bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maximising the Value of Unconventional Reservoirs by Choosing the Optimal Appraisal Strategy
Authors: Willigers B. J. , Bratvold R. B , Bickel J. E. 
Published: April 2016

Abstract
The choice of appraisal strategy for the decision whether to develop a reservoir largely determines the amount of uncertainty that is carried forward to the development and execution phase of the project. Hence, the selection of an appraisal strategy can indirectly influence later go/no-go decisions. Reservoirs are appraised by drilling and producing wells. In unconventional reservoirs, these wells represent a small subset of possible wells that could be monetised if the decision were made to develop the reservoir, i.e. the appraisal wells sample an underlying population of possible wells.
This study explores how an optimal appraisal strategy can be designed in terms of the number of appraisal phases, the number of wells to be drilled in each appraisal stage, and how long to produce the appraisal wells before deciding whether to abandon the project or to proceed to the next stage. It is demonstrated how the view on the average expected ultimate recovery of a well in an unconventional reservoir can be continually revised as new information surfaces.
Production data from a large well set from the Montney Formation, which straddles British Columbia and Alberta, Canada, is used to assess how accurately initial production predicts the expected ultimate recovery of a single well.
Simultaneous Solution for Ultimate Recovery, Original Hydrocarbon in Place, and Permeability from Production Data Analysis with Application to the Eagle Ford Shale
Authors: Naeem U l , Hussain Dahraj , Khamees Kareem Al , Callard Jeffrey G. , Devegowda Deepak 
Published: April 2016

Abstract
Two parallel objectives, reservoir characterization and reserves validation are sought with this work. Reservoir characterization for multi-fractured horizontal wells leads to economic optimization of fracture spacing along a horizontal wellbore and the lateral spacing of horizontal wellbores. Accurate reserve determinations are important for forecasting revenue and when buying and selling reserves.
The Eagle Ford shale supplies a rich data set with reservoir fluid phase continuity from oil to condensate to dry gas. Contours of reduced temperature (absolute reservoir temperature divided by critical temperature) are shown in Figure 1. Reservoir temperature was based on recorded temperatures from logs. Determination of critical temperature is discussed later in the paper. Note that the scale in the key, while properly depicting gas with reduced temperatures greater than one, does not intend to portray that gas wells are north of oil wells.
Motivation for this study was based on developing an understanding of recovery factors for producing wells transecting the phase envelope from oil into condensate fluids and for recovery factors, in general, for liquids rich shale reservoirs.
Monthly production, completion reports (G-1 and W-2) and well logs are used to perform production data analysis and to determine perforation cluster and stage spacing for the hydraulic fracture stimulation treatments.
The Market for Privately Owned Mineral Rights in the US Shale Context: A Dynamic Approach
Authors: Agerton Mark J. 
Published: April 2016

Abstract
One of the unique aspects of the US shale boom is that firms have purchased most mineral rights from thousands of small landowners. Though several studies have focused on cross-sectional aspects of these leases, none study their dynamics. Incorporating several aspects of the unique US context, I develop and simulate a model of depletable mineral rights that matches several key aspects of data on leasing and drilling in the US Eagle Ford shale.
Comprehensively Valuing an Asset; How a Holistic Value Approach Aligns With Specific Corporate Goals
Authors: Capps Caitlan , Jones David 
Published: April 2016

Abstract
Valuing an asset is not simply taking total potential revenue and deducting from it the estimated cost to produce that revenue. Likewise, an asset with the highest net present value (NPV) is not necessarily the best investment for a company to make. More important than its potential to generate revenue, defining the value of an asset depends on the context of the company portfolio to which the asset belongs as well as the current and future environment and infrastructure surrounding that asset. Too simple an approach in evaluating an asset can cause a distortion of results; for instance, a simple NPV calculation of one particular asset may not factor in a company's overall cash flow, any present long-term investments or existing rig contracts. Similarly, a company must take into account market risk, current interdependencies of the complex network of getting product to market, and future infrastructural and environmental challenges before moving forward with a decision. By approaching the broad term "asset value" and demarcating it to fit a specific company based on the aforementioned items, the company can holistically value an asset. Valuing an asset requires having the ability to isolate specific variables, run several iterations of calculations, and analyze the results from multiple angles, all while using data that is a true reflection of the current state of the market and asset in question. There are multiple ways of measuring value that can have drastically differing implications, and by utilizing a comprehensive approach, an asset's true value can be measured for the company performing the evaluation. In this way, any one asset's value can differ from company to company. By building a comprehensive model which takes into consideration all present and future constraints and characteristics of an opportunity, a company can evaluate numerous variables and analyze them against strategic goals.
Comparing the Results of an Exploration Portfolio Optimized Using Utility Theory Versus the Kelly Criterion
Authors: MacKay James A. , Citron Gary P. , Carragher Peter 
Published: April 2016

Abstract
Both the Kelly Criterion and risk aversion using utility theory are methods that attempt to mitigate the risk of gambler's ruin through capital management by suggesting working interest levels for each project. Utility theory uses an assigned risk tolerance and a natural log utility function to calculate the optimum working interest for a project. The modified Kelly method does not use a utility function but rather a geometric mean-based valuation derived from the ratio of the expected value to the net present value. This ratio, called the Kelly Criterion, is a guide for capital allocation to a project as the percent of the total capital available.
When the total recommended cost of all the projects exceeds the budget, the combined portfolio is optimized by further adjusting the working interest using a linear programming technique, such as Excel’s ™ Solver. This optimization process was described by MacKay (1995) at a previous HEES Symposium (SPE 30043). The objective of this paper is to compare the procedure described by MacKay (1995) to a similar procedure using the modified Kelly method. The Kelly Criterion is currently used for financial investment decisions (Lee, 2006) and described in the book "Fortune’s Formula" by Poundstone (2005).
Screening, Assessing, and Sorting Chinese Oilfields for CO2-EOR Suitability and Potential Economic and Social Benefits
Authors: Meng X. , Zhou H. B. , Luo D. K. 
Published: April 2016

Abstract
The earth environment that human beings rely on is seriously threatened by air pollution and global climate change caused by massive CO2 emissions into the atmosphere. Several studies show that geological storage is an effective way to dispose of CO2. Most oilfields in China have entered middle and late development stages, and a great proportion of them are suitable for CO2-EOR and carbon storage. Enormous economic and social benefits could be brought about by applying CO2-EOR technologies in these oilfields. Therefore, the objective of this paper is to systematically screen, assess, and sort the oilfields in China for their suitability for CO2-EOR and assess potential economic and social benefits for implementing CO2-EOR.
First, the screening criteria of the reservoirs suitable for CO2-EOR used in previous studies by many experts were summarized. Second, the screening of Chinese oilfields suitable for CO2-EOR was first executed based on these screening criteria. Then, a comprehensive assessment and sorting of reservoirs suitable for CO2-EOR was carried out using the fuzzy analytic hierarchy process (FAHP) method. Finally, potential economic and social benefits due to CO2-EOR in China were assessed.
Based on data from 511 onshore oilfields in China, the screening result indicates that 151 oilfields are suitable for CO2 miscible flooding and 1 oilfield is suitable for CO2 immiscible flooding. Using the fuzzy analytic hierarchy process method, the 152 oilfields were synthetically assessed and sorted and their potential benefits were evaluated. Using enhanced oil recovery from 5% to 20%, the resulting incremental production could be 3.45×108t to 13.81×108t, respectively, and the CO2 storage potential could be 8.55×108t to 34.19×108t. Total potential economic benefits could reach $76.15 billion to $710.75 billion, CO2 emission reduction benefits could be $0.35 billion to $64.27 billion, energy security benefits could be $0.84 billion to $3.35 billion, and the total benefits could reach $77.34 billion to $778.37 billion. The implementation of CO2-EOR in China could greatly contribute to the Chinese economy and carbon reduction commitment.
This study conducted a survey of the suitability of Chinese oilfields for CO2 EOR, evaluated and sorting the suitability of different oilfields comprehensively and finally calculated the potential economic and social benefits. This study will provide a foundation for the implementation of a CO2-EOR program in China.
Analysis of Supply and Demand Dynamics to Predict Oil Market Trends: A Case Study of 2015 Price Data
Authors: Rafieisakhaei Mohammadhussein , Barazandeh Babak , Tarrahi Mohammadali 
Published: April 2016

