bluuebunny/crossref_metadata_2025 huggingface dataset:
Experiences With an Efficient Rate-Management Approach for the 8th Tortonian Reservoir in the Vienna Basin
Authors: Kornberger Martin , Thiele Marco R.
Published: June 2014

Active well-rate management to promote the efficient use of injected fluids and to demote fluid cycling is a simple way to increase recovery in brown fields while minimizing costs and preserving existing field/well-fluid-handling constraints. In this work, we present the application of an efficient flow-based surveillance technique to drive rate-management decisions for the 8th Tortonian reservoir in the Vienna basin, Austria. The 8th Tortonian is a typical example of a decade-long peripheral waterflood on a long, steady decline for which it is difficult to justify expensive drilling/workover programs. Active rate management to improve pattern sweep presents an inexpensive solution to increase recovery. In case of the 8th Tortonian, EUR 10 000 (USD 13,000) was spent to modify well rates, resulting in approximately 5700-m3 (approximately 35,000-STB) incremental oil recovered during a 30-month period. The current oil rate remains higher than the oil rate before the start of the project.

Our approach takes advantage of streamline-derived well-allocation factors (WAFs) to quantify injector/producer connections. It is simple and efficient to estimate WAFs with total historical well-fluid rates, well locations, and a geological model. With the WAFs, the ratio of produced oil to injected water (efficiency) of each injector/producer pair can be estimated. Well-pair efficiencies are the starting point for the rate-management approach described in this work.

A simple, single-homogeneous-layer system was used in conjunction with historical rates and well locations to estimate the WAFs for the 8th Tortonian reservoir. Connections were compared with available tracer data, and an area of interest was subsequently selected in which both streamlines and tracer data confirmed oil recovery by injected water. A key constraint was to maintain the total gross rate of the area selected at current capacity. New target rates were determined and implemented, resulting in a 30% increase of oil rate during a 30-month period. Considering the simplicity and efficiency of the approach, this is a notable result. The production response of the selected wells showed an increased recovery in conjunction with a relatively constant water cut, suggesting contact with previously unswept oil. All operations and modifications were performed at minimal cost. There were no perforation changes or acidizing jobs involved, and rate changes were obtained simply by changing pump sizes or increasing the number of strokes by changing the V-belt pulley.
Fifteen Years of Expandable-Sand-Screen Performance and Reliability
Authors: Ismail I.M.. M. , Geddes M.W.. W.
Published: June 2014

Expandable-sand-screen (ESS), a technology concept envisaged by Shell and initially developed by Petroline, was first field trialed in 1997 with the idea that eliminating the annulus between the sand screen and wellbore would improve downhole sand control and allow enhanced reservoir performance and management. By the end of 2012, ESS was installed in 677 wells, with 418,184 ft of screen deployed globally. As such, ESS has matured as a viable sand-control technology combining openhole-gravel-pack functionality with the installation simplicity of a standalone-screen (SAS) completion.

With performance, reliability, and long-term well life expectancy of paramount importance to field-development economics, an extensive internal installation database has been maintained for Weatherford's ESS systems. Over the past 15 years, observation and analysis of design, planning, field implementation, and useful life cycle have been documented in this database. This performance insight provides the foundation for future reliability and has been used to identify learning opportunities, influencing the product evolution and technology-application envelope.

With performance and reliability analysis provided and discussed in detail, the applicable ESS envelope is outlined. Product-design enhancement, methodical application evaluation, and rigorous operating procedures result in improved successful use. Analysis of both infant and production failure trends are presented and show improvement. These data are used to estimate future life predictions by use of recognized reliability-analysis tools. The applicability of ESS in openhole wells is highlighted, with continuing performance in oil producers, gas producers, water injectors, and underground-gas-storage applications. There are various sand-control technologies successfully used in reservoirs around the globe. This study outlines the applicable envelope for ESS use, providing insight to enable informed evaluation, life-of-well risk appraisal, and, ultimately, reliable sand-control-completion selection for existing or new field-development appraisal.
Next Step in Offshore Heavy Oil - Mariner Reservoir Development
Authors: Berg Eirik A. , Silcock Simone , Østbø-Bjåstad Bodil
Published: June 2014

Mariner is a large heavy oil discovery in block UK-9/11, located 320 km north east of Aberdeen. The execution and development of the project will be from Statoil's new Aberdeen office. The discovery contains 1–2 Billion Barrels of Oil in Place in two reservoirs (Maureen and Heimdal). 19 appraisal wells have been drilled. The oil viscosities are 67 cp (Maureen) to 508 cp (Heimdal) at reservoir conditions. Production start is in February 2017. The reservoir development is based on use of re-injected produced water. ESP pumps are used for artificial lift. In total 100 wells are planned including multilateral slanted wells and horizontal wells. Two drilling rigs and one work-over rig will be active in parallel the first 4 years. Challenges to be met are related to high oil viscosity which gives early water breakthrough and mapping of remobilized Heimdal channel sands. The available seismic only allows for a stochastic Heimdal reservoir model. A full field broadband seismic survey will be available in 2013, applying the newest advances in technology to aim at better imaging the Heimdal sands. Current development strategy for the Heimdal reservoir is pattern drilling using an inverted 9-spot pattern. The work going forward will focus on use of the new seismic data to establish a deterministic reservoir model to be used for well planning. