dominant. This 

suggests targeting the Program’s strategy and tactics to capture conversion technology 

gains early; and, thereafter, just tracking the technology (with associated reduced 

budget allocations) into the mid- and long-term time frames. 

7
C-6. Although there are different timing and budget implications for the most effective 

realization of various TIOs, all TIOs are essential to capturing full long-term gains. 

Recommendations 

We recommend expanding the risk assessment activities to address these objectives: 

R-1. Focus the MYPP on those research activities that offer best success of meeting the 

5¢/kWh LCOE target by 2040 for EGS systems. 

R-2. Complete the mapping of the GTP work breakdown structure (WBS) with respect to 

potential impacts, i.e., incorporate other information to determine which research 

areas/tasks give the most “bang for the buck” and in what time frame. This provides a 

basis to optimize program strategy, tactics, and activities. 

R-3. Investigate alternative budget, schedule, and competitive task funding scenarios. 

R-4. Develop better drilling cost models, especially those that can account for short-term 

perturbations due to oil and gas drilling demands. This may be as simple as 

incorporating additional parameters into the cost models, such as a ratio of open drilling 

permit applications to the number of available drill rigs. This will allow for 

investigation of issues such as determining most probable depths for optimizing LCOE 

for EGS systems as a function of geologic temperature gradients. 

R-5. Expand the technical risk analysis to include other resources, such as geopressured 

reservoirs and coproduction from oil and gas wells. 

R-6. Finally, this implementation of GTP technical risk analysis should be proposed as a 

platform to update data used by the Energy Information Administration (EIA) for the 

National Energy Modeling System (NEMS) program and database. Risk projections 

can be coupled with geologic resource data to generate periodically updated supply 

curves of geothermal resources. A resource supply curve provides energy costs as a 

function of installed capacity, and the data can be regionalized, whereas NEMS now 

uses a matrix of nominally site-specific energy and cost data to represent the U.S. 

geothermal energy potential on a restricted geographic basis. Addressing the NEMS 

database would be fundamentally beneficial in the near term, because the geothermal 

data in NEMS now are understood to be outdated. Furthermore, EIA has initiated some 

interpretations of commercial geothermal development potential, and this risk analysis 

tool may provide leverage by which to collaborate with EIA in better representing 

geothermal potential for NEMS. Preliminary discussions with EIA in this vein have 

been favorably received. 

Looking forward, by incorporating risk in the supply curve characterization of geothermal 

resources, the Program can support NEMS applications that also seek to incorporate risk into 

national economic modeling. 

8
Risk Assessment Participants 

The Geothermal Risk Analysis Team 

The Risk Analysis Team included Joe Cohen and Jim McVeigh of PERI; Gerry Nix, Gian Porro, 

and Martin Vorum of NREL; and Pat Quinlan of Sentech, Inc. This team was responsible for 

coordinating the efforts of the Geothermal Expert Team, as well as collecting the individual 

technology improvement estimates from each of the experts, compiling a consensus of the expert 

team estimates, and reporting on these estimates. Additionally, PERI was responsible for 

developing the Monte Carlo simulation coding, using the estimates to run the probabilistic risk 

analyses, and compiling the detailed results for this report to DOE. 

PERI has extensive experience in designing and modifying probabilistic risk analyses models. 

For example, PERI had a lead role in developing the DOE Wind Technologies Program’s Wind 

Pathways risk model. PERI also supports DOE staff in the development of guidelines for risk 

analysis that are evolving within the Office of Energy Efficiency and Renewable Energy (EERE) 

and other branches. 

The Geothermal Expert Team 

Table 1 lists the experts who participated in this process of planning and implementing risk 

analysis for the Program. The Geothermal Expert Team was convened to assess the potential 

impacts and attendant probabilities of success of the Geothermal Research Program’s R&D 

activities on technology performance and cost. Members of the team performed their 

assessments and reviewed the consensus estimates between March 15, 2006, and March 31, 

2006. The team was divided into three technology subgroups: 1) EGS and Exploration, 2) 

Wellfield and Drilling, and 3) Energy Conversion. 

Table 1. Experts Participating in the Geothermal Risk Analysis5 

Organization Name Subgroup 

GETEM Development Team 

Sandia National Laboratory (SNL) Chip Mansure Wellfield/Drilling 

SNL Steve Bauer Wellfield/Drilling 

Livesay Consultants Bill Livesay Wellfield/Drilling 

Black Mountain Susan Petty EGS/Exploration 

Idaho National Laboratory (INL) Greg Mines Energy Conversion 

Advisers 

INL Joel Renner EGS/Exploration 

Lawrence Berkeley National Laboratory (LBNL) Carol Bruton EGS/Exploration 

LBNL Bill Bourcier Energy Conversion 

SNL Doug Blankenship Wellfield/Drilling 

SNL Randy Norman Wellfield/Drilling 

5

 Includes participation in any of the teleconferences (including kickoff), submission of individual scoring, or 

review/comments on group scoring. 

9 
NREL Keith Gawlik Energy Conversion 

NREL Gerry Nix Energy Conversion 

Barber Nichols Ken Nichols Energy Conversion 

BIBB & Associates Inc. John Brugman Energy Conversion 

Energy and Geoscience Institute (EGI), University 

of Utah Joe Moore EGS/Exploration 

EGI Phil Wannamaker EGS/Exploration 

EGS Inc. Paul Brophy EGS/Exploration 

Global Power Solutions Gary McKay Energy Conversion 

Graphic Vision Kathy Enedy EGS/Exploration 

MIL-TECH UK Ltd Roy Baria EGS/Exploration 

Halliburton Porter Underwood EGS/Exploration 

Massachusetts Institute of Technology (MIT) Jeff Tester EGS/Exploration 

Ormat Technologies, Inc. Daniel Schochet Energy Conversion 

Software Enterprises Inc. Ralph Veatch EGS/Exploration 

The Industrial Company (TIC) Richard Campbell Energy Conversion 

University of Massachusetts Dartmouth (Retired) Ron DiPippo Energy Conversion 

Unocal (Retired) D. Stephen Pye Wellfield/Drilling 

10
The remaining sections detail the bases, planning, and implementation of the risk analysis 

method. Results that are summarized above are described in detail below. 

GETEM Reference Cases and Input Organization 

The GETEM Model Reference Cases 

It is important to note that the cost and performance inputs in GETEM define a number of site 

and project characteristics, namely the temperature, type, and depth of the resource; and the type 

of energy conversion system. The Risk Analysis Team, with guidance from the GETEM 

Development team, assigned case-study baselines for the analysis using multiple “Reference 

Cases.” The Reference Cases were developed as performance benchmarks for the GTP Research 

Program. The following four cases are the Reference Cases from which improvements in 

technology cost and performance were projected. 

1. Hydrothermal Binary

6 2. Hydrothermal Flash 

3. EGS Binary Shallow7 4. EGS Flash Deep 

The GETEM Model Input Variables 

For this analysis, the input variables and calculated values on the GETEM model input sheets 

(see Appendices A through D) are defined as belonging to one of the four following categories: 

a. Plug Values - Inputs that remain fixed for the risk analyses and do not change regardless 

of “case” specification or as a result of R&D. 

b. Case Defining Plug Values - Inputs that define each “case” and were varied between 

cases, but are not used within a case to define R&D improvements. 

c. Model Calculations - performance and cost values that the model calculates; these were 

not varied by the experts, and could change as a result of changes in other inputs. 

d. Research-improved Technology Performance Metrics (TPMs) - inputs that are “risked,” 

or statistically sampled, by applying a distribution of improvements from R&D that were 

estimated by the Geothermal Expert Team. 

DOE EERE is developing a risk analysis methodology that defines TPMs as measures of a 

technology’s performance or costs that can be used both to track program performance and to 

specify improvements projected for the Program’s research efforts. For purposes of this 

analysis, the TPMs are a subset of the inputs to the GETEM model. 

The GETEM-based risk analysis uses the baseline data and ranges of improvements from the 

TIOs to examine probabilistic impacts of technology changes on the LCOE of generated 

electrical energy. The results portray ranges of probabilities of meeting the GTP research goals. 

GETEM estimates LCOE for geothermal power projects. In GETEM, a user assigns input values 

6

 Corresponds to a reference case used to estimate Program research in the MYPP. 7

 Ibid. 

11
to a profile of parameters to define geothermal resource development projects. Each time the 

GETEM program file (an Excel spreadsheet) is saved, it uniquely defines a case that comprises a 

profile of “baseline” parameter values. The model is configured to give the user a comparison of 

the “baseline” case with an “improved” case, such that the input parameters can uniquely and 

simultaneously be varied toward different goals. The goals may include reducing capital costs, 

examining varying resource decline implications, and increasing equipment performance 

characteristics, etc. The GETEM code is configured such that power conversion systems are 

separately defined, depending on the user’s application of either flashed-steam technology or 

binary energy conversion systems. 

The GETEM Development Team was responsible for establishing the baseline parameters (i.e., 

the current cost and performance parameters of the technology). The Geothermal Expert Team 

was responsible for estimating ranges of improvements that may result from the TIOs, as well as 

probabilities of success of these improvements (i.e., the probability that GTP R&D will result in 

a non-zero level of improvement, as defined by the improvement range). 

Appendices A through D list the GETEM model inputs, broken out by the input categories 

listed on the preceding page, and showing the baseline input data for Hydrothermal Binary, 

Hydrothermal Flash, EGS Binary and EGS Flash technologies, respectively. The baseline 

GETEM inputs are taken from the Reference Case runs used in the MYPP. The Expert Team 

was not asked to comment on the baseline values. However, the experts were asked to suggest 

revisions and their rationales if they thought the baseline numbers should be altered. 

As shown in the appendices, the GETEM model includes more than 50 individual inputs. The 

input categories are similar for the Binary and Flash Technology cases, although slight 

differences exist in some of the individual inputs. Table 2 lists the subset of GETEM inputs that 

were selected as TPMs for this risk analysis, and for which the Geothermal Expert Team was 

asked to estimate ranges and probabilities of improvement impacts. 

Table 2. TPM Subset of the GETEM Model Inputs 

GETEM Inputs/TPMs Units 

Utilization Factor % 

Brine Effectiveness Watt-hour / pound 

Plant Cost $ / kilowatt (kW) 

Production Well Cost $1,000 / well 

Injector Well Cost $1,000 / well 

Surface Equipment Cost $1,000 / well 

Exploration Success Ratio 

Confirmation Success Ratio 

Stimulation Cost $1,000 / well 

Production Well Flow Rate gallons per minute / well 

Temperature Drawdown Rate % / year 

Annual O&M Nonlabor % 

Number of O&M staff # 

12
Geothermal Technology Improvement Opportunities 

The TIOs are the specific ways that program R&D can improve geothermal technology to affect 

the LCOE. To remain consistent with the developing DOE EERE Risk Analysis approach, we 

are using the TIO terminology instead of the Geothermal Program’s term, technology 

improvement potential (TIP), but these are the same entities. 

There are 75 individual TIOs identified by the Program, which have been grouped into 23 TIO 

Roll-ups by the GETEM Development Team. The 23 TIO Roll-ups are shown in Table 3 and 

are listed on the Geothermal Expert Team Scoring Matrices. 

The full TIO list, provided by NREL, is shown in outline format following Table 3. 

13
Table 3. Technology Improvement Opportunity Roll-ups 

TIO 

No. TIO Roll-up Name TIO Description Tec

Su

1 Target Temperature Prediction Increase accuracy of target temperature prediction EGS/ 2 Fractures, Proppants, Rheology Improve fracture methods, proppants, and rheology EGS/ 3 Fracture Control/Packers Control of fracturing - new and improved borehole 

packers 

EGS/ 

4 Fracture Prediction Modeling Develop numerical models that accurately predict 

fracture growth and permeability development 

EGS/ 

5 Subsurface Circulation System Ability to create a subsurface circulation system as 

designed 

EGS/ 

6 Reservoir Performance 

Modeling 

Develop numerical models that explain and extend reservoir performance 

EGS/ 

7 Artificial Lift Improve artificial lift technology EGS/ 8 Short Circuit Mitigation Improve short-circuit mitigation methods EGS/ 9 Technical Systems Analysis Perform systems analysis and integration EGS/ 

10 Remote Sensing Remote sensing exploration methods (InSAR, 

hyperspectral imaging, GPS) 

EGS/ 

11 Geophysics Geophysical exploration methods (seismic, 

magnetotellurics) 

EGS/ 

12 Geochemistry Geochemical exploration methods (isotopes, gases) EGS/ 13 Resource Assessment National geothermal assessment and supply (EGS, 

hydrothermal) 

EGS/ 

14 Drilling Time Reduction Reduction of drilling time and expense, especially in hard 

abrasive formations 

Wellfi

15 Wellbore Lining Reduction Reduction of time and expense to line the wellbore 

(including using less material and less costly material) 

Wellfi

16 Flat Time Reduction Reduction of nonessential flat time Wellfi17 Instrumentation, Testing, 

Simulation 

Development of basic information through analysis and simulation efforts. 

Wellfi

18 Completion and Production Completion and production-related development projects Wellfi19 Cycle Related Cycle Related Energy 

14
TIO 

No. TIO Roll-up Name TIO Description Tec

Su

20 Component Related Component Related Energy 21 Monitoring and Scaling Monitoring and Scaling Energy 22 Design/Construction Related Design/Construction Related Energy 23 Automation/Enhanced Controls Automation/Enhanced Controls Energy 

* The individual TIOs are listed in more detail on the following pages. 

15
The full TIO list for the Program is shown below, as provided by NREL: 

1. TIOs for Enhanced Geothermal Systems 

1.1. Resource Characterization and Exploration

1.1.1. Increase accuracy of target temperature prediction. Gradient and heat-flow data over 

entire United States at data density needed for firm conclusions of EGS potential 

1.2. Reservoir Design and Development 

1.2.1. Improved fracture methods, proppants, and rheology for EGS reservoirs 

1.2.2. Control of fracturing in EGS reservoirs New and improved borehole packers, 

especially open-hole packers, for isolation of stimulation zones 

1.2.3. Develop numerical models that accurately predict fracture growth and permeability

development as a function of stimulation options and reservoir properties 

1.2.4. Ability to create a subsurface circulation system as designed, and to control fracture 

growth and patterns for optimum fluid contact area and volume

1.3. Reservoir Operation and Management 

1.3.1. Numerical models that explain reservoir performance and reliably extend predictions 

of performance into the future

1.3.2. Artificial lift technology - artificial lift equipment and methods with flexible setting

depths, which can produce 200°C fluid at target flow rate of 54 kg/s for at least 1 year

1.3.3. Improved short circuit mitigation methods - successful short-circuit control for 

temperatures up to 200°C 

1.4. Systems Analysis 

1.4.1. Assemble, analyze, and interpret pertinent information on technologies relevant to 

EGS development from worldwide EGS research, petroleum reservoir development, 

mining operations, and other appropriate sources 

1.4.2. Robust economic models to help guide EGS research and development 

1.5. Technology Transfer 

1.5.1. Collaborative relationships with industries large enough to move EGS development 

forward at desired rates to reach the 2040 goals. Involve at least one major energy

company in the EGS Program by 2009 

2. TIOs for Exploration 

2.1. Remote Sensing 

2.1.1. Show utility of InSAR for remote detection of systems 

2.1.2. Integrate hyperspectral imaging with geophysical data

2.1.3. Show utility of GPS in detecting candidate sites 

2.1.4. Improve modeling of permeability using remote sensing data

2.2. Geophysics 

2.2.1. Improve resolution of magnetotellurics (controlled source audio, computer analysis) 

2.2.2. Improve resolution of seismic (high frequencies, VSP, 3-D) 

2.2.3. Integration of geophysical techniques (joint inversion modeling)

2.3. Geochemistry 

2.3.1. Verify use of isotopes for identifying fluid source and deep permeability

2.3.2. Verify use of gases to identify hidden geothermal systems 

2.3.3. Couple isotope and geochemistry data in transport models 

2.3.4. Correlate geochemical interpretation with geophysical and geologic models

16
2.4. National Geothermal Assessment 

2.4.1. Updated national geothermal assessment including EGS 

2.4.2. Develop a supply curve for hydrothermal systems based on U.S. Geological Survey

(USGS) assessment 

2.4.3. Develop a supply curve for EGS based on USGS assessment 

2.4.4. Maintain exploration data 

3. TIOs for Wellfield Construction 

3.1. Systems Analysis 

3.1.1. Cost model predicting the impacts of drilling technology improvements (input into 

greater ¢/kWh model). 

3.2. Numerical Simulation 

3.2.1. Rock/bit interactions understanding

3.2.2. Drilling instability understanding

3.2.3. Drilling system performance and reliability understanding

3.3. Laboratory Testing 

3.3.1. Drilling Dynamics Simulator capabilities 

3.3.2. Autoclave testing capabilities 

3.4. Field Testing 

3.4.1. Field validation tests successfully supporting smart development efforts 

3.5. High-Temperature Electronics 

3.5.1. Successful demonstrations of geothermal tool electronics 

3.5.2. Increased availability of high-temperature services to the geothermal industry

3.6. Development of Advanced Diagnostics 

3.6.1. Diagnostics While Drilling (DWD) availability and functionality in geothermal

temperature regimes 

3.6.2. Increased bit life through real-time trouble avoidance 

3.6.3. Mean-time to Failure of DWD system electronics

3.6.4. Adaptation of non-wireline telemetry technologies for DWD 

3.6.5. Flat-time reduction 

3.6.6. Adaptation of DWD capabilities to support new drilling technologies 

3.6.7. Real-time telemetry/look-ahead technologies to locate and drill to targets cost 

effectively.

3.7. Engineering the Needed Infrastructure 

3.7.1. Commercially available high-temperature electronics components (a gauge of the 

number of new high-temperature component manufacturers) 

3.8. Well Design 

3.8.1. Well designs optimizing steel and cement use through site-specific analyses

3.8.2. Well designs minimizing steel through lean designs (e.g., monobore technology)

3.9. Rock Reduction and Removal 

3.9.1. Rate of Penetration – granite (ROP)

3.9.2. Bit life (run distance)

3.9.3. Normalized rock reduction cost

3.10. Wellbore integrity 

3.10.1. Flat-time reduction 

3.10.2. Shortened drill and completion time

17
3.11. Well Construction/Completion 

3.11.1. Economic acid-resistant cements

3.11.2. Adaptation of Dual Tube Reverse Circulation (DTRC) drilling for use on generic rigs. 

3.11.3. Wellbore/pump designs/deployment allowing pumps to be set at any depth without 

increasing casing diameter 

3.11.4. Shoe-to-shoe drilling without stopping to plug each lost-circulation zone 

3.12. Wellfield O&M

3.12.1. New corrosion-resistant casing materials/coating systems to reduce well life-cycle 

cost

4. TIOs for Energy Conversion 

4.1. Mixed Working Fluid Plants 

4.2. Other Innovative Cycles 

4.3. Innovative Cycles 

4.4. Non-Turbine Cycles 

4.5. Alternative Working Fluids (non-hydrocarbons) with Improved Heat Transfer 

Characteristics 

4.6. Advanced Air-Cooled Condensers 

4.7. Hybrid Cooling Systems 

4.8. Improved Non-condensable Gas Removal Subsystems

4.9. Increased Turbine Efficiency 

4.10. Innovative Process Monitors 

4.11. Chemistry and Physics of Geothermal Brines 

4.12. Innovative Materials 

4.13. Cost-effective Plant Design and Construction Strategies

4.14. Automation to Reduce Operating Labor 

18
Risk Cases Considered 

Seven cases were evaluated for this risk analysis. The Geothermal Expert Team scored the TIOTPM impacts for five separate cases: 

1. Hydrothermal Binary 2010 

2. Hydrothermal Flash 2010 

3. EGS Binary 2010 

4. EGS Flash 2010 

5. EGS Binary Evolutionary 2040 

Two additional cases were developed to evaluate the improvements projected by the GTP 

research teams in the MYPP: 

6. Hydrothermal Binary 2010 MYPP 

7. EGS Binary 2010 MYPP 

The four GETEM reference cases displayed in Appendices A through D provided the baseline 

input data profiles for these seven risk cases. The baseline data in the appendix cases are 

allocated to the risk cases by title: e.g., hydrothermal binary, EGS flash, etc. 

Geothermal Expert Team Scoring Matrices 

For each of the 23 TIO Roll-ups that fell within their respective areas of expertise, the experts 

were asked to estimate minimum, most likely (or expected), and maximum improvements, as 

well as an estimated probability of success in achieving the “most likely” improvement, to assign 

to the 13 TPMs. Each range of improvements is expressed in percentage terms, relative to the 

baseline TPM value, except for the Utilization Factor, Exploration Success, and Confirmation 

Success TPMs, where the improvements are expressed as absolute additions to the baseline. A 

minimum improvement value is defined as the lowest possible non-zero value that might result 

from the R&D activities, and a maximum is defined as the largest possible advance that could be 

achieved through R&D. 

The experts were asked to consider a constant budget amount for each of the subgroup program 

areas,8 but told that specific spending on TIO areas could be changed to what they considered 

optimal levels (e.g., if no projects are currently being funded in a given TIO, they were not 

precluded from estimating any potential R&D improvements in that area; and, in fact, were 

asked to give their estimates on potential improvements if funding for that TIO was realized). 

This approach to funding eliminated many but not all concerns as to whether a flat-budget 

funding assumption could, in practice, result in achieving impacts that the experts would assign 

in a technical assessment of the TIO risks. For some TIOs, experts still recognized a budget 

constraint in the 2010 time frame that limited the impact of the research on the given TPMs. 

8

 Consistent with the budget outlined in the 2005 MYPP. 

19
The probability of success is a probability of achieving an advance at the expected value of the 

estimated range of improvements, regardless of the specific value assigned. This approach 

enables the expert to define a finite probability that R&D could generate no technological or 

economic improvement. In contrast, simply specifying zero as the minimum value in a 

triangular distribution would give result in very little statistical probability of a zero 

improvement result being selected in the Monte Carlo simulation. Accordingly, this made it 

possible to assign lower probabilities of success to higher-risk, more uncertain areas of R&D. In 

addition, impact limits reflecting experts’ inferences of practical budget constraints were also 

expressed in terms of lower probabilities of success. 

For a given TIO, the R&D might only yield improvements for one, or a few, of the TPMs. The 

experts were asked to fill in only the values for improvements where they thought the TIO would 

have impact. Table 4 identifies graphically those TPMs actually risked by the experts for each 

TIO. Furthermore, the experts were given a score sheet to record their estimates for the ranges 

and probabilities of improvements. Tables 5 through 7 show the score sheets that were used by 

the Expert Team subgroups for some of the TIOs in the EGS Binary 2010 Case (Appendix E 

provides the full scoring sheets for all of the TIOs in all of the cases). 

To assist in assessing risks for the TIOs and interpreting their roll-ups to the TPMs, the Expert 

Team was provided copies of the GTP Multiyear Program Plan. 

20
Table 4. Mapping of Which TIOs Impact Each of the GETEM Input TPMs in All Ca

TIO 

No. TIO Roll-up Name Technology Subgroup TIOs Included 

GETEM Inputs/ TP

Utilization Factor

Brine Effectiveness 

Plant Cost 

Producer Well Cost 

Injector Well Cost 

Surface Equip Cost

Exploration Success

Confirmation Success

1 Target Temperature Prediction EGS/ Exploration 1.1.1 2 Fractures, Proppants, Rheology EGS/ Exploration 1.2.1 3 Fracture Control/Packers EGS/ Exploration 1.2.2 4 Fracture Prediction Modeling EGS/ Exploration 1.2.3 5 Subsurface Circulation System EGS/ Exploration 1.2.4 6 Reservoir Performance Modeling EGS/ Exploration 1.3.1 7 Artificial Lift EGS/ Exploration 1.3.2 8 Short-Circuit Mitigation EGS/ Exploration 1.3.3 9 Technical Systems Analysis EGS/ Exploration 1.4.1, 1.4.2, 1.5.1 

10 Remote Sensing EGS/ Exploration 2.1 11 Geophysics EGS/ Exploration 2.2 

21
TIO 

No. TIO Roll-up Name Technology Subgroup TIOs Included 

GETEM Inputs/ TP

Utilization Factor

Brine Effectiveness 

Plant Cost 

Producer Well Cost 

Injector Well Cost 

Surface Equip Cost

Exploration Success

Confirmation Success

12 Geochemistry EGS/ Exploration 2.3 13 Resource Assessment EGS/ Exploration 2.4 14 Drilling Time Reduction Wellfield/ Drilling 3.9.1 - 3.9.3, 3.10.2, 3.11.2, 3.11.4 15 Wellbore Lining Reduction Wellfield/ Drilling 3.8.1, 3.8.2, 3.11.3, 3.12.1 16 Flat-Time Reduction Wellfield/ Drilling 3.10.1 17 Instrumentation, Testing, Simulation Wellfield/ Drilling 3.1 - 3.6 18 Completion and Production Wellfield/ Drilling 3.7, 3.11.1 19 Cycle Related Power Conversion 4.1.1 - 4.1.5 20 Component Related Power Conversion 4.1.6 - 4.1.9 21 Monitoring and Scaling Power Conversion 4.10 22 Design/Construction Related Power Conversion 4.11 - 4.13 23 Automation/Enhanced Controls Power Conversion 4.15 

Note: Diagonal lines identify the subset of TPMs risked for each TIO in the MYPP Cases. 

22 
Table 5. EGS/Exploration Subgroup Scoring Matrix- EGS Binary 2010 Case* 

TIO Categories 

TIO 1- Increase accuracy of target temperature prediction TIO 2- Improve fracture 

Metrics/TPMs 

Exploration Success 

Units 

Ratio 

Baseline 

in 2005 

0.80 

Improvement Range 

Min 

1%

Expected 

5%

Max 

7% 

Confirmation Success Ratio 0.80 1% 2% 4% Stimulation Cost $K/well 750 Production WellFlow Rate gpm/well 332 

Temperature Drawdown Rate 

Exploration Success 

%/year 

Ratio 

3% 

0.80 

Confirmation Success Ratio 0.80 

methods, proppants and rheology TIO 3- Control of fracturing - new and improved borehole packers 

Stimulation Cost $K/well 750 -35% 0% +50% Production Well Flow Rate gpm/well 332 5% 13% 25.% 

Temperature Drawdown Rate 

Exploration Success 

%/year 

Ratio 

3% 

0.80 

Confirmation Success Ratio 0.80 Stimulation Cost $K/well 750 -25% 0% 25% Production Well Flow Rate gpm/well 332 10% 17.5% 35% 

Temperature Drawdown Rate %/year 3% 

TIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

Exploration Success Ratio 0.80 Confirmation Success Ratio 0.80 Stimulation Cost $K/well 750 -20% 10% 30% Production Well Flow Rate gpm/well 332 10% 25% 50% 

Temperature Drawdown Rate %/year 3% 4% 10% 15% 

*This example shows only four of the 13 TIOs in this subgroup. Negative improvement values indicate a TPM resulting from improvement in one or more other TPMs. 

23
Table 6. Wellfield/Drilling Subgroup Scoring Matrix- EGS Binary 2010 Case* 

TIO Categories Metrics/TPMs Units Baseline 

in 2005 

Improvement Range Probab

of Suc

Min Expected Max 

TIO 14- Reduction of drilling time and expense, especially in hard abrasive 

Well Cost $K/well 4,918 5% 12% 20% 65% Surface Equipment Cost $K/well 100 Production Well Flow Rate gpm/well 332 

formations TIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material) 

Annual O&M Non-labor 

Well Cost 

% of 

field cost 

$K/well 

1.5% 

4,918 4% 10% 15% 50% 

Surface Equipment Cost $K/well 100 Production Well Flow Rate gpm/well 332 

Annual O&M Nonlabor 

% of 

field cost 1.5% 

Well Cost $K/well 4,918 2% 4% 10% 50% 

TIO 16- Reduction of non-essential flat time 

Surface Equipment Cost $K/well 100 Production Well Flow Rate gpm/well 332 

% of 

Annual O&M Nonlabor field cost 1.5% 

TIO 17- Development of basic information through analysis and simulation efforts. 

Well Cost $K/well 4,918 4% 8% 12% 75% Surface Equipment Cost $K/well 100 Production Well Flow Rate gpm/well 332 

% of field 

Annual O&M Nonlabor cost 1.5% 

*This example shows only four of the five TIOs in this subgroup. 

24 
Table 7. Energy Conversion Subgroup Scoring Matrix- EGS Binary 2010 Case

TIO Categories GETEM INPUTS/TPMs Units 

Baseline 

in 2005 

Improvement Range Probability 

Min Expected Max of Success Ex

Utilization Factor % 95% 1.0% 3.0% 4.0% 90% 

TIO 19- Cycle Related 

Brine Effectiveness W-h/lb 10.86 10% 25.% 40.% 90% 

Thplaim

Plant Cost $/kW 2,140 -10% 10% 30% 30% Annual O&M Nonlabor % 1.5% 

Number of O&M Staff # 14.6 

Utilization Factor % 95% 1% 3% 4% 80% 

TIO 20- Component Related 

Brine Effectiveness W-h/lb 10.86 3.3% 8.% 

12.5 

% 75% 

Plant Cost $/kW 2,140 2% 5.% 8% 75% Annual O&M Nonlabor % 1.5% 0% 5% 8% 50% 

Number of O&M Staff # 14.6 

Utilization Factor % 95% 0.% 0.3% 0.5% 30% 

TIO 21- Brine Effectiveness W-h/lb 10.86 2.5% 6.5% 10% 55% Monitoring & Scaling 

Plant Cost $/kW 2,140 Annual O&M Nonlabor % 1.5% 2.8% 17% 40% 65% 

Number of O&M Staff # 14.6 

TIO 22- Design/ Construction Related 

Utilization Factor % 95% 0% 2% 5% 50% Brine Effectiveness W-h/lb 10.86 Plant Cost $/kW 2,140 6% 16% 25% 75% Annual O&M Nonlabor % 1.5% 

Number of O&M Staff # 14.6 

*This example shows only four of the five TIOs in this subgroup. Negative improvement values indicate TPM resulting from improvement in one or more other TPMs. For example, a negative value in the minientry can accommodate an increase in the plant cost in order to achieve improved brine effectiveness. 

25
Because TIOs impact the TPMs differently for hydrothermal vs. EGS resources, and for binary 

vs. flashed-steam conversion technologies, the experts were asked to fill out the seven score 

sheets separately, but only for those cases and TIOs to which they felt comfortable and qualified 

to respond. The text box on the next page shows the suggested scoring process given to the 

Expert Team. 

In addition to the four 2010 cases, the experts were asked to consider the EGS Binary case for an 

“Evolutionary 2040” scenario. The evolutionary scenario sought to project mid- to long-term 

incremental changes to the current technology. Although stated as 2040, the exact year that the 

improvements would be achieved was not critical – the experts were asked to estimate potential 

improvements, assuming available time and budget would be adequate to achieve the research 

goals. 

Furthermore, the experts were asked to consider the relationships between and within the TIOs 

and how improvements in one area should relate to advancements or the probability of 

advancements in other areas. For each TPM that is affected by multiple TIOs, the impacts from 

each of the TIOs were added together and assumed to be equally weighted, unless the Expert 

Team specified other relationships (e.g., the Wellfield/Drilling subgroup used a multiplicative 

method of combining the impacts). Additionally, the team subgroups defined limits (or caps) to 

constrain the amounts of improvement achievable for most of the TPMs. The caps were added 

when it was recognized that simply summing the impacts of all TIOs affecting any given TPM 

could, in some instances, overstate the achievable values of technologic or economic 

improvements. In extreme cases, this might cause GETEM to calculate negative LCOE values. 

PERI compiled the individual experts’ scoring sheets, and recorded the consensus estimates from 

the subgroup phone conferences. That information has been documented for archival record of 

this work. The consensus estimates were then relayed to the entire Geothermal Expert Team for 

final comments or suggested changes to these values. The final subgroup consensus score sheets 

were combined into one set of score sheets, which are shown in Appendix E. 

26
Suggested Scoring Process for the Expert Team 

1. When estimating the range of impact a single TIO Roll-up may have on a GETEM input 

parameter, assume initially that the effects of all TIO Roll-ups that impact that parameter 

are additive and equally weighted. Equivalently, assume that the impact any TIO Roll-up 

may have on a GETEM input parameter is independent and additive with impacts of 

other TIO Roll-ups. 

2. Document the rationale for your estimates in the “comments” column. Include as many 

references as possible as part of your rationale. This is a requirement imposed by the 

administration and Congress that is critical to building the Program’s credibility. 

3. When assessing a TIO Roll-up, refer to the detailed list of TIOs to get an idea of the 

specific research topics involved. Make your best judgment on the combined impact of 

these specific TIOs on their respective TIO Roll-up. Refer as needed to the MYPP 

document for fuller descriptions of the specific research topics. 

4. Start with the hydrothermal binary case. Once you have estimated a range of impact for a 

TIO Roll-up for this case, ask whether that range would change for any of the other 

cases; and, if so, enter those ranges on the proper scoring sheets. 

5. Once assessments have been made for each of the TIO Roll-ups for a case, add the 

combined improvements for each GETEM input variable (assuming the R&D is 

successful), and do a litmus test on the combined impact. If the combined amount 

appears to be too high or too low, try to identify and note any relationships between the 

effects of the TIO Roll-ups that might argue against equal weighting and/or the additivity 

(i.e., consider the relationships between the TIO Roll-ups and how improvements in one 

area can increase, reduce, or preclude advancements or the probability of advancements 

in other areas). Adjust the initial ranges based on these considerations. 

6. Leave cells blank when the TIO Roll-up does not impact a specific GETEM input (do not 

bother entering zeros). 

7. Only address those TIOs and GETEM input variables that you feel you have the expertise 

to consider. Leave everything else blank. 