Abstract
Understanding the oil price changes through the demand and supply dynamics is a challenging problem. Traditional models based on stochastic process and aggregated supply and demand have been successful in explaining the price trends in short periods of time where there is no big changes in either supply or demand sides of oil market. However, these models usually failed to capture the big shocks of oil price in circumstances where there are unexpected influential events, such as reports on the economic growth of the non-OECD members.
In this paper, we propose a revised model of oil price based on the supply and demand dynamics. Particularly, we inspect the effects of unconventional parameters on the oil price, many of which have been ignored in the traditional models. Our model investigates the effects of these expectational parameters on the major factors that shape the supply and demand. Particularly, the oil price is still modeled to follow the supply to demand ratio, however, the supply and demand are replaced with their expected trends in the model. In other words, based on the influential events that can happen in either demand or supply sides, related variables are initiated which subsequently affect the expected trend of supply or demand, and the oil price eventually.
Our model is a system dynamic model that mathematically relates the determinants of the oil price based on the underlying causal relations. The whole model numerically solves differential equations relating the marginal parameters and the main factors including the oil price, demand and supply. We separate the oil supply into US, OPEC and other non-OPEC countries supplies whose parameters differ due to conventional and unconventional resources. Moreover, we separate the oil demand into OECD, Brazil, Russia, India, China (BRIC) and non-OECD countries’ demands due to the difference in the dependence on the economic growth and oil consumption in those group of countries. We build our core model based on regression analysis on the historic data of WTI oil price, OECD and BRIC economic growth and demand, US, OPEC and other countries supply data. Then we train other parameters of the model using the historic reactions of the market to unexpected events that have occurred in the past.
Finally, we simulate the model to analyze a case study of the events occurred in the 2015 including the deceleration of the growth in Chinese economy, speculations on American shale productions, speculations on the OPEC’s decisions, and conflicts in the Middle-East region. Our results show that our model can be used to reproduce the price trends compliant with the past data, and provide predicted trends of supply, demand and their influences on the price.
The Consequences of New Sources of Capital for the Oil and Gas Sector
Authors: Wild Emma , Wansbury Natalie , Crudgington James , Andrews Mark 
Published: April 2016

Abstract
In recent years there has been a dramatic shift in the sources of capital available for the acquisition, development and production of oil and gas assets. New entrants include Private Equity firms, Infrastructure Funds, and other ‘non-traditional buyers’ to the sector. The consequences of new sources of capital are investigated.
A statistical analysis of transactions that have occurred globally in the last 3 years across upstream, midstream and downstream is presented. This paper also considers a case study and discusses key value drivers for both the buyer and seller, as well as their strategic rationale. Finally, observations are provided on the impact that new entrants are having on cost and risk management in the E&P sector.
Traditional capital sources are on the decline as the majors look to rebalance their portfolios and divest of non-core assets. Increased shareholder scrutiny, and the reduction in oil price has also forced the majority of E&P companies to reduce capital budgets. Non-traditional investors, in the form of National Oil Companies "NOCs" (including sovereign wealth funds), and financial investors (such as private equity and infrastructure funds) have emerged the dominant players in the M&A buyer population, due either to their large sovereign cash reserves, or the vast sums raised for investment funds.
Whilst this new capital has been welcomed by the industry, as it helps to support drilling and development activity levels (that otherwise would have been in further decline), it has also brought with it additional considerations for existing operators, joint venture partners, and regulators. These include: reduced technical/project management skills and the ability to adequately assess and manage risk; misaligned corporate strategies; uneducated buyers entering M&A processes; and differing abilities to manage costs.
This paper highlights the challenges faced by the oil and gas sector and the requirements for capability and competency; the impact of the new entrants to the sector and the sector's need to drive a step change in efficiency and performance, not just receive an injection of capital. However the most important consideration is risk appetite, and a company's ability to appropriately assess risk. The investors who develop or acquire the expertise to adequately characterize level of risk exposure, and identify assets commensurate with their internal risk appetite, will be the most successful in the long run.
Evolution of Uncertainty Methods in Decline Curve Analysis
Authors: Purvis D. C. , Kuzma Heidi 
Published: April 2016

Abstract
Decline curve analysis has dominated reserve estimation techniques for decades. Ironically, the introduction and expansion of probabilistic calculation techniques largely by-passed these kind of calculations, but not for lack of effort.
Much thought and writing has been dedicated to the unique issue of defining uncertainty in future production trends. Despite two decades of slow evolution, the resulting methods have been partial and prohibitive. Methods like scenario analysis, Delphi forecasting, bootstrapping and Bayesian networks have been proposed and even sometimes utilized. Though they have demonstrated some success, they all suffer from limitations in difficulty and objectivity and aggregation. They have also all utilized smooth model fits and projections. In tandem, other kinds and ways of uncertainty analysis have been applied in the time-domain or dependent sequences using decision trees, Bayesian networks and, more recently, Markov chains.
Newly developed machine-learning techniques combine these two separate streams of uncertainty analysis into a framework that promises to address both the quantification and aggregation of uncertainty in an objective way. What seems like a black-box method is instead a natural and automated extension of well-accepted techniques, and the few published studies of the technique suggest that it may be robust, particularly over the scale of years.
Understanding Shale Resource Production: What are the Key Variables?
Authors: Ikonnikova Svetlana , Vankov Emilian , Gülen Gürcan , Browning John 
Published: April 2016