MYPP Cases Scoring 

As noted above in identifying the seven risk cases considered in this task, two of them 

correspond to References Cases in the MYPP document. Paralleling the Expert Team 

improvement estimates for the other five risk cases, the improvements cited in the MYPP 

document were translated into comparable estimates of ranges of improvements and probabilities 

of success for these two risk cases: 1) Hydrothermal Binary MYPP 2010, and 2) EGS Binary 

MYPP 2010. These MYPP-based cases were included in the analysis to both test the Monte 

Carlo model formulation as well as to provide a point of reference to the Expert Team cases. 

MYPP estimates were culled from the MYPP report by Martin Vorum and Gian Porro. Further 

expert input was provided by Susan Petty, Joel Renner, and Chip Mansure. The following 

general approach was used: 

27
1. In most cases, the improvement values identified for 2010 to 2016 were used and 

assumed to be expected (most likely) values. 

2. Because the MYPP document does not generally specify improvement ranges for TPMs, 

minimum and maximum values for each input were calculated by decreasing and 

increasing the expected value by 25%. This narrow range centered on the expected value 

and was adopted as a conservative and neutral approach. 

3. TIO improvement ranges for Hydrothermal and EGS reference cases were assumed to be 

the same for EGS/Exploration and Energy Conversion activities. TIO ranges for 

Wellfield/Drilling were made distinct and consistent with estimates of well cost 

improvements upon which the two MYPP cases were based.9 

4. As the LCOE improvements documented in the MYPP were inferred to have already 

incorporated to some extent a probability of success, the probability-of-success parameter 

was generally set to 75% or above. This parameter was set somewhat lower for 

Exploration-specific TIOs due to current funding and the inherently higher level of 

uncertainty that often characterizes exploration activity. 

5. Weighting, additivity, and imposition of limits to TPM improvements across TIOs were 

made consistent with those in the Expert Team cases, as describe above. 

As indicated by the diagonal lines in Table 5, the TPMs for the MYPP cases often were applied 

less frequently than in the Expert Team cases. For Exploration and Drilling TIOs, improvement 

ranges for two TPMs were specified for each TIO, the same as in the Expert Team cases. Only 

one EGS-related variable was specified in the MYPP but not risked: the amount of power 

recoverable from the developed reservoir. 

Changes Made to Experts Inputs 

The following describes changes that were made to the consensus estimates that the Expert Team 

subgroups formulated, along with the rationale for making these changes: 

1. Use of “old” well cost data for performing the risk analyses. When the 

process began, the experts noted that the baseline well costs were much lower than currently 

experienced in industry. In fact, well costs have increased significantly in recent years. This is 

due largely to increased demand for the limited stock of equipment used for drilling across the 

geothermal, oil, and gas businesses; and also to increased demand for commodity materials 

such as steel and concrete. Therefore, at the suggestion of Chip Mansure and Bill Livesay, 

GETEM was used to examine higher baseline well costs10

 for each of the cases. That resulted 

in increases in LCOE values, particularly for the cases with deeper wells, as would be 

expected. 

However, a key goal of this task is to examine risk implications, specifically using the

MYPP projections. Therefore, it was decided by NREL to hold the well costs at the levels 

used in the GETEM Reference Cases. The percentage improvements that the Expert Team 

estimated in the context of “new” costs were applied to the original MYPP baseline.

9

 As provided by Chip Mansure. 10 MYPP baseline costs were increased to reflect the change in the Bureau of Labor Statistics Producer Price Index

for the product “drilling oil, gas, dry, or service wells.” 

28
There are arguments to be made that a persistent, past surplus of drilling capacity has 

abated to a degree that will support sustained, sellers’-market cost increases. While current 

expert opinion varies, that view remains to be substantiated and requires long-term data. The 

MYPP baseline costs are required for continuity in this task, regardless of whether a higher 

cost basis is eventually shown to be more reflective of the long-term market. Given more time 

and budget, this issue should be explored further. 

2. Cost or performance parameters that are being reduced. Some of the 

subgroups gave improvements as values greater than 100% for parameters for which the 

improvements are defined in GETEM as reductions (e.g., Stimulation Cost, Temperature 

Drawdown Rate). That would result in negative input values that would cause errors. The 

experts expressed these as percentages, which have been assumed to be meant as “factors” of 

improvement. The values greater than 100% were converted in the following manner: a 200% 

improvement was converted to a 50% reduction, a 300% improvement converted to a 66% 

improvement, and a 400% improvement converted to a 75% improvement.11 However, it 

should be noted that improvements that increased a TPM (i.e., Production Well Flow Rate) 

were not altered in this manner and were allowed to increase, sometimes well above 100%. 

3. The plant cost input to GETEM. Initially, the actual “Plant Cost” input variable 

in GETEM was one of the parameters used as a TPM in the risk computations. However, it 

was observed that the GETEM model uses other TPMs to affect the total plant cost, such as 

increasing the size of the plant and increasing the brine effectiveness. This was inconsistent 

with the way in which the experts were asked to consider the various TIOs. Therefore, the risk 

method now varies the GETEM cell that applies a standalone “improvement” to the calculated 

plant cost in the “improved case” results. The same ranges for improvement were used, so this 

change is assumed minor. However, it should be noted that if the Expert Team specified, for 

example, a 25% improvement in plant costs from program R&D, the total reduction of plant 

costs that GETEM calculates will be more than 25% when there are also changes to plant size 

and brine effectiveness. 

11 Subsequent to the completion of the risk analysis runs, a more precise conversion method was determined: 

Fractional improvement = 1 – [1 / (1 + original improvement factor)]. This approach yields slightly lower 

percentages than actually used. 

29
Summary of Results 

Table 8 provides a summary of the results of the risk analysis runs. This table lists the baseline 

LCOE, the improved LCOE range calculated by GETEM (i.e., the minimum, mean, and 

maximum LCOEs determined by the risk analysis model), and the probability of meeting the 

5¢/kWh Program goal. 

Table 8. Summary of LCOE Range and Probability of Meeting 5¢/kWh Goal by Case 

Case and Year 

Baseline 

2005 

LCOE 

Improved-Case 

LCOE Range12 Probability of Meeting 

Min Mean Max 5¢/kWh 

Goal 

Mean LCOE 

by Case Year 

Results of Expert Team Estimates 

HT Binary 2010 8.54 3.80 4.73 6.13 75% 54% 

HT Flash 2010 4.73 2.94 3.43 4.13 100% 54% 

EGS Binary 2010 28.5 5.71 11.5 18.9 N/A13 51% 

EGS Flash 2010 29.3 8.39 15.6 23.0 N/A 53% 

Evolutionary EGS Binary 2040 28.5 3.85 6.29 13.8 14% 59% 

Results of MYPP Estimates 

HT Binary 2010 8.54 4.35 4.74 5.10 99% 52% 

EGS Binary 2010 28.5 12.5 14.3 17.8 N/A 52% 

The “Min” and “Max” values of the calculated LCOE ranges correspond to 5% and 95% probabilities 

of occurrence, respectively. 

As can be seen in Table 8, the Hydrothermal (HT) cases, for both the Binary and Flash 

technologies, have very high probabilities of meeting the 5¢/kWh goal by 2010, while the 

Enhanced Geothermal Systems (EGS) cases have practically no chance of meeting the 5¢/kWh 

goal by 2010. These results are not surprising, as the use of EGS resources is more of a longterm scenario, as evidenced by their very high Baseline 2005 LCOEs. Still, the EGS cases show 

significant reductions in LCOE by 2010 (about 50% or more), and have the potential to make the 

technology cost competitive by 2040. 

It should be noted that for all Binary technology cases, the number of independent power units 

was assumed to be three units in the baseline and improved to one unit by 2010 or 2040. This 

change was specified by NREL staff and leads, by itself, to a reduction in the LCOE of about 

1¢/kWh in all improved Binary LCOEs, regardless of any impacts from the success of the TIOs. 

12 The LCOE mean values in Table 8 are calculated as probability-weighted averages. 13 Three EGS entries in Table 2 are labeled “N/A” (not applicable). This is because Program goals project that 

technology improvements under DOE research will make it possible for new, greenfield power development 

projects to attain LCOE values of 5¢/kWh. This goal is further scheduled to occur by 2010 for hydrothermal 

resource power systems, and by 2040 for EGS power systems. Therefore, the EGS cases would not meet the 

5¢/kWh threshold by 2010. 

30
 Mean=4.732055 

3.5 4.5 5.5 6.5

However, in the Flash technology cases, the number of independent power units is one unit in 

both the baseline and improved cases; and, therefore, has no impact on the Flash LCOEs. 

The ranges in Table 8 represent key values from a cumulative probability distribution, and an 

example of such a cumulative probability distribution function (PDF) for the Hydrothermal 

Binary 2010 Experts Case is shown in Figure 1. Appendix F provides these cumulative PDFs 

for each of the seven risk cases of this task. 

Distribution for Imp Bin- Total COE/L64 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

3.5 4.5 5.5 6.5

 5% 90% 5%

 4.1781 5.4059 

 Mean=4.732055 

LCOE (¢/kWh) 

Probability 

Figure 1. Cumulative PDF for Total LCOE (¢/kWh) for the Hydrothermal Binary 2010 Experts Case. 

Figure 1 shows the range of LCOE for the Hydrothermal Binary 2010 Experts Case (i.e., a 

minimum of 3.80¢/kWh, a mean of 4.73¢/kWh, and a maximum of 6.13¢/kWh), as well as 

showing the cumulative probability of achieving any value within that range. For example, to 

determine what LCOE had at least an 80% chance of being achieved, one would move 

horizontally from the 0.800 value on the y-axis until intersecting the curve, and then find the 

corresponding value on the x-axis (i.e., 5.06¢/kWh). Furthermore, the Cumulative PDF graphs 

show the 5% and 95% values (i.e., 4.18¢/kWh and 5.41¢/kWh, respectively), which are 

commonly used figures in statistical analysis but do not have any special significance in this 

study. The LCOE values at the 5% and 95% probabilities of occurrence are those values listed in 

Table 8 as minimum and maximum improved-case LCOEs. 

31
Case-Specific Results 

The results summarized in Table 8 include the impacts of all of the TIOs combined. However, to 

assess the individual impacts of each of the 23 roll-up TIOs on a composite LCOE, the risk 

models were run independently for each roll-up TIO (i.e., zeroing out the impacts of all other 

TIOs to assess potential “standalone” improvements for each TIO). 

The following sections show vertical bar graphs for each case, itemizing the composite LCOE 

and selected LCOE component groups that GETEM gives as subtotals for the Baseline and 

Improved runs. Additionally, horizontal bar graphs for each case break out the integrated and 

standalone impacts of the 23 roll-up TIOs on the LCOE reduction. In these graphs, the heavy, 

main bars show the mean LCOE reductions, while the lighter error bars extending from the main 

bars show the maximum LCOE reductions, as determined by the probabilistic risk model. 

As stated earlier, the bars for each of the standalone TIOs reflect potential improvements under 

aggressive budget assumptions (i.e., optimal funding considered independently for each TIO 

within a fixed budget amount for each subprogram research area). As described on Page 26, the 

risk team selectively limited the model’s freedom to aggregate TIO contributions to each TPM to 

prevent the TIOs from being fully additive at all probabilities of occurrence. The need for the 

limitation reflects abstractions in the assessment process of quantifying the TIOs’ influences on 

the TPMs. This limitation ensured that combined TPM impacts in the integrative risk 

computation were not simply composites of standalone TIO contributions. Absent these 

constraints, TPM improvements would have been overestimated, resulting in erroneous 

calculated LCOE values. 

Using Figure 7 as an example, the composite mean LCOE improvement for all TIOs (top bar) is 

about 17¢/kWh, while the TIOs all have predicted individual mean gains of 1¢ to 5¢. Applying 

all of the individual gains cumulatively would give LCOE improvements greater than 17¢. 

These graphs are useful for helping to understand the potential technical and economic 

improvements of each TIO, and in judging the relative impacts of TIOs as a basis for allocating 

research funding. The point made here is that these should not be used to calculate potential 

improvements across the standalone TIO runs for projecting combined benefits, absent 

indications that such summing is at least approximately close to an integrated risk result. 

A useful next step in this process of developing risk analysis methodology and tools would be to 

elicit experts’ estimates of potential improvements that could be achieved under a truly fixed 

budget scenario. This would entail assessing potential tradeoffs in achievement as functions of 

variable task funding, and competition or synergy between achievements among tasks at fixed 

total funding. This moves in the direction of analyzing management risk. It would entail 

assessing a program work breakdown structure (WBS) by detailed tasks, making allocations to 

each task for level of effort, budget, schedule, and product (results) per unit of effort. 

32
Hydrothermal Binary 2010 Experts Case 

Figure 2 shows the components of the LCOE in the Hydrothermal Binary 2010 Experts Case. 

The Plant Capital portion of the LCOE is the largest component in the Baseline Case and 

remains so in the Improved Case, despite incurring the largest absolute LCOE reduction. 

Figure 2. Hydrothermal Binary 2010 ExpertsCaseImproved 2010 COE Relative to 2005 Baseline COE 

0.00 

1.00 

2.00 

3.00 

4.00 

5.00 

6.00 

7.00 

8.00 

9.00 

Total C

OE

Exploration

and

Confirmation

Well Field

Capital

Well Field

O&

M

Field, Nonwell Capital

Field, Nonwell O

&

M

Plant Capital

Plant O

&

M

Royalty

Contingency 

COE Component 

(cents/kWh) 

Baseline Case Improved Case 

Figure 3 shows the standalone impacts of each individual TIO on the overall LCOE 

improvement. Again, the power plant unit reduction (from three units in the baseline to one unit 

in the improved cases) results in a LCOE reduction, which is shown in the figures, of about 

1¢/kWh in all Binary Cases. As can be seen in Figure 3, and in agreement with the results 

shown in Figure 2, the largest TIO impacts for this case occur in the Energy Conversion TIOs 

(TIOs 19, 20, and 22), which impact the Utilization Factor, Brine Effectiveness, and Plant Cost 

TPMs. The reader may judge the approximate extent to which the standalone TIO impacts are 

additive, based on whether and by how much their sum exceeds the composite impact on LCOE 

of all TIOs taken together. 

33
Figure 3. Hydrothermal Binary 2010 Experts- TIO Improvements to 

COE Range 

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 

ALL TIOs + Pow er Plant Unit Reduction 

Pow er Plant Unit Reduction 

ALL TIOs 

TIO 1 - Target Temperature Prediction 

TIO 2 - Fractures, Proppants, Rheology TIO 3 - Fracture Control/Packers 

TIO 4 - Fracture Prediction Modeling TIO 5 - Subsurface Circulation System 

TIO 6 - Reservoir Performance Modeling TIO 7 - Artificial Lift 

TIO 8 - Short Circuit Mitigation 

TIO 9 - Technical Systems Analysis 

TIO 10 - Remote Sensing TIO 11 - Geophysics 

TIO 12 - Geochemistry TIO 13 - Resource Assessment 

TIO 14 - Drilling Time Reduction 

TIO 15 - Wellbore Lining Reduction 

TIO 16 - Flat Time Reduction 

TIO 17 - Instrumentation, Testing, TIO 18 - Completion & Production 

TIO 19 - Cycle Related 

TIO 20 - Component Related 

TIO 21 - Monitoring & Scaling TIO 22 - Design/Construction Related 

TIO 23 - Automation/Enhanced Controls 

COE Improvement (¢/kWh) 

Bar = Mean, Error Bar = Max 

34
Hydrothermal Flash 2010 Experts Case 

Figure 4 shows that, for the Flash technology, while the Plant Capital component remains the 

largest portion of LCOE, it is much smaller than for the Binary technology of the preceding case, 

as shown in Figure 2. This is consistent with the simpler design of flashed-steam plant power 

systems. Also, the Well Field Capital portion of the LCOE, while remaining under 1¢/kWh, 

becomes a much higher percentage of the total COE than for the Binary technology, reflecting an 

increase in well depths from 5,000 to 8,000 feet. 

Figure 4. Hydrothermal Flash 2010 ExpertsCaseImproved 2010 COE Relative to 2005 Baseline COE 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

3.00 

3.50 

4.00 

4.50 

5.00 

Total C

OE

Exploration

and

Confirmation

Well Field

Capital

Well Field

O&

M

Field, Nonwell Capital

Field, Nonwell O&M

Plant Capital

Plant O

&

M

Royalty

Contingency 

COE Component 

(c

ents/kWh) 

Baseline Case Improved Case 

Figure 5 shows the standalone impacts of each TIO on the overall LCOE improvement. In this 

case, the EGS and Exploration TIOs have almost no impact, while the Energy Conversion TIOs 

again have the greatest potential impacts. Improvements from the standalone TIOs become more 

distinguishable and important in the other cases, as seen in the following case descriptions. 

35
Figure 5. Hydrothermal Flash 2010 Experts- TIO Improvements to COE 

Range 

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 

ALL TIOs 

TIO 1 - Target Temperature Prediction 

TIO 2 - Fractures, Proppants, Rheology TIO 3 - Fracture Control/Packers 

TIO 4 - Fracture Prediction Modeling TIO 5 - Subsurface Circulation System 

TIO 6 - Reservoir Performance Modeling TIO 7 - Artificial Lift 

TIO 8 - Short Circuit Mitigation 

TIO 9 - Technical Systems Analysis 

TIO 10 - Remote Sensing TIO 11 - Geophysics 

TIO 12 - Geochemistry TIO 13 - Resource Assessment 

TIO 14 - Drilling Time Reduction 

TIO 15 - Wellbore Lining Reduction 

TIO 16 - Flat Time Reduction 

TIO 17 - Instrumentation, Testing, TIO 18 - Completion & Production 

TIO 19 - Cycle Related 

TIO 20 - Component Related 

TIO 21 - Monitoring & Scaling TIO 22 - Design/Construction Related 

TIO 23 - Automation/Enhanced Controls 

COE Improvement (¢/kWh) 

Bar = Mean, Error Bar = Max 

36
EGS Binary 2010 Experts Case 

Figure 6 shows that, for the EGS Binary 2010 Case, the Well Field Capital and Field, Non-well 

O&M components of LCOE become much larger portions of the total LCOE than in the 

Hydrothermal cases. Because EGS resources are assumed to be much deeper (i.e., 13,000 to 

19,000 feet for EGS compared to 5,000 to 8,000 feet for Hydrothermal), the drilling costs and 

field O&M costs are much higher. The dominance of wellfield costs also reflects the role of 

reservoir stimulation and faster reservoir decline for EGS systems than for the hydrothermal 

systems in the preceding two cases. Potential improvements in this case are greatest in the Well 

Field Capital and Field, Non-well O&M components of LCOE, which results in the Plant Capital 

component becoming one of the larger portions of the LCOE in the improved case. 

Figure 6. EGS Binary 2010 Experts CaseImproved 2010 COE Relative to 2005 Baseline COE 

0.00 

5.00 

10.00 

15.00 

20.00 

25.00 

30.00 

Total C

OE

Exploration

and

Confirmation

Well Field

Capital

Well Field

O&

M

Field, Nonwell Capital

Field, Nonwell O

&

M

Plant Capital

Plant O

&

M

Royalty

Contingency 

COE Component 

(cents/kWh) 

Baseline Case Improved Case 

Figure 7 shows that the EGS and Exploration TIOs (TIO 1 through 13) have much greater 

potential impacts in the EGS case than in the hydrothermal cases. Likewise, the error bars (i.e., 

indicating the maximum potential improvements) are much larger for these TIOs compared to 

drilling and conversion TIOs. This implies that, while the probability of success for these TIOs 

was deemed to be low in the 2010 time frame, they hold the greatest long-term potential impacts 

for this case.14

 While the EGS and Exploration TIOs tend to dominate potential impact, cyclerelated improvement in Energy Conversion, TIO 19, actually shows the largest expected impact 

by 2010 (more than 20% improvement in LCOE). This impact results from a significantly 

increased range of improvement and probability of success over the Hydrothermal Binary case 

reflecting the experts’ view that plant configuration can be optimized for the higher temperatures 

encountered at increased depths in this case. 

14 Experts estimating improvement ranges for this discipline generally felt that the current funding level for EGS and 

Exploration activity, even if reallocated in entirety to each TIO, imposes a limit on the improvement that could be 

achieved by 2010. This limit, construed primarily as a reduction in the probability of success, is reflected in the 

large extent of the positive error bar associated with these TIOs. 

37
Figure 7. EGS Binary 2010 Experts- TIO Improvements to COE Range 

0.00 5.00 10.00 15.00 20.00 25.00 30.00 

ALL TIOs + Pow er Plant Unit Reduction 

Pow er Plant Unit Reduction 

ALL TIOs 

TIO 1 - Target Temperature Prediction 

TIO 2 - Fractures, Proppants, Rheology TIO 3 - Fracture Control/Packers 

TIO 4 - Fracture Prediction Modeling TIO 5 - Subsurface Circulation System 

TIO 6 - Reservoir Performance Modeling TIO 7 - Artificial Lift 

TIO 8 - Short Circuit Mitigation 

TIO 9 - Technical Systems Analysis 

TIO 10 - Remote Sensing TIO 11 - Geophysics 

TIO 12 - Geochemistry TIO 13 - Resource Assessment 

TIO 14 - Drilling Time Reduction 

TIO 15 - Wellbore Lining Reduction 

TIO 16 - Flat Time Reduction 

TIO 17 - Instrumentation, Testing, TIO 18 - Completion & Production 

TIO 19 - Cycle Related 

TIO 20 - Component Related 

TIO 21 - Monitoring & Scaling TIO 22 - Design/Construction Related 

TIO 23 - Automation/Enhanced Controls 

COE Improvement (¢/kWh) 

Bar = Mean, Error Bar = Max 

38
EGS Flash 2010 Experts Case 

Figure 8 shows that, for the EGS Flash 2010 Case, similar to the EGS Binary case, the Well 

Field Capital and Field, Non-well O&M components are the predominant components of the 

baseline LCOE, accounting for 14.1¢/kWh and 5.3¢/kWh, respectively, of the total 29.3¢/kWh. 

Again, the main improvements come from lowering these components, both of which are more 

than cut in half, to 7.0¢/kWh and 2.6¢/kWh, respectively. 

Figure 8. EGS Flash 2010 Experts CaseImproved 2010 COE Relative to 2005 Baseline COE 

0.00 

5.00 

10.00 

15.00 

20.00 

25.00 

30.00 

35.00 

Total C

OE

Exploration

and

Confirmation

Well Field

Capital

Well Field

O&

M

Field, Nonwell Capital

Field, Nonwell O

&

M

Plant Capital

Plant O

&

M

Royalty

Contingency 

COE Component 

(cents/kWh) 

Baseline Case Improved Case 

Figure 9 shows that, while the Wellfield and Drilling TIOs (TIO 14 through 18) and the Energy 

Conversion TIOs (TIOs 19 through 23) generally have larger expected impacts in the 2010 time 

frame, the greatest potential lies in the EGS and Exploration TIOs. That is, there is large 

potential in some TIOs that cannot or may not be realized in the limitation of the 2010 time 

frame. For example, TIO 7, Artificial Lift, has a relatively low probability of success, resulting 

in a low mean improvement; but its maximum potential improvement (i.e., if this R&D is 

successful) is the largest of any TIO for this case. 

The estimated mean impacts of each individual TIO are more truly additive in this case, because 

the improvements are not hitting the caps specified in the model (i.e., the sum of all the 

individual TIO bars is close to the size of the All TIOs bar). 

39
Figure 9. EGS Flash 2010 Experts- TIO Improvements to COE Range 

0.00 5.00 10.00 15.00 20.00 25.00 30.00 

ALL TIOs 

TIO 1 - Target Temperature Prediction 

TIO 2 - Fractures, Proppants, Rheology 

TIO 3 - Fracture Control/Packers 

TIO 4 - Fracture Prediction Modeling TIO 5 - Subsurface Circulation System 

TIO 6 - Reservoir Performance Modeling 

TIO 7 - Artificial Lift 

TIO 8 - Short Circuit Mitigation 

TIO 9 - Technical Systems Analysis 

TIO 10 - Remote Sensing 

TIO 11 - Geophysics 

TIO 12 - Geochemistry 

TIO 13 - Resource Assessment 

TIO 14 - Drilling Time Reduction 

TIO 15 - Wellbore Lining Reduction 

TIO 16 - Flat Time Reduction 

TIO 17 - Instrumentation, Testing, 

TIO 18 - Completion & Production 

TIO 19 - Cycle Related 

TIO 20 - Component Related 

TIO 21 - Monitoring & Scaling 

TIO 22 - Design/Construction Related 

TIO 23 - Automation/Enhanced Controls 

COE Improvement (¢/kWh) 

Bar = Mean, Error Bar = Max 

40
EGS Binary 2040 Evolutionary Experts Case 

Figure 10 shows that the long-term EGS Binary 2040 Evolutionary Case is similar to the shortterm EGS Binary 2010 Case, except that the reductions of the Well Field Capital and Field, Nonwell O&M components of LCOE are even larger in this 2040 case (i.e., reductions from 

8.27¢/kWh to 1.21¢/kWh in 2040 vs. 3.14¢/kWh in 2010 for the Well Field Capital component, 

and from 7.99¢/kWh to 0.59¢/kWh in 2040 vs. 2.45¢/kWh in 2010 for the Field, Non-well O&M 

component). This is to be expected for long-term GTP R&D work. Reductions to the Plant 

Capital component remain relatively constant, which leads to this portion becoming the largest 

component of the LCOE in the improved 2040 case. 

Figure 10. EGS Binary 2040 Evolutionary Experts CaseImproved 2040 COE Relative to 2005 Baseline COE 

0.00 

5.00 

10.00 

15.00 

20.00 

25.00 

30.00 

Total C

OE

Exploration

and

Confirmation

Well Field

Capital

Well Field

O&

M

Field, Nonwell Capital

Field, Nonwell O

&

M

Plant Capital

Plant O

&

M

Royalty

Contingency 

COE Component 

(cents/kWh) 

Baseline Case Improved Case 

Figure 11 again shows that, for the EGS cases, the maximum potential improvements are from 

the EGS and Exploration TIOs (TIOs 1 through 13), with the exception of TIO 19. However, in 

the 2040 time frame, even greater mean improvements are expected. In most cases, this 

increased improvement results from the experts’ perception that more time and money is needed 

to complete these activities than the 2010 time frame can realistically provide, and this is 

reflected primarily as an increase in the probability of success for the 2040 cases. 

41
Figure 11. EGS Binary 2040 Evolutionary Experts-TIO Improvements 

to COE Range 

0.00 5.00 10.00 15.00 20.00 25.00 30.00 

ALL TIOs + Pow er Plant Unit Reduction 

Pow er Plant Unit Reduction 

ALL TIOs 

TIO 1 - Target Temperature Prediction 

TIO 2 - Fractures, Proppants, Rheology TIO 3 - Fracture Control/Packers 

TIO 4 - Fracture Prediction Modeling TIO 5 - Subsurface Circulation System 

TIO 6 - Reservoir Performance Modeling TIO 7 - Artificial Lift 

TIO 8 - Short Circuit Mitigation 

TIO 9 - Technical Systems Analysis 

TIO 10 - Remote Sensing TIO 11 - Geophysics 

TIO 12 - Geochemistry TIO 13 - Resource Assessment 

TIO 14 - Drilling Time Reduction 

TIO 15 - Wellbore Lining Reduction 

TIO 16 - Flat Time Reduction 

TIO 17 - Instrumentation, Testing, TIO 18 - Completion & Production 

TIO 19 - Cycle Related 

TIO 20 - Component Related 

TIO 21 - Monitoring & Scaling TIO 22 - Design/Construction Related 

TIO 23 - Automation/Enhanced Controls 

COE Improvement (¢/kWh) 

Bar = Mean, Error Bar = Max 

42
Figure 14. Hydrothermal Binary 2010 MYPP CaseImproved 2010 COE Relative to 2005 Baseline COE

Hydrothermal Binary 2010 MYPP Case 

Figure 12 shows that the Hydrothermal Binary 2010 MYPP Case is very similar to the 

Hydrothermal Binary 2010 Experts Case. While the mean LCOE reduction is nearly identical in 

both cases (i.e., reducing from a baseline of 8.54¢/kWh to 4.74¢/kWh in the MYPP Case vs. 

4.73¢/kWh in the Experts Case), as shown in Figures F1 and F6 in Appendix F, the range around 

the mean is much narrower in the MYPP Case (i.e., a minimum and maximum of 4.35¢/kWh and 

5.10¢/kWh in the MYPP Case, vs. 3.80¢/kWh and 6.13¢/kWh in the Experts Case). Although 

this might imply that the Expert Team thought there was greater uncertainty in the LCOE 

improvements and in meeting the 5¢/kWh goal, it more likely results from the assumptions on 

which the MYPP cases were based – a set improvement range of +/- 25% around the expected 

value. 

0.00 

1.00 

2.00 

3.00 

4.00 

5.00 

6.00 

7.00 

8.00 

9.00 

Total C

OE

Exploration

and

Confirmation

Well Field

Capital

Well Field

O&

M

Field, Nonwell Capital

Field, Nonwell O

&

M

Plant Capital

Plant O&M

Royalty

Contingency 

COE Component 

(cents/kWh) 

Baseline Case Improved Case 

Figure 12. Hydrothermal Binary 2010 MYPP CaseImproved 2010 COE Relative to 2005 Baseline COE 

Figure 13 reinforces the notion that the MYPP Case shows little uncertainty above and below 

the expected LCOE improvements, as reflected in the small differences between the mean and 

maximum improvements. Again, the issue of hitting the caps implemented in the model limits 

the apparent additivity of the individual TIOs, as previously discussed. 

43
Figure 15 Hydrothermal Binary 2010 MYPP- TIO Improvements to COE

Range

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 

ALL TIOs + Pow er Plant Unit Reduction 

Pow er Plant Unit Reduction 

ALL TIOs 

TIO 1 - Target Temperature Prediction 

TIO 2 - Fractures, Proppants, Rheology TIO 3 - Fracture Control/Packers 

TIO 4 - Fracture Prediction Modeling TIO 5 - Subsurface Circulation System 

TIO 6 - Reservoir Performance Modeling TIO 7 - Artificial Lift 

TIO 8 - Short Circuit Mitigation 

TIO 9 - Technical Systems Analysis 

TIO 10 - Remote Sensing TIO 11 - Geophysics 

TIO 12 - Geochemistry TIO 13 - Resource Assessment 

TIO 14 - Drilling Time Reduction 

TIO 15 - Wellbore Lining Reduction 

TIO 16 - Flat Time Reduction 

TIO 17 - Instrumentation, Testing, TIO 18 - Completion & Production 

TIO 19 - Cycle Related 

TIO 20 - Component Related 

TIO 21 - Monitoring & Scaling TIO 22 - Design/Construction Related 

TIO 23 - Automation/Enhanced Controls 

COE Improvement (¢/kWh) 

Bar = Mean, Error Bar = Max 

Figure 13. Hydrothermal Binary 2010 MYPP - Improvements to 

COE Range 

44
Figure 16. EGS Binary 2010 MYPP Case

Improved 2010 COE Relative to 2005 Baseline COE

EGS Binary 2010 MYPP Case 

Figure 14 shows that the EGS Binary 2010 MYPP Case is very similar to the EGS Binary 2010 

Experts Case, but the MYPP case has a much narrower distribution of LCOE improvements (as 

seen in Figures F3 and F7 in Appendix F). As with the preceding MYPP Hydrothermal Binary 

case, this results from the assumptions governing the construction of the ranges of improvements 

for the MYPP case. Despite the fact that the Expert Case predicts greater improvements for both 

the mean and maximum improvements, neither the MYPP estimates nor the Experts estimates 

for the EGS Binary 2010 Cases suggests that 5¢/kWh is reachable by 2010. However, both the 

MYPP and Experts estimates suggest substantial (i.e., about 50% or more) improvements can be 

made in by the 2010 time frame. 

-

0.00 

5.00 

10.00 

15.00 

20.00 

25.00 

30.00 

Total COE

Exploration

and

Confirmation

Well Field

Capital

Well Field

O&

M

Field, Nonwell Capital

Field, Nonwell O

&

M

Plant Capital

Plant O

&

M

Royalty

Contingency 

COE Component 

(cents/kWh) 

Baseline Case Improved Case 

Figure 14. EGS Binary 2010 MYPP CaseImproved 2010 COE Relative to 2005 Baseline COE 

Figure 15, similar to Figure 13, shows that the MYPP cases have less uncertainty in the LCOE 

reductions than the matching ranges for the Expert Case. This applies to the composite TIOs, as 

well as to the standalone TIO improvements. 