Abstract
Gradually increasing production of natural gas from shale formations has surpassed the production from all other sources, including conventional, coal-bed, and tight formations in the U.S. (EIA, Monthly Energy Review, Jan. 2016). In fact, thanks to shale, natural gas production in the U.S. increased much faster than demand growth. Lower gas prices since 2010-11 owing to excess supply, has been encouraging more natural gas utilization in power generation and industrial sector, and exports via pipelines to Mexico and the rest of the world via liquefaction facilities. Many of these facilities are still under construction; and demand growth may not be fully felt until 2018 or later. In the meantime, shale drilling has slowed down considerably owing to low oil (and NGL) prices in addition to low natural gas prices. This situation raises concerns about the shale gas resource potential and future production capabilities.
To address these concerns, the understanding of the two key resource characteristics is essential: (1) the total resource-in-place, and (2) the extractability of the resource under the given technological and economic conditions. The Marcellus play is the largest shale gas play in the U.S.; gas production from the play continued to increase despite declining prices and drilling activity. In this study, we focus on the Marcellus play to study these two characteristics.
The resource base estimate for the Marcellus has been provided by geologic studies (e.g. Smye et al., in review). The recovery remains a subject of discussion in numerous engineering studies (Malpani et al., 2015; Xie and Li, 2014; Arogundade and Sohrabi, 2012). These studies, however, are mostly focused on the best drilling and completion practices, rather than looking at changes in productivity over time or comparison of marginal contribution of different inputs to productivity, which is more relevant for economic studies of the resource extraction. The present paper attempts to fill this gap, preparing the base for further economic viability analyses.
Impacts of Price Differentials, Taxation, and Costs on Shale Gas Drilling: A Marcellus Case Study
Authors: Ikonnikova Svetlana , Gülen Gürcan , Browning John 
Published: April 2016

Abstract
We explore the comparative impacts of capital costs, price differentials, and state fiscal policies on economic decision to drill, paying close attention to the decline of shale well production. We use a standard cash flow model for well economics and perform empirical analysis using actual production and completion data for Marcellus wells, cost and tax payments information from Pennsylvania, West Virginia and New York, and basis differentials in different parts of the play. Wells drilled in similar rock quality areas can have different economic value owing to completion choices and associated costs, state fiscal regimes, and market dynamics as reflected in prices realized by the producers at the wellhead.
The Impact of Changing Operational Activities on Unconventional Resource Extraction
Authors: Cherian Bilu V. , Stacey Edwin S. , Bressler Stephen , Chisler Steve , Rifia Rafif , Kublik Kristina , Narasimhan Santhosh , Gray James K. , Olaoye Olubiyi A. , Atkinson Mariah 
Published: April 2016

Abstract
In mid-2000, the North American energy renaissance began to take shape with a boom in unconventional oil and gas production. Within a decade, the combination of horizontal drilling, completion tools and hydraulic fracturing innovations unlocked a vast resource that was previously considered uneconomic. With a large focus of North American operations been around efficiency, a manufacturing model approach was deployed with significant capital efficiencies that further accelerated the learning curve. As these basins now mature and enter the infill development period, long term production results from these unconventional plays are starting to present valuable information in understanding the late time production performance and in-fill well performance (water cuts, production rates and changes due to interference).
This paper presents results from the analysis of well performance by evaluating infill wells, in-fill lease-line wells and relating these interactions to the completion types and job types deployed. The order of the in-fill operations (East-West, Zipper, etc.) on performance is evaluated together with models to demonstrate the impact of fracturing operations and production operations on fracture asymmetry. Fracture models and production models, together with interference data, are utilized to enhance the understanding of the interactions and support hypothesis that demonstrate the importance of understanding operational timing.
Evolution of Shale Production in a Time of Turbulence
Authors: Cui C. J. , Galvin P. K. , Meyet M. P. , Mozur M. W. 
Published: April 2016

Abstract
North American shale oil producers find themselves in the spotlight. Before 2015, much focus was placed on the miraculous growth of U.S. crude production, which ramped up by 1 million barrels per day (MMBbl/d) every year for five consecutive years, a phenomenon often characterized as the "shale boom". But, heading into 2015, these same producers were hit particularly hard by the sharp and rapid decline in crude oil prices. In an attempt to better understand how North American production has reacted to the fall of oil prices, this paper begins with a high-level overview of the key value drivers behind the shale boom. It aims to explain how past drilling activities, ongoing rig count changes and drilled but uncompleted wells influence current and future shale oil production. Although the dynamics of crude supply and demand are highly unpredictable, this paper identifies underlying themes in the North American oil and gas industry that continue to prevail during a highly volatile market.