45
Figure 17. EGS Binary 2010 MYPP- TIO Improvements to COE Range

0.00 5.00 10.00 15.00 20.00 25.00 30.00 

ALL TIOs + Pow er Plant Unit Reduction 

Pow er Plant Unit Reduction 

ALL TIOs 

TIO 1 - Target Temperature Prediction 

TIO 2 - Fractures, Proppants, Rheology TIO 3 - Fracture Control/Packers 

TIO 4 - Fracture Prediction Modeling TIO 5 - Subsurface Circulation System 

TIO 6 - Reservoir Performance Modeling TIO 7 - Artificial Lift 

TIO 8 - Short Circuit Mitigation 

TIO 9 - Technical Systems Analysis 

TIO 10 - Remote Sensing TIO 11 - Geophysics 

TIO 12 - Geochemistry TIO 13 - Resource Assessment 

TIO 14 - Drilling Time Reduction 

TIO 15 - Wellbore Lining Reduction 

TIO 16 - Flat Time Reduction 

TIO 17 - Instrumentation, Testing, TIO 18 - Completion & Production 

TIO 19 - Cycle Related 

TIO 20 - Component Related 

TIO 21 - Monitoring & Scaling TIO 22 - Design/Construction Related 

TIO 23 - Automation/Enhanced Controls 

COE Improvement (¢/kWh) 

Bar = Mean, Error Bar = Max 

Figure 15. EGS Binary 2010 MYPP - Improvements to COE 

Range 

46
Appendix A: Hydrothermal Binary Power System Case - Inputs 

Global Economic Parameters Unit Baseline Input Category 

Fixed Charge Rate Ratio 0.128 Plug 

Utilization Factor Ratio 0.95 TPM 

Contingency % 5% Plug 

Input parameters 

Temperature of GT Fluid in Reservoir Deg-C 150 Case 

Plant Size (Exclusive of Brine Pumping) MW(e) 30.0 Case 

Number of independent power units 3 Case 

Brine Effectiveness (exclusive of brine 

pumping) 

Calculate 

Y or N Y Case 

If N (no), enter value in cell C19 and/or E19 W-h/lb Case 

Calculated Brine Effectiveness W-h/lb 4.63 Calc 

Brine Effectiveness W-h/lb 4.63 TPM 

Apply improvement to reducing flow 

requirement or increasing power output 

F - flow or 

P - power 

P Case 

Plant Cost Calculate

 or N Y Case 

If N (no), enter value in cell C24 and/or E24 $/kW - Case 

Calculated Plant Cost $/kW $2,445 Calc 

Plant Cost $/kW $2,445 TPM 

Wells Cost Curve: 1=Low, 2=Med, 3=High 2 Case 

PRODUCTION WELL Depth Feet 5,000 Case 

Estimated Cost, from SNL Curve $K/well $1,222 Calc 

User's Cost Curve Multiplier ratio 1.00 Case 

Producer, Final Cost $K/well $1,222 TPM 

INJECTION WELL Depth Feet 5,000 Case 

Estimated Cost, from SNL Curve $K/well $1,222 Calc 

Injector, Final Cost $K/well $1,222 TPM 

Surface Equip Cost/Well $K/well $100 TPM 

Exploration Success Ratio 0.20 TPM

 Power Found MW(e) 50 Case 

Number of Confirmation wells Count 3 Case 

Confirmation Success Ratio 0.60 TPM 

Injector/Producer Ratio 0.50 Case 

Spare Prods Count - Case 

Well stimulation 

Y- yes or 

N - no 

N Case 

Stimulation cost $K/well $500 TPM 

GF Pump Efficiency 80% Case 

Pump type 

L=lineshaft; 

S=submersible 

L Case 

Flow per LINESHAFT pump gpm/well 2,000 TPM 

A-1 
Global Economic Parameters Unit Baseline Input Category 

Inputted pump depth ft 1,000 Case 

Lineshaft pump cost $K $250 Case 

Flow per SUBMERSIBLE pump gpm/well 2,250 Case 

Additional drawdown for flow>1500 gpm ft/100 gpm - Case 

Pump depth ft 1,000 Calc 

Submersible pump cost $K $250 Plug 

Injection pump dP psi 100 Plug 

Injection pump cost $/hp $700 Plug 

Temperature Drawdown Rate: Input %/year 0.30 TPM 

Result A: Life of nominal reservoir years 30 Calc 

Result B: Loss of discounted revenue % 8.1% Calc 

Annual O&M non-labor (fraction of plant 

cost) % 1.5% TPM 

Annual O&M non-labor (fraction of field 

cost) % 1.0% Plug 

Number of O&M staff # 14.6 TPM 

A-2 
Appendix B: Hydrothermal Flashed-Steam Power System Case - Inputs 

Global Economic Parameters Unit Baseline Input Category 

Fixed Charge Rate Ratio 0.128 Plug 

Utilization Factor Ratio 0.90 TPM 

Contingency % 5% Plug 

Input parameters 

Temperature of GT Fluid in Reservoir Deg-C 200 Case 

ncg level ( based on total flow) ppm 200 Case 

H2S level (based on total flow) ppm 2 Case 

Number of flashes 

1= 1 flash, 

2= 2 flash 2 Case 

Plant Size (Exclusive of Brine Pumping) MW(e) 50.0 Case 

Number of independent power units 1 Case 

Condenser type 

S=surface; 

DC= direct 

contact S Case 

NCG Removal 

J = jet; 

VP=vac 

pump VP Case 

Brine Effectiveness (exclusive of brine 

pumping) 

Calculate 

Y or N Y Case 

If N (no), enter value in cell C24 and/or E24 W-h/lb Case 

Calculated Brine Effectiveness (net, no 

pumping) W-h/lb 9.40 Calc 

Brine Effectiveness (net) W-h/lb 9.40 TPM 

Apply improvement to reducing flow 

requirement or increasing power output 

F - flow or 

P - power 

P Case 

Plant Cost Calculate 

Y or N Y Case 

If N (no), enter value in cell C29 and/or E29 $/kW - Case 

Equipment cost multiplier for installed cost 2.53 Plug 

Calculated Plant Cost $/kW $995 Calc 

Plant Cost $/kW $995 TPM 

Wells Cost Curve: 1=Low, 2=Med, 3=High 2 Case 

PRODUCTION WELL Depth Feet 8,000 Case 

Estimated Cost, from SNL Curve $K/well $1,910 Calc 

User's Cost Curve Multiplier ratio 1.00 Case 

Producer, Final Cost $K/well $1,910 TPM

 INJECTION WELL Depth Feet 8,000 Case 

Estimated Cost, from SNL Curve $K/well $1,910 Calc 

Injector, Final Cost $K/well $1,910 TPM 

Surface Equip Cost/Well $K/well $100 TPM 

Exploration Success Ratio 0.20 TPM

 Power Found MW(e) 100 Case 

Number of Confirmation wells Count 4 Case 

B-1
Global Economic Parameters Unit Baseline Input Category 

Confirmation Success Ratio 0.60 TPM 

Injector/Producer Ratio 0.50 Case 

Spare Prods Count - Case 

Well stimulation 

Y- yes or 

N - no 

N Case 

Stimulation cost $K/well $300 TPM 

Wells Pumped Y- yes or 

N - no N Case 

Unpumped well flow rate lb/h 500,000 Case 

GF Pump Efficiency 9999% Case 

Pump type 

L=lineshaft; 

S=submersibl 

e 

L Case 

Flow per LINESHAFT pump gpm/well 900 TPM 

Inputted pump depth ft 2,000 Case 

Lineshaft pump cost $K $300 Case 

Flow per SUBMERSIBLE pump gpm/well 2,250 Case 

Additional drawdown for flow>1500 gpm ft/100 gpm - Case 

Revised pump depth ft 2,000 Calc 

Submersible pump cost $K $250 Plug 

Injection pump dP psi 100 Plug 

Injection pump cost $/hp $700 Plug 

Drawdown Rate for Flow/Well: Input: %/year 2.00 TPM 

Result A: Discounted No. of Makeup Wells number 1.3 Calc 

Result B: Loss of discounted revenue % 5.5% Calc 

Annual O&M non-labor (fraction of plant 

cost) % 1.5% TPM 

Annual O&M non-labor (fraction of field 

cost) % 1.0% Plug 

Number of O&M staff # 16.3 TPM 

B-2
Appendix C: EGS Binary Power System Case - Inputs 

Global Economic Parameters Unit Baseline Input Category 

Fixed Charge Rate Ratio 0.128 Plug 

Utilization Factor Ratio 0.95 TPM 

Contingency % 5% Plug 

Input parameters 

Temperature of GT Fluid in Reservoir Deg-C 200 Case 

Plant Size (Exclusive of Brine Pumping) MW(e) 30 Case 

Number of independent power units 3 Case 

Brine Effectiveness (exclusive of brine 

pumping) 

Calculate 

Y or N Y Case 

If N (no), enter value in cell C19 and/or 

E19 W-h/lb Case 

Calculated Brine Effectiveness W-h/lb 10.86 Calc 

Brine Effectiveness W-h/lb 10.86 TPM 

Apply improvement to reducing flow 

requirement or increasing power output 

F - flow or 

P - power P Case 

Plant Cost Calculate 

Y or N Y Case 

If N (no), enter value in cell C24 and/or 

E24 $/kW - Case 

Calculated Plant Cost $/kW $2,140 Calc 

Plant Cost $/kW $2,140 TPM 

Wells Cost Curve: 1=Low, 2=Med, 3=High 2 Case 

PRODUCTION WELL Depth Feet 13,123 Case 

Estimated Cost, from SNL Curve $K/well $4,098 Calc 

User's Cost Curve Multiplier ratio 1.20 Case 

Producer, Final Cost $K/well $4,918 TPM 

INJECTION WELL Depth Feet 13,123 Case 

Estimated Cost, from SNL Curve $K/well $4,098 Calc 

Injector, Final Cost $K/well $4,918 TPM 

Surface Equip Cost/Well $K/well $100 TPM 

Exploration Success Ratio 0.80 TPM

 Power Found MW(e) 600 Case 

Number of Confirmation wells Count 2 Case 

Confirmation Success Ratio 0.80 TPM 

Injector/Producer Ratio 0.33 Case 

Spare Prods Count - Case 

Well stimulation 

Y- yes or 

N - no Y Case 

Stimulation cost $K/well $750 TPM 

GF Pump Efficiency 80% Case 

Pump type 

L=lineshaft; 

S=submersible L 

Case 

C-1 
Global Economic Parameters Unit Baseline Input Category 

Flow per LINESHAFT pump gpm/well 332 TPM 

Inputted pump depth ft 2,000 Case 

Lineshaft pump cost $K $300 Case 

Flow per SUBMERSIBLE pump gpm/well 395 Case 

Additional drawdown for flow>1500 gpm ft/100 gpm - Case 

Pump depth ft 2,000 Calc 

Submersible pump cost $K $250 Plug 

Injection pump dP psi 100 Plug 

Injection pump cost $/hp 700 Plug 

Temperature Drawdown Rate: Input %/year 3.0 TPM 

Result A: Life of nominal reservoir years 6 Calc 

Result B: Loss of discounted revenue % 18.4% Calc 

Annual O&M non-labor (fraction of plant 

cost) % 1.5% TPM 

Annual O&M non-labor (fraction of field 

cost) % 1.0% Plug 

Number of O&M staff # 14.6 TPM 

C-2 
Appendix D: EGS Flashed-Steam Power System Case - Inputs 

Global Economic Parameters Unit Baseline Input Category 

Fixed Charge Rate Ratio 0.128 Plug 

Utilization Factor Ratio 0.90 TPM 

Contingency % 5% Plug 

Input parameters 

Temperature of GT Fluid in Reservoir Deg-C 250 Case 

ncg level ( based on total flow) ppm 200 Case 

H2S level (based on total flow) ppm 2 Case 

Number of flashes 

1= 1 flash, 

2= 2 flash 2 Case 

Plant Size (Exclusive of Brine Pumping) MW(e) 50 Case 

Number of independent power units 1 Case 

Condenser type 

S=surface; 

DC= direct 

contact S Case 

NCG Removal J = jet; 

VP=vac pump VP Case 

Brine Effectiveness (exclusive of brine 

pumping) 

Calculate 

Y or N Y Case 

If N (no), enter value in cell C24 and/or 

E24 W-h/lb Case 

Calculated Brine Effectiveness (net, no 

pumping) W-h/lb 16.28 Calc 

Brine Effectiveness (net) W-h/lb 16.28 TPM 

Apply improvement to reducing flow 

requirement or increasing power output 

F - flow or 

P - power P Case 

Plant Cost Calculate 

Y or N Y Case 

If N (no), enter value in cell C29 and/or 

E29 $/kW - Case 

Equipment cost multiplier for installed cost 2.53 Plug 

Calculated Plant Cost $/kW $940 Calc 

Plant Cost $/kW $940 TPM 

Wells Cost Curve: 1=Low, 2=Med, 

3=High 2 Case 

PRODUCTION WELL Depth Feet 19,685 Case 

Estimated Cost, from SNL Curve $K/well $10,895 Calc 

User's Cost Curve Multiplier ratio 1.15 Case 

Producer, Final Cost $K/well $12,530 TPM 

INJECTION WELL Depth Feet 19,685 Case 

Estimated Cost, from SNL Curve $K/well $10,895 Calc 

Injector, Final Cost $K/well $12,530 TPM 

Surface Equip Cost/Well $K/well $100 TPM 

D-1 
Global Economic Parameters Unit Baseline Input Category 

Exploration Success Ratio 0.80 TPM

 Power Found MW(e) 600 Case 

Number of Confirmation wells Count 2 Case 

Confirmation Success Ratio 0.80 TPM 

Injector/Producer Ratio 0.33 Case 

Spare Prods Count - Case 

Well stimulation 

Y- yes or 

N - no Y Case 

Stimulation cost $K/well $750 TPM 

Wells Pumped Y- yes or 

N - no Y Case 

Unpumped well flow rate lb/h 118,000 Case 

GF Pump Efficiency 80% Case 

Pump type 

L=lineshaft; 

S=submersible L 

Case 

Flow per LINESHAFT pump gpm/well 332 TPM 

Inputted pump depth ft 2,000 Case 

Lineshaft pump cost $K $300 Case 

Flow per SUBMERSIBLE pump gpm/well 395 Case 

Additional drawdown for flow>1500 gpm ft/100 gpm - Case 

Revised pump depth ft 2,000 Calc 

Submersible pump cost $K $250 Plug 

Injection pump dP psi 100 Plug 

Injection pump cost $/hp 700 Plug 

Drawdown Rate for Flow/Well: 

Input: %/year 15.0 TPM 

Result A: Discounted No. of Makeup Wells number 11.8 Calc 

Result B: Loss of discounted revenue % 10.2% Calc 

Annual O&M non-labor (fraction of plant 

cost) % 1.5% TPM 

Annual O&M non-labor (fraction of field 

cost) % 1.0% Plug 

Number of O&M staff # 16.3 TPM 

D-2 
Appendix E: Consensus Expert Team Scoring Matrices 

Risk Cases Considered Seven cases were evaluated for this risk analysis. The Geothermal Expert Team scored the TIO-TPM im

1. Hydrothermal Binary 2010 2. Hydrothermal Flash 2010 3. EGS Binary 2010 4. EGS Flash 2010 5. EGS Binary Evolutionary 2040 

Analysts also specifically sought to compare the projections of the Expert Team initiating this risk assessplanning projections of the GTP. To do this, two additional cases were developed to evaluate the improveresearch teams in the 2005 MYPP: 

6. Hydrothermal Binary 2010 MYPP 7. EGS Binary 2010 MYPP 

The following Excel printout lists the five sets of the Expert Team’s consensus scoring on expected reseatechnology. The scoring derived from the MYPP also is listed in the last two sets of printout sheets. The four GETEM reference cases displayed in Appendices A through D provided the baseline input data cases. The baseline data in Appendices A through D are allocated to the risk cases by corresponding subBinary, EGS Flash, etc. 

E-1 
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 1.0% 5.0% 7.0% 90% Assumed that this EGS TIO impacts the HT cConfirmation Success Ratio 0.60 1.0% 2.0% 4.0% 90% Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60 Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 500 -9.0% 0.0% 12.5% 60% Might lead to more expensive fluids and proProduction Well Flow Rate gpm/well 2,000 1.3% 4.3% 6.3% 60% Better diagnostic tools for evaluating candidTemperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60 Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 500 -6.3% 0.0% 6.3% 10% Uncertain whether there would be a reductioProduction Well Flow Rate gpm/well 2,000 2.5% 4.4% 8.8% 25% More effective fracture placementTemperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60 Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 500 -20.0% 10.0% 30.0% 10% HHP and Materials may Increase or DecreaseProduction Well Flow Rate gpm/well 2,000 10.0% 25.0% 50.0% 70% More effective fracture optimizationTemperature Drawdown Rate %/year 0.30% 4.0% 10.0% 15.0% 40%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 2- Improve fracture methods, proppants and rheologyTIO 3- Control of fracturing - new and improved borehole packersTIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEET

GETEM INPUTS/TPMs Comments

TIO 1- Increase accuracy of target temperature predictionTIO Categories Units

TIO Improvements in 2010 in % Prob. of 

Success % 

E-2
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500 -2.5% 7.5% 12.5% 20% Assumed that this EGS TIO impacts the HT cProduction Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30% 1.3% 7.3% 18.8% 20% Assumed that this EGS TIO impacts the HT cAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30% 5.0% 10.0% 20.0% 30% Assumed that this EGS TIO impacts the HT cAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000 20.0% 50.0% 75.0% 75%Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500 1.0% 12.5% 25.0% 10%Production Well Flow Rate gpm/well 2,000 1.0% 12.5% 25.0% 10%Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 5- Ability to create a subsurface circulation system as designed TIO 6- Develop numerical models that explain and extend reservoir performance TIO 7- Improve artificial lift technology TIO 8- Improve short circuit mitigation methods

E-3
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 Team notes that this is for technical systems Confirmation Success Ratio 0.60Stimulation Cost $K/well 500 10.0% 15.0% 20.0% 50% Assumed that this EGS TIO impacts the HT cProduction Well Flow Rate gpm/well 2,000 1.0% 5.0% 10.0% 70% Assumed that this EGS TIO impacts the HT cTemperature Drawdown Rate %/year 0.30% 1.0% 25.0% 75.0% 40% Assumed that this EGS TIO impacts the HT cAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 1.0% 7.0% 10.0% 25% Group feels that the Power Found variable sConfirmation Success Ratio 0.60 1.0% 5.0% 8.0% 12%Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 4.0% 6.0% 8.0% 60%Confirmation Success Ratio 0.60 7.0% 10.0% 14.0% 60%Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 5.0% 15.0% 20.0% 50% Group feels that the Power Found variable sConfirmation Success Ratio 0.60 1.0% 8.0% 15.0% 50%Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 11- Geophysical exploration methods (seismic, magnetotellurics)TIO 12- Geochemical exploration methods (isotopes, gases)TIO 9- Perform systems analysis and integrationTIO 10- Remote sensing exploration methods (InSAR, hyperspectral imaging, GPS)

E-4
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio

0.20

Really an enabling TIO that allows the other condemn the program. Industry has been puand actually drilling wells). 

Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 5.0% 8.0% 12.0% 65% ROP improvements only. Budget too low.Injector Well Cost $K/well 1,222 5.0% 8.0% 12.0% 65% 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 2.0% 6.0% 11.0% 50%

Titanium could be used in the Salton Sea welimited resource base.

Injector Well Cost $K/well 1,222 2.0% 6.0% 11.0% 50%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 2.0% 5.0% 11.0% 40% Experts would like to see more budget and eInjector Well Cost $K/well 1,222 2.0% 5.0% 11.0% 40% Experts 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 13- National geothermal assessment and supply (EGS, hydrothermal)TIO 14- Reduction of drilling time and expense, especially in hard abrasive formationsTIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material)TIO 16- Reduction of non-essential flat time

E-5
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 3.0% 7.5% 15.0% 80% Electronics development will be important foInjector Well Cost $K/well 1,222 3.0% 7.5% 15.0% 80%

Only one expert considered improvements tbeing handled under the EGS/Exploration TI

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 2.0% 4.0% 6.0% 70% According to GETEM the best we can do is 1 Injector Well Cost $K/well 1,222 2.0% 4.0% 6.0% 70% According to GETEM the bes

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5% One expert thought this TIO might have a sm

of very corrosive or very hot fields.

Number of O&M staff # 14.6

Utilization Factor % 95% 1.0% 3.0% 4.0% 90%

Brine Effectiveness W-h/lb 4.63 4.6% 10.0% 17.4% 80% Experts used the average of their independe

Plant Cost $/kW 2,445 Experts assumed the impact would be cost-n

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95% 1.0% 3.0% 4.0% 80%

Brine Effectiveness W-h/lb 4.63 3.3% 8.0% 12.5% 75% Experts strongly indicated that lower temper

Plant Cost $/kW 2,445 2.0% 5.0% 7.8% 75%

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5% 0.0% 5.0% 8.0% 50%Number of O&M staff # 14.6 Experts assumed the impact would be cost-n

TIO 19- Cycle RelatedTIO 20- Component RelatedTIO 18- Completion and production related development projectsTIO 17- Development of basic information through analysis and simulation efforts.

E-6
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 95% 0.0% 0.3% 0.5% 30%

Brine Effectiveness W-h/lb 4.63 2.5% 6.5% 10.0% 55%

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5% 2.8% 17.0% 40.0% 65%Number of O&M staff # 14.6

Utilization Factor % 95% 0.0% 2.0% 5.0% 50%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445 6.0% 16.0% 25.0% 75% One expert felt that a 50% reduction could be 

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5% Experts assumed the impact would be cost-nNumber of O&M staff # 14.6 Experts assumed the impact would be cost-n

Utilization Factor % 95% 0.5% 1.7% 2.7% 75%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445 -2.0% -1.0% -0.5% 75%

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5% -5.0% 0.0% 5.0% 65%Number of O&M staff # 14.6 20.0% 35.0% 50.0% 75%

Utilization Factor %

95% 2.5% 10.0% 16.2% 65%

Cap value at 100% for Util Factor for combinto limit improvements to 5% increase from 9

Brine Effectiveness W-h/lb 4.63 10.4% 24.5% 39.9% 70% Cap value at 25% improvement

Plant Cost $/kW 2,445 6.0% 20.0% 32.3% 75% Cap value at 50% improvement

Production Well Cost $K/well 1,222 13.3% 27.0% 44.3% 61% Mulitplicative combination of % improvemenInjector Well Cost $K/well 1,222 13.3% 27.0% 44.3% 61% Mulitplicative combination of % improvemen

Surface Equipment Cost $K/well 100 0.0% 0.0% 0.0%Exploration Success Ratio 0.20 11.0% 33.0% 45.0% 56% Cap value at 95%, if it goes over limit, proratConfirmation Success Ratio 0.60 10.0% 25.0% 41.0% 53% Cap value at 95%, if it goes over limit, proratStimulation Cost $K/well 500 -26.8% 45.0% 106.3% 27% Cap value at 75% improvementProduction Well Flow Rate gpm/well 2,000 35.8% 101.2% 175.0% 52%Temperature Drawdown Rate %/year 0.30% 11.3% 52.3% 128.8% 33% Cap value at 75% improvementAnnual O&M non-labor % 1.5% -2.3% 22.0% 53.0% 60% Cap value at 40% improvementNumber of O&M staff # 14.6 20.0% 35.0% 50.0% 75% Cap value at 50% improvement

TIO 23- Automation/Enhanced ControlsTIO 21- Monitoring & ScalingTIO 22- Design/Construction RelatedSum of TIOs

E-7
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 1.0% 5.0% 7.0% 90% Assumed that this EGS TIO impacts the HT cConfirmation Success Ratio 0.60 1.0% 2.0% 4.0% 90% Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60 Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 300 -8.8% 0.0% 12.5% 60% Might lead to more expensive fluids and propProduction Well Flow Rate gpm/well 900 1.3% 3.3% 6.3% 60% Better diagnostic tools for evaluating candidTemperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60 Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 300 -6.3% 0.0% 6.3% 10% Uncertain whether there would be a reduction Production Well Flow Rate gpm/well 900 2.5% 4.4% 8.8% 25% More effective fracture placementTemperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60 Assumed that this EGS TIO impacts the HT cStimulation Cost $K/well 300 -20.0% 10.0% 30.0% 10% HHP and Materials may Increase or DecreaseProduction Well Flow Rate gpm/well 900 10.0% 25.0% 50.0% 70% More effective fracture optimizationTemperature Drawdown Rate %/year 2.00% 4.0% 10.0% 15.0% 40%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Units

TIO Improvements in 2010 in % Prob. of 

Success % 

HYDROTHERMAL FLASH 2010- SYSTEM SCORING SHEET

GETEM INPUTS/TPMs Comments

TIO 1- Increase accuracy of target temperature predictionTIO CategoriesTIO 2- Improve fracture methods, proppants and rheologyTIO 3- Control of fracturing - new and improved borehole packersTIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

E-8
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

HYDROTHERMAL FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300 -2.5% 7.3% 12.5% 20% Assumed that this EGS TIO impacts the HT cProduction Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00% 1.3% 7.3% 18.8% 20% Assumed that this EGS TIO impacts the HT cAnnual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00% 5.0% 10.0% 20.0% 30% Assumed that this EGS TIO impacts the HT cAnnual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900 1.0% 50.0% 100.0% 10%Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300 1.0% 12.5% 25.0% 10%Production Well Flow Rate gpm/well 900 1.0% 12.5% 25.0% 10%Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 6- Develop numerical models that explain and extend reservoir performance TIO 7- Improve artificial lift technology TIO 8- Improve short circuit mitigation methodsTIO 5- Ability to create a subsurface circulation system as designed 

E-9
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

HYDROTHERMAL FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 Team notes that this is for technical systems Confirmation Success Ratio 0.60Stimulation Cost $K/well 300 10.0% 15.0% 20.0% 50% Assumed that this EGS TIO impacts the HT cProduction Well Flow Rate gpm/well 900 1.0% 5.0% 10.0% 70% Assumed that this EGS TIO impacts the HT cTemperature Drawdown Rate %/year 2.00% 1.0% 25.0% 75.0% 40% Assumed that this EGS TIO impacts the HT cAnnual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 1.0% 7.0% 10.0% 25% Group feels that the Power Found variable shConfirmation Success Ratio 0.60 1.0% 5.0% 8.0% 12%Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 4.0% 6.0% 8.0% 60%Confirmation Success Ratio 0.60 7.0% 10.0% 14.0% 60%Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 5.0% 15.0% 20.0% 50% Group feels that the Power Found variable shConfirmation Success Ratio 0.60 1.0% 8.0% 15.0% 50%Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 10- Remote sensing exploration methods (InSAR, hyperspectral imaging, GPS)TIO 11- Geophysical exploration methods (seismic, magnetotellurics)TIO 12- Geochemical exploration methods (isotopes, gases)TIO 9- Perform systems analysis and integration

E-10
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

HYDROTHERMAL FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio

0.20

Really an enabling TIO that allows the other icondemn the program. Industry has been puand actually drilling wells). 

Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910 5.0% 8.0% 12.0% 65% Experts assumed this TIO would impact the H

Injector Well Cost $K/well 1,910 5.0% 8.0% 12.0% 65% Experts assumed this TIO 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910 2.0% 6.0% 11.0% 50% Experts assumed this TIO would impact the H

Injector Well Cost $K/well 1,910 2.0% 6.0% 11.0% 50% Experts assumed this TIO 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910 2.0% 5.0% 11.0% 40% Experts assumed this TIO would impact the H

Injector Well Cost $K/well 1,910 2.0% 5.0% 11.0% 40% Experts assumed this TIO 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 14- Reduction of drilling time and expense, especially in hard abrasive formationsTIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material)TIO 16- Reduction of non-essential flat timeTIO 13- National geothermal assessment and supply (EGS, hydrothermal)

E-11
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

HYDROTHERMAL FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910 3.0% 7.5% 15.0% 80% Experts assumed this TIO would impact the H

Injector Well Cost $K/well 1,910 3.0% 7.5% 15.0% 80% Experts assumed this TIO 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995

Production Well Cost $K/well 1,910 2.0% 4.0% 6.0% 70% Experts assumed this TIO would impact the H

Injector Well Cost $K/well 1,910 2.0% 4.0% 6.0% 70% Experts assumed this TIO 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5% One expert thought this TIO might have a sm

of very corrosive or very hot fields.

Number of O&M staff # 16.3

Utilization Factor % 90% 1.0% 3.0% 4.0% 90%

Brine Effectiveness W-h/lb 9.40 1.0% 5.0% 10.0% 90%

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90% 1.0% 3.0% 5.0% 80%

Brine Effectiveness W-h/lb 9.40 2.3% 6.7% 10.0% 70% include comments on lower temp resources 

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 18- Completion and production related development projectsTIO 17- Development of basic information through analysis and simulation efforts.TIO 19- Cycle RelatedTIO 20- Component Related

E-12
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

HYDROTHERMAL FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40 0.3% 3.3% 6.7% 60%

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5% 2.8% 16.3% 26.8% 70%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40

Plant Cost $/kW 995 8.3% 18.3% 25.0% 80%

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5% 5.0% 10.0% 15.0% 80%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 9.40 1.3% 2.5% 4.0% 50%

Plant Cost $/kW 995

Production Well Cost $K/well 1,910

Injector Well Cost $K/well 1,910

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 300Production Well Flow Rate gpm/well 900Temperature Drawdown Rate %/year 2.00%Annual O&M non-labor % 1.5% 5.5% 10.0% 15.0% 80%Number of O&M staff # 16.3 20.0% 40.0% 50.0% 80% Ambiguity in the methodology, in that no atte

10% prob of success b/c no funding is curren

Utilization Factor %

90% 2.0% 6.0% 9.0% 85%

Cap value at 100% for Util Factor for combineto limit improvements to 5% increase from 95

Brine Effectiveness W-h/lb 9.40 4.9% 17.5% 30.7% 68% Cap value at 25% improvement

Plant Cost $/kW 995 8.3% 18.3% 25.0% 80% Cap value at 50% improvement

Production Well Cost $K/well 1,910 13.3% 27.0% 44.3% 61% Mulitplicative combination of % improvement

Injector Well Cost $K/well 1,910 13.3% 27.0% 44.3% 61% Mulitplicative combination of % improvement

Surface Equipment Cost $K/well 100 0.0% 0.0% 0.0%Exploration Success Ratio 0.20 11.0% 33.0% 45.0% 56% Cap value at 95%, if it goes over limit, prorate Confirmation Success Ratio 0.60 10.0% 25.0% 41.0% 53% Cap value at 95%, if it goes over limit, prorate Stimulation Cost $K/well 300 -26.5% 44.8% 106.3% 27% Cap value at 75% improvementProduction Well Flow Rate gpm/well 900 16.8% 100.2% 200.0% 41%Temperature Drawdown Rate %/year 2.00% 11.3% 52.3% 128.8% 33% Cap value at 75% improvementAnnual O&M non-labor % 1.5% 13.3% 36.3% 56.8% 77% Cap value at 40% improvementNumber of O&M staff # 16.3 20.0% 40.0% 50.0% 80% Cap value at 50% improvement

Sum of TIOsTIO 23- Automation/Enhanced ControlsTIO 21- Monitoring & ScalingTIO 22- Design/Construction Related

E-13
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 1.0% 5.0% 7.0% 90.0% Experts were assuming some indication of teConfirmation Success Ratio 0.80 1.0% 2.0% 4.0% 90.0%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 Group feels that the Power Found variable shTemperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -35.0% 0.0% 50.0% 60.0% Driven by petroleum industry. % improveme

expensive fluids and proppants.

Production Well Flow Rate gpm/well 332 5.0% 13.0% 25.0% 60.0% Driven by petroleum industry. % improveme

tools for evaluating candidates.

Temperature Drawdown Rate %/year 3.00% Technology Transfer task for petroleum to geAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80 No field work currently going on for this.Stimulation Cost $K/well 750 -25.0% 0.0% 25.0% 10.0% Uncertain whether there would be a reductioProduction Well Flow Rate gpm/well 332 10.0% 17.5% 35.0% 25.0% More effective fracture placementTemperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -20.0% 10.0% 30.0% 10.0% HHP and Materials may Increase or DecreaseProduction Well Flow Rate gpm/well 332 10.0% 25.0% 50.0% 70.0% More effective fracture optimizationTemperature Drawdown Rate %/year 3.00% 4.0% 10.0% 15.0% 40.0% Haven't been able to do the testing to see if mAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Units

TIO Improvements in 2010 in % Prob. of 

Success % 

EGS BINARY 2010- SYSTEM SCORING SHEET

GETEM INPUTS/TPMs Comments

TIO 1- Increase accuracy of target temperature predictionTIO CategoriesTIO 2- Improve fracture methods, proppants and rheologyTIO 3- Control of fracturing - new and improved borehole packersTIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

E-14
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -10.0% 30.0% 50.0% 20.0% Low prob of success because of no budget fProduction Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 5.0% 30.0% 75.0% 20.0% Low prob of success because of no budget fAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 5.0% 10.0% 20.0% 30.0% Low prob of success because of no budget fAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 1.0% 50.0% 200.0% 15.0% Low prob of success because of no budget fTemperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% Team thinks this TIO will have an impact on nNumber of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 1.0% 25.0% 50.0% 10.0% Enabling TIO that will allow other TIOs to impProduction Well Flow Rate gpm/well 332 1.0% 50.0% 100.0% 10.0% Low prob of success because of no budget fTemperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 6- Develop numerical models that explain and extend reservoir performance TIO 7- Improve artificial lift technology TIO 8- Improve short circuit mitigation methodsTIO 5- Ability to create a subsurface circulation system as designed 

E-15
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 Team notes that this is for technical systems Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 10.0% 15.0% 20.0% 50.0%Production Well Flow Rate gpm/well 332 1.0% 5.0% 10.0% 70.0%Temperature Drawdown Rate %/year 3.00% 1.0% 25.0% 75.0% 40.0% Low prob of success because of no budget fAnnual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 1.0% 7.0% 10.0% 25% Group feels that the Power Found variable shConfirmation Success Ratio 0.80 1.0% 5.0% 8.0% 12%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 4.0% 6.0% 8.0% 60%Confirmation Success Ratio 0.80 7.0% 10.0% 14.0% 60%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 5.0% 15.0% 20.0% 50% Group feels that the Power Found variable shConfirmation Success Ratio 0.80 1.0% 8.0% 15.0% 50%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 10- Remote sensing exploration methods (InSAR, hyperspectral imaging, GPS)TIO 11- Geophysical exploration methods (seismic, magnetotellurics)TIO 12- Geochemical exploration methods (isotopes, gases)TIO 9- Perform systems analysis and integration

E-16
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio

0.80

Really an enabling TIO that allows the other icondemn the program. Industry has been puand actually drilling wells). 

Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 5.0% 12.0% 20.0% 65%Injector Well Cost $K/well 4,918 5.0% 12.0% 20.0% 65%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 4.0% 10.0% 15.0% 50%Injector Well Cost $K/well 4,918 4.0% 10.0% 15.0% 50%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 2.0% 4.0% 10.0% 50%Injector Well Cost $K/well 4,918 2.0% 4.0% 10.0% 50%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 14- Reduction of drilling time and expense, especially in hard abrasive formationsTIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material)TIO 16- Reduction of non-essential flat timeTIO 13- National geothermal assessment and supply (EGS, hydrothermal)

E-17
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 4.0% 8.0% 12.0% 75%Injector Well Cost $K/well 4,918 4.0% 8.0% 12.0% 75.0% More interested in rock mechanics in EGS case 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 2.5% 4.0% 7.0% 60%Injector Well Cost $K/well 4,918 2.5% 4.0% 7.0% 60%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% One expert thought this TIO might have a sm

of very corrosive or very hot fields.

Number of O&M staff # 14.6

Utilization Factor %

95% 1.0% 3.0% 4.0% 90%

Some experts were concerned that a 200C rebetter for flashed-steam technology, but anopressure must be maintained.

Brine Effectiveness W-h/lb 10.86 10.0% 25.0% 40.0% 90% There are opportunities to optimize plant conPlant Cost $/kW 2,140 -10.0% 10.0% 30.0% 30%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95% 1.0% 3.0% 4.0% 80%

Brine Effectiveness W-h/lb 10.86 3.3% 8.0% 12.5% 75%Plant Cost $/kW 2,140 2.0% 5.0% 8.0% 75%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% 0.0% 5.0% 8.0% 50%Number of O&M staff # 14.6

TIO 18- Completion and production related development projectsTIO 17- Development of basic information through analysis and simulation efforts.TIO 19- Cycle RelatedTIO 20- Component Related

E-18
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95% 0.0% 0.3% 0.5% 30%

Brine Effectiveness W-h/lb 10.86 2.5% 6.5% 10.0% 55%Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% 2.8% 17.0% 40.0% 65%Number of O&M staff # 14.6

Utilization Factor % 95% 0.0% 2.0% 5.0% 50%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140 6.0% 16.0% 25.0% 75%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95% 0.5% 1.7% 2.7% 75%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140 -2.0% -1.0% -0.5% 75%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% -5.0% 0.0% 5.0% 65%Number of O&M staff # 14.6 20.0% 35.0% 50.0% 75%

Utilization Factor %

95% 2.5% 10.0% 16.2% 65%

Cap value at 100% for Util Factor for combineto limit improvements to 5% increase from 95

Brine Effectiveness W-h/lb 10.86 15.8% 39.5% 62.5% 73% Cap value at 25% improvementPlant Cost $/kW 2,140 -4.0% 30.0% 62.5% 64% Cap value at 50% improvementProduction Well Cost $K/well 4,918 16.3% 32.8% 49.9% 60% Mulitplicative combination of % improvemenInjector Well Cost $K/well 4,918 16.3% 32.8% 49.9% 60% Mulitplicative combination of % improvemen

Surface Equipment Cost $K/well 100 0.0% 0.0% 0.0%Exploration Success Ratio 0.80 11.0% 33.0% 45.0% 56% Cap value at 95%, if it goes over limit, prorate Confirmation Success Ratio 0.80 10.0% 25.0% 41.0% 53% Cap value at 95%, if it goes over limit, prorate Stimulation Cost $K/well 750 -79.0% 80.0% 225.0% 27% Cap value at 75% improvementProduction Well Flow Rate gpm/well 332 28.0% 160.5% 420.0% 42%Temperature Drawdown Rate %/year 3.00% 15.0% 75.0% 185.0% 33% Cap value at 75% improvementAnnual O&M non-labor % 1.5% -2.3% 22.0% 53.0% 60% Cap value at 40% improvementNumber of O&M staff # 14.6 20.0% 35.0% 50.0% 75% Cap value at 50% improvement

Sum of TIOsTIO 23- Automation/Enhanced ControlsTIO 21- Monitoring & ScalingTIO 22- Design/Construction Related

E-19
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 1.0% 5.0% 7.0% 90% Assumed that this EGS TIO impacts the EGS FConfirmation Success Ratio 0.80 1.0% 2.0% 4.0% 90% Assumed that this EGS TIO impacts the EGS FStimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80 Assumed that this EGS TIO impacts the EGS FStimulation Cost $K/well 750 -8.8% 0.0% 12.5% 60% Driven by petroleum industry. % improvemen

expensive fluids and proppants.

Production Well Flow Rate gpm/well 332 1.3% 3.3% 6.3% 60% Driven by petroleum industry. % improvemen

tools for evaluating candidates.

Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80 Assumed that this EGS TIO impacts the EGS FStimulation Cost $K/well 750 -6.3% 0.0% 6.3% 10% Uncertain whether there would be a reduction Production Well Flow Rate gpm/well 332 2.5% 4.4% 8.8% 25% More effective fracture placementTemperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80 Assumed that this EGS TIO impacts the EGS FStimulation Cost $K/well 750 -20.0% 10.0% 30.0% 10% HHP and Materials may Increase or DecreaseProduction Well Flow Rate gpm/well 332 10.0% 25.0% 50.0% 70% More effective fracture optimizationTemperature Drawdown Rate %/year 15.0% 4.0% 10.0% 15.0% 40% Haven't been able to do the testing to see if moAnnual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 2- Improve fracture methods, proppants and rheologyTIO 3- Control of fracturing - new and improved borehole packersTIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

EGS FLASH 2010- SYSTEM SCORING SHEET

GETEM INPUTS/TPMs Comments

TIO 1- Increase accuracy of target temperature predictionTIO Categories Units

TIO Improvements in 2010 in % Prob. of 

Success % 

E-20
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

EGS FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -2.5% 7.3% 12.5% 20% Assumed that this EGS TIO impacts the EGS FProduction Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0% 1.3% 7.3% 18.8% 20% Assumed that this EGS TIO impacts the EGS FAnnual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0% 5.0% 10.0% 20.0% 30% Assumed that this EGS TIO impacts the EGS FAnnual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 1.0% 50.0% 100.0% 5%Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 1.0% 12.5% 25.0% 10%Production Well Flow Rate gpm/well 332 1.0% 12.5% 25.0% 10% Assumed that this EGS TIO impacts the EGS FTemperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 5- Ability to create a subsurface circulation system as designed TIO 6- Develop numerical models that explain and extend reservoir performance TIO 7- Improve artificial lift technology TIO 8- Improve short circuit mitigation methods

E-21
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

EGS FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 10.0% 15.0% 20.0% 50% Team notes that this is for technical systems aProduction Well Flow Rate gpm/well 332 1.0% 5.0% 10.0% 70%Temperature Drawdown Rate %/year 15.0% 1.0% 25.0% 75.0% 40%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 1.0% 7.0% 10.0% 25% Group feels that the Power Found variable shoConfirmation Success Ratio 0.80 1.0% 5.0% 8.0% 12%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 4.0% 6.0% 8.0% 60%Confirmation Success Ratio 0.80 7.0% 10.0% 14.0% 60%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 5.0% 15.0% 20.0% 50% Group feels that the Power Found variable shoConfirmation Success Ratio 0.80 1.0% 8.0% 15.0% 50%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 11- Geophysical exploration methods (seismic, magnetotellurics)TIO 12- Geochemical exploration methods (isotopes, gases)TIO 9- Perform systems analysis and integrationTIO 10- Remote sensing exploration methods (InSAR, hyperspectral imaging, GPS)

E-22
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

EGS FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio

0.80

Really an enabling TIO that allows the other imcondemn the program. Industry has been pusand actually drilling wells). 

Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530 5.0% 12.0% 20.0% 65% Experts assumed this TIO would impact the EG

Injector Well Cost $K/well 12,530 5.0% 12.0% 20.0% 65% Experts assumed this TIO wou

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530 6.0% 13.0% 18.0% 50%

One expert thought that "robust hard rock unddrilling, minimum clearance casing design" is is not currently being funded.

Injector Well Cost $K/well 12,530 6.0% 13.0% 18.0% 50% Experts assumed this TIO wou

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530 2.0% 4.0% 10.0% 50% Experts assumed this TIO would impact the EG

Injector Well Cost $K/well 12,530 2.0% 4.0% 10.0% 50% Experts assumed this TIO wou

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 13- National geothermal assessment and supply (EGS, hydrothermal)TIO 14- Reduction of drilling time and expense, especially in hard abrasive formationsTIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material)TIO 16- Reduction of non-essential flat time

E-23
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

EGS FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530 4.0% 8.0% 12.0% 75% Experts assumed this TIO would impact the EG

Injector Well Cost $K/well 12,530 4.0% 8.0% 12.0% 75% Experts assumed this TIO wou

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940

Production Well Cost $K/well 12,530 2.0% 3.5% 6.0% 60%

Injector Well Cost $K/well 12,530 2.0% 3.5% 6.0% 60%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5% One expert thought this TIO might have a sma

of very corrosive or very hot fields.

Number of O&M staff # 16.3

Utilization Factor % 90% 1.0% 3.0% 4.0% 90% Experts assumed the same improvements and 

Brine Effectiveness W-h/lb 16.28 1.0% 5.0% 10.0% 90% Experts assumed the same improvements and Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

Utilization Factor % 90% 1.0% 3.0% 5.0% 80% Experts assumed the same improvements and 

Brine Effectiveness W-h/lb 16.28 2.3% 6.7% 10.0% 70% Experts assumed the same improvements and Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5%Number of O&M staff # 16.3

TIO 19- Cycle RelatedTIO 20- Component RelatedTIO 18- Completion and production related development projectsTIO 17- Development of basic information through analysis and simulation efforts.

E-24
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

EGS FLASH 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2010 in % Prob. of 

Success % 

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28 0.3% 3.3% 6.7% 60% Experts assumed the same improvements and Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5% 3.0% 16.3% 26.8% 70% Experts assumed the same improvements and Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28Plant Cost $/kW 940 8.3% 18.3% 25.0% 80% Experts assumed the same improvements and 

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5% 5.0% 10.0% 15.0% 80% Experts assumed the same improvements and Number of O&M staff # 16.3

Utilization Factor % 90%

Brine Effectiveness W-h/lb 16.28 1.3% 2.5% 4.0% 50% Experts assumed the same improvements and Plant Cost $/kW 940

Production Well Cost $K/well 12,530

Injector Well Cost $K/well 12,530

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 15.0%Annual O&M non-labor % 1.5% 5.5% 10.0% 15.0% 80% Experts assumed the same improvements and Number of O&M staff # 16.3 20.0% 40.0% 50.0% 80% Experts assumed the same improvements and 

Utilization Factor %

90% 2.0% 6.0% 9.0% 85%

Cap value at 100% for Util Factor for combined to limit improvements to 5% increase from 95% 

Brine Effectiveness W-h/lb 16.28 4.9% 17.5% 30.7% 68% Cap value at 25% improvementPlant Cost $/kW 940 8.3% 18.3% 25.0% 80% Cap value at 50% improvement

Production Well Cost $K/well 12,530 17.7% 34.7% 51.2% 60% Mulitplicative combination of % improvements 

Injector Well Cost $K/well 12,530 17.7% 34.7% 51.2% 60% Mulitplicative combination of % improvements 

Surface Equipment Cost $K/well 100 0.0% 0.0% 0.0%Exploration Success Ratio 0.80 11.0% 33.0% 45.0% 56% Cap value at 95%, if it goes over limit, prorate Confirmation Success Ratio 0.80 10.0% 25.0% 41.0% 53% Cap value at 95%, if it goes over limit, prorate Stimulation Cost $K/well 750 -26.5% 44.8% 106.3% 27% Cap value at 75% improvementProduction Well Flow Rate gpm/well 332 16.8% 100.2% 200.0% 40%Temperature Drawdown Rate %/year 15.0% 11.3% 52.3% 128.8% 33% Cap value at 75% improvementAnnual O&M non-labor % 1.5% 13.5% 36.3% 56.8% 77% Cap value at 40% improvementNumber of O&M staff # 16.3 20.0% 40.0% 50.0% 80% Cap value at 50% improvement

TIO 23- Automation/Enhanced ControlsTIO 21- Monitoring & ScalingTIO 22- Design/Construction RelatedSum of TIOs

E-25
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 2.0% 10.0% 14.0% 90% Experts assumed double improvement range

be atleast 60%

Confirmation Success Ratio 0.80 2.0% 4.0% 8.0% 90% Experts assumed double improvement range

be atleast 60%

Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -17.5% 0.0% 75.0% 60% Experts assumed double improvement range

be atleast 60%

Production Well Flow Rate gpm/well 332 10.0% 25.0% 50.0% 60% Experts assumed double improvement range

be atleast 60%

Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -12.5% 0.0% 50.0% 60% Experts assumed double improvement range

be atleast 60%

Production Well Flow Rate gpm/well 332 20.0% 35.0% 70.0% 60% Experts assumed double improvement range

be atleast 60%

Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -10.0% 20.0% 60.0% 60% Experts assumed double improvement range

be atleast 60%

Production Well Flow Rate gpm/well 332 20.0% 50.0% 100.0% 70% Experts assumed double improvement range

be atleast 60%

Temperature Drawdown Rate %/year 3.00% 8.0% 20.0% 30.0% 60% Experts assumed double improvement range

be atleast 60%

Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 2- Improve fracture methods, proppants and rheologyTIO 3- Control of fracturing - new and improved borehole packersTIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

Evolutionary EGS Binary 2040 4000m at 200C- SYSTEM SCORING SH

GETEM INPUTS/TPMs Comments

TIO 1- Increase accuracy of target temperature predictionTIO Categories Units

TIO Improvements in 2040 in % Prob. of 

Success % 

E-26
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Evolutionary EGS Binary 2040 4000m at 200C- SYSTEM SCORING SH

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2040 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 -5.0% 60.0% 75.0% 60% Experts assumed double improvement range

be atleast 60%

Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 10.0% 60.0% 75.0% 60% Experts assumed double improvement range

be atleast 60%

Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 10.0% 20.0% 40.0% 60% Experts assumed double improvement range

be atleast 60%

Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 2.0% 100.0% 400.0% 60% Experts assumed double improvement range

be atleast 60%

Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 2.0% 50.0% 75.0% 60% Experts assumed double improvement range

be atleast 60%

Production Well Flow Rate gpm/well 332 2.0% 100.0% 200.0% 60% Experts assumed double improvement range

be atleast 60%

Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 5- Ability to create a subsurface circulation system as designed TIO 6- Develop numerical models that explain and extend reservoir performance TIO 7- Improve artificial lift technology TIO 8- Improve short circuit mitigation methods

E-27
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Evolutionary EGS Binary 2040 4000m at 200C- SYSTEM SCORING SH

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2040 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750 20.0% 30.0% 40.0% 60% Experts assumed double improvement range

be atleast 60%

Production Well Flow Rate gpm/well 332 2.0% 10.0% 20.0% 70% Experts assumed double improvement range

be atleast 60%

Temperature Drawdown Rate %/year 3.00% 2.0% 50.0% 75.0% 60%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 2.0% 14.0% 20.0% 60% Experts assumed double improvement range

be atleast 60%

Confirmation Success Ratio 0.80 2.0% 10.0% 16.0% 60% Experts assumed double improvement range

be atleast 60%

Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 8.0% 12.0% 16.0% 60% Experts assumed double improvement range

be atleast 60%

Confirmation Success Ratio 0.80 14.0% 20.0% 28.0% 60% Experts assumed double improvement range

be atleast 60%

Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 10.0% 30.0% 60.0% 60% Experts assumed double improvement range

be atleast 60%

Confirmation Success Ratio 0.80 2.0% 16.0% 30.0% 60% Experts assumed double improvement range

be atleast 60%

Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 11- Geophysical exploration methods (seismic, magnetotellurics)TIO 12- Geochemical exploration methods (isotopes, gases)TIO 9- Perform systems analysis and integrationTIO 10- Remote sensing exploration methods (InSAR, hyperspectral imaging, GPS)

E-28
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Evolutionary EGS Binary 2040 4000m at 200C- SYSTEM SCORING SH

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2040 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio

0.80

Really an enabling TIO that allows the other imcondemn the program. Industry has been puand actually drilling wells). 

Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 5.0% 15.0% 20.0% 80%

Experts assumed for this TIO there would be for the 2040 timeframe relative to EGS Binary 

Injector Well Cost $K/well 4,918 5.0% 15.0% 20.0% 80%

Experts assumed for this TIO there would be 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 4.0% 15.0% 20.0% 75%

Experts assumed for this TIO there would be for the 2040 timeframe relative to EGS Binary 

Injector Well Cost $K/well 4,918 4.0% 15.0% 20.0% 75%

Experts assumed for this TIO there would be 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 2.0% 4.0% 10.0% 50%

Experts assumed for this TIO there would be 2040 timeframe relative to EGS Binary 2010 c

Injector Well Cost $K/well 4,918 2.0% 4.0% 10.0% 50%

Experts assumed for this TIO there would be 

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 13- National geothermal assessment and supply (EGS, hydrothermal)TIO 14- Reduction of drilling time and expense, especially in hard abrasive formationsTIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material)TIO 16- Reduction of non-essential flat time

E-29
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Evolutionary EGS Binary 2040 4000m at 200C- SYSTEM SCORING SH

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2040 in % Prob. of 

Success % 

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 4.0% 12.0% 15.0% 75%

Experts assumed for this TIO there would be improvements for the 2040 timeframe relative 

Injector Well Cost $K/well 4,918 4.0% 12.0% 15.0% 75%

Experts assumed for this TIO th

improv

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 2.5% 4.0% 7.0% 70%

Experts assumed for this TIO there would be improvements for the 2040 timeframe relative 

Injector Well Cost $K/well 4,918 2.5% 4.0% 7.0% 70%

Experts assumed for this TIO th

improv

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95% 1.0% 3.0% 4.0% 90% Experts assumed the same improvements an

noted.

Brine Effectiveness W-h/lb 10.86 10.0% 25.0% 40.0% 90% Can always add thermal efficiency at increasePlant Cost $/kW 2,140 -10.0% 10.0% 30.0% 30% Experts suggested the need to focus on lowe

plant cost baseline may be too high.

Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95% 1.0% 3.0% 4.0% 80%

Brine Effectiveness W-h/lb 10.86 3.3% 8.0% 12.5% 75%Plant Cost $/kW 2,140 2.0% 5.0% 7.8% 75%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% 0.0% 5.0% 8.0% 50%Number of O&M staff # 14.6

TIO 19- Cycle RelatedTIO 20- Component RelatedTIO 18- Completion and production related development projectsTIO 17- Development of basic information through analysis and simulation efforts.

E-30
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Evolutionary EGS Binary 2040 4000m at 200C- SYSTEM SCORING SH

TIO Categories GETEM INPUTS/TPMs Units Comments

TIO Improvements in 2040 in % Prob. of 

Success % 

Utilization Factor % 95% 0.0% 0.3% 0.5% 30%

Brine Effectiveness W-h/lb 10.86 2.5% 6.5% 10.0% 55%Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% 2.8% 17.0% 40.0% 65%Number of O&M staff # 14.6

Utilization Factor % 95% 0.0% 2.0% 5.0% 50%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140 6.0% 16.0% 25.0% 75%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95% 0.5% 1.7% 2.7% 75%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140 -2.0% -1.0% -0.5% 75%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% -5.0% 0.0% 5.0% 65%Number of O&M staff # 14.6 20.0% 35.0% 50.0% 75%

Utilization Factor %

95% 2.5% 10.0% 16.2% 65%

Cap value at 100% for Util Factor for combineto limit improvements to 5% increase from 95

Brine Effectiveness W-h/lb 10.86 15.8% 39.5% 62.5% 73% Cap value at 25% improvementPlant Cost $/kW 2,140 -4.0% 30.0% 62.3% 64% Cap value at 50% improvementProduction Well Cost $K/well 4,918 16.3% 41.4% 54.5% 70% Mulitplicative combination of % improvementInjector Well Cost $K/well 4,918 16.3% 41.4% 54.5% 70% Mulitplicative combination of % improvement

Surface Equipment Cost $K/well 100 0.0% 0.0% 0.0%Exploration Success Ratio 0.80 22.0% 66.0% 110.0% 68% Cap value at 95%, if it goes over limit, prorate Confirmation Success Ratio 0.80 20.0% 50.0% 82.0% 68% Cap value at 95%, if it goes over limit, prorate Stimulation Cost $K/well 750 -23.0% 160.0% 375.0% 60% Cap value at 75% improvementProduction Well Flow Rate gpm/well 332 56.0% 320.0% 840.0% 63%Temperature Drawdown Rate %/year 3.00% 30.0% 150.0% 220.0% 60% Cap value at 75% improvementAnnual O&M non-labor % 1.5% -2.3% 22.0% 53.0% 60% Cap value at 40% improvementNumber of O&M staff # 14.6 20.0% 35.0% 50.0% 75% Cap value at 50% improvement

TIO 23- Automation/Enhanced ControlsTIO 21- Monitoring & ScalingTIO 22- Design/Construction RelatedSum of TIOs

E-31
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 6.0% 8.0% 10.0% 65%Confirmation Success Ratio 0.60 6.0% 8.0% 10.0% 65%Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000 9.8% 13.0% 16.3% 85%Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000 3.8% 5.0% 6.3% 85%Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30% 3.6% 4.8% 6.0% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Units

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEE

GETEM INPUTS/TPMs Comments

TIO 1- Increase accuracy of target temperature predictionTIO CategoriesTIO 2- Improve fracture methods, proppants and rheologyTIO 3- Control of fracturing - new and improved borehole packersTIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

E-32
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEE

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30% 6.8% 9.1% 11.4% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30% 4.2% 5.7% 7.1% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000 7.5% 10.0% 12.5% 85%Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30% 6.8% 9.1% 11.4% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 6- Develop numerical models that explain and extend reservoir performance TIO 7- Improve artificial lift technology TIO 8- Improve short circuit mitigation methodsTIO 5- Ability to create a subsurface circulation system as designed 

E-33
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEE

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000 3.0% 4.0% 5.0% 85%Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 1.5% 2.0% 2.5% 65%Confirmation Success Ratio 0.60 1.5% 2.0% 2.5% 65%Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 12.0% 16.0% 20.0% 65%Confirmation Success Ratio 0.60 11.9% 15.8% 19.8% 65%Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20 1.5% 2.0% 2.5% 65%Confirmation Success Ratio 0.60 1.5% 2.0% 2.5% 65%Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 10- Remote sensing exploration methods (InSAR, hyperspectral imaging, GPS)TIO 11- Geophysical exploration methods (seismic, magnetotellurics)TIO 12- Geochemical exploration methods (isotopes, gases)TIO 9- Perform systems analysis and integration

E-34
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEE

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 6.2% 15.4% 75%Injector Well Cost $K/well 1,222 6.2% 15.4% 75%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 1.0% 4.4% 75%Injector Well Cost $K/well 1,222 1.0% 4.4% 75%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222 5.2% 11.0% 75%Injector Well Cost $K/well 1,222 5.2% 11.0% 75%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 14- Reduction of drilling time and expense, especially in hard abrasive formationsTIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material)TIO 16- Reduction of non-essential flat timeTIO 13- National geothermal assessment and supply (EGS, hydrothermal)

E-35
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEE

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63 10.1% 13.5% 16.9% 100%

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63 4.9% 6.5% 13.1% 100%

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 18- Completion and production related development projectsTIO 17- Development of basic information through analysis and simulation efforts.TIO 19- Cycle RelatedTIO 20- Component Related

E-36
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP HYDROTHERMAL BINARY 2010- SYSTEM SCORING SHEE

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5% 46.4% 58.0% 72.5% 100%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445 15.0% 18.0% 22.6% 100%

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 4.63

Plant Cost $/kW 2,445

Production Well Cost $K/well 1,222Injector Well Cost $K/well 1,222

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.20Confirmation Success Ratio 0.60Stimulation Cost $K/well 500Production Well Flow Rate gpm/well 2,000Temperature Drawdown Rate %/year 0.30%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6 40.0% 50.0% 62.5% 100%

Utilization Factor %

95% 0.0% 0.0% 0.0%

Cap value at 100% for Util Factor for combinto limit improvements to 5% increase from 9

Brine Effectiveness W-h/lb 4.63 15.0% 20.0% 30.0% 100% Cap value at 25% improvement

Plant Cost $/kW 2,445 15.0% 18.0% 22.6% 100% Cap value at 50% improvement

Production Well Cost $K/well 1,222 12.0% 0.0% 28.0% 75% Mulitplicative combination of % improvemenInjector Well Cost $K/well 1,222 12.0% 0.0% 28.0% 75% Mulitplicative combination of % improvemen

Surface Equipment Cost $K/well 100 0.0% 0.0% 0.0%Exploration Success Ratio 0.20 21.0% 28.0% 35.0% 65% Cap value at 95%, if it goes over limit, proratConfirmation Success Ratio 0.60 20.9% 27.8% 34.8% 65% Cap value at 95%, if it goes over limit, proratStimulation Cost $K/well 500 0.0% 0.0% 0.0% Cap value at 75% improvementProduction Well Flow Rate gpm/well 2,000 24.0% 32.0% 40.0% 85%Temperature Drawdown Rate %/year 0.30% 21.5% 28.6% 35.8% 85% Cap value at 75% improvementAnnual O&M non-labor % 1.5% 46.4% 58.0% 72.5% 100% Cap value at 40% improvementNumber of O&M staff # 14.6 40.0% 50.0% 62.5% 100% Cap value at 50% improvement

Sum of TIOsTIO 23- Automation/Enhanced ControlsTIO 21- Monitoring & ScalingTIO 22- Design/Construction Related

E-37
Appendix E- Expert Team Consensus Estimates

Baseline

in 2005 Minimum % Expected % Maximum %

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 6.0% 8.0% 10.0% 85%Confirmation Success Ratio 0.80 6.0% 8.0% 10.0% 85%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 9.8% 13.0% 16.3% 85%Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 3.8% 5.0% 6.3% 85%Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 3.6% 4.8% 6.0% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Units

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP EGS BINARY 2010- SYSTEM SCORING SHEET

GETEM INPUTS/TPMs Comments

TIO 1- Increase accuracy of target temperature predictionTIO CategoriesTIO 2- Improve fracture methods, proppants and rheologyTIO 3- Control of fracturing - new and improved borehole packersTIO 4- Develop numerical models that accurately predict fracture growth and permeability development 

E-38
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 6.8% 9.1% 11.4% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 4.2% 5.7% 7.1% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 7.5% 10.0% 12.5% 85%Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00% 6.8% 9.1% 11.4% 85%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 6- Develop numerical models that explain and extend reservoir performance TIO 7- Improve artificial lift technology TIO 8- Improve short circuit mitigation methodsTIO 5- Ability to create a subsurface circulation system as designed 

E-39
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332 3.0% 4.0% 5.0% 85%Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 1.5% 2.0% 2.5% 65%Confirmation Success Ratio 0.80 1.5% 2.0% 2.5% 65%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 12.0% 16.0% 20.0% 65%Confirmation Success Ratio 0.80 11.9% 15.8% 19.8% 65%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80 1.5% 2.0% 2.5% 65%Confirmation Success Ratio 0.80 1.5% 2.0% 2.5% 65%Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 10- Remote sensing exploration methods (InSAR, hyperspectral imaging, GPS)TIO 11- Geophysical exploration methods (seismic, magnetotellurics)TIO 12- Geochemical exploration methods (isotopes, gases)TIO 9- Perform systems analysis and integration

E-40
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 8.2% 15.4% 75%Injector Well Cost $K/well 4,918 8.2% 15.4% 75%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 1.0% 8.8% 75%Injector Well Cost $K/well 4,918 1.0% 8.8% 75%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918 3.1% 6.6% 75%Injector Well Cost $K/well 4,918 3.1% 6.6% 75%

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 14- Reduction of drilling time and expense, especially in hard abrasive formationsTIO 15- Reduction time and expense to line the wellbore (including using less material and less costly material)TIO 16- Reduction of non-essential flat timeTIO 13- National geothermal assessment and supply (EGS, hydrothermal)

E-41
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86 10.1% 13.5% 16.9% 100%Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86 4.9% 6.5% 13.1% 100%Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

TIO 18- Completion and production related development projectsTIO 17- Development of basic information through analysis and simulation efforts.TIO 19- Cycle RelatedTIO 20- Component Related

E-42
Appendix E- Expert Team Consensus Estimates

Baseline

Units in 2005 Minimum % Expected % Maximum %

TIO Improvements in 2010 in % Prob. of 

Success % 

MYPP EGS BINARY 2010- SYSTEM SCORING SHEET

TIO Categories GETEM INPUTS/TPMs Comments

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5% 46.4% 58.0% 72.5% 100%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140 15.0% 18.0% 22.6% 100%Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6

Utilization Factor % 95%

Brine Effectiveness W-h/lb 10.86Plant Cost $/kW 2,140Production Well Cost $K/well 4,918Injector Well Cost $K/well 4,918

Surface Equipment Cost $K/well 100Exploration Success Ratio 0.80Confirmation Success Ratio 0.80Stimulation Cost $K/well 750Production Well Flow Rate gpm/well 332Temperature Drawdown Rate %/year 3.00%Annual O&M non-labor % 1.5%Number of O&M staff # 14.6 40.0% 50.0% 62.5% 100%

Utilization Factor %

95% 0.0% 0.0% 0.0%

Cap value at 100% for Util Factor for combinto limit improvements to 5% increase from 9

Brine Effectiveness W-h/lb 10.86 15.0% 20.0% 30.0% 100% Cap value at 25% improvementPlant Cost $/kW 2,140 15.0% 18.0% 22.6% 100% Cap value at 50% improvementProduction Well Cost $K/well 4,918 12.0% 0.0% 28.0% 75% Mulitplicative combination of % improvemeInjector Well Cost $K/well 4,918 12.0% 0.0% 28.0% 75% Mulitplicative combination of % improveme

Surface Equipment Cost $K/well 100 0.0% 0.0% 0.0%Exploration Success Ratio 0.80 21.0% 28.0% 35.0% 70% Cap value at 95%, if it goes over limit, proraConfirmation Success Ratio 0.80 20.9% 27.8% 34.8% 70% Cap value at 95%, if it goes over limit, proraStimulation Cost $K/well 750 0.0% 0.0% 0.0% Cap value at 75% improvementProduction Well Flow Rate gpm/well 332 24.0% 32.0% 40.0% 85%Temperature Drawdown Rate %/year 3.00% 21.5% 28.6% 35.8% 85% Cap value at 75% improvementAnnual O&M non-labor % 1.5% 46.4% 58.0% 72.5% 100% Cap value at 40% improvementNumber of O&M staff # 14.6 40.0% 50.0% 62.5% 100% Cap value at 50% improvement

Sum of TIOsTIO 23- Automation/Enhanced ControlsTIO 21- Monitoring & ScalingTIO 22- Design/Construction Related

E-43
 Mean=3.426597 

2.8 3.15 3.5 3.85 4.2

 Mean=4.732055 

3.5 4.5 5.5 6.5

Appendix F: Cumulative Probability Distribution Functions of LCOE by Case 

Distribution for Imp Bin- Total COE/L64 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

3.5 4.5 5.5 6.5

 5% 90% 5%

 4.1781 5.4059 

 Mean=4.732055 

Figure F1. Hydrothermal Binary 2010 Experts Case LCOE (¢/kWh) 

 Distribution for Imp FL- Total COE/L71 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

2.8 3.15 3.5 3.85 4.2

 5% 90% 5%

 3.1327 3.7698 

 Mean=3.426597 

Figure F2. Hydrothermal Flash 2010 Experts Case LCOE (¢/kWh)

F-1 
 Mean=15.56329 

8 12 16 20 24

 Mean=11.53538 

4 8 12 16 20

Distribution for Imp Bin- Total COE/L64 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

4 8 12 16 20

 5% 90% 5%

 7.97 15.3293 

 Mean=11.53538 

Figure F3. EGS Binary 2010 Experts Case LCOE (¢/kWh) 

 Distribution for Imp FL- Total COE/L71 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

8 12 16 20 24

 5% 90% 5%

 11.9952 19.5671 

 Mean=15.56329 

Figure F4. EGS Flash 2010 Experts Case LCOE (¢/kWh)

F-2
 Mean=6.289409 

3 5.75 8.5 11.25 14

Distribution for Imp Bin- Total COE/L64 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

3 5.75 8.5 11.25 14

 5% 90% 5%

 4.5882 8.8342 

Mean=6.289409 

Figure F5. Evolutionary EGS Binary 2040 Experts Case LCOE (¢/kWh) 

F-3
 Mean=14.31604 

12 14 16 18

 Mean=4.735013 

4.3 4.525 4.75 4.975 5.2

Distribution for Imp Bin- Total COE/L64 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

4.3 4.525 4.75 4.975 5.2

 5% 90% 5%

 4.5489 4.9193 

 Mean=4.735013 

Figure F6. Hydrothermal Binary 2010 MYPP Case LCOE (¢/kWh) 

Distribution for Imp Bin- Total COE/L64 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

12 14 16 18

 5% 90% 5%

 13.0433 15.8276 

 Mean=14.31604 

Figure F7. EGS Binary 2010 MYPP Case LCOE (¢/kWh) 

F-4
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March 2007 

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Technical Report 

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4. TITLE AND SUBTITLE 

Preliminary Technical Risk Analysis for the Geothermal 

Technologies Program 

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DE-AC36-99-GO10337 

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6. AUTHOR(S) 

J. McVeigh and J. Cohen (PERI); 

M. Vorum, G. Porro, and G. Nix (NREL) 

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NREL/TP-640-41156 

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GT04.1101 

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This report explains the goals, methods, and results of a probabilistic analysis of technical risk for a portfolio of R&D 

projects in the DOE Geothermal Technologies Program (The “Program”). The analysis is a task by Princeton Energy 

Resources International, LLC (PERI), in support of the National Renewable Energy Laboratory (NREL) on behalf of 

the Program. The main challenge in the analysis lies in translating R&D results to a quantitative reflection of technical 

risk for a key Program metric: levelized cost of energy (LCOE). This requires both computational development (i.e., 

creating a spreadsheet-based analysis tool) and a synthesis of judgments by a panel of researchers and experts of 

the expected results of the Program’s R&D. 

15. SUBJECT TERMS 

NREL; geothermal; Geothermal Technologies Program; risk analysis; research; levelized cost of energy; LCOE; 

Geothermal Electric Technology Evaluation Model; GETEM; technology improvement opportunities; PERI; Princeton 

Energy Resources International 

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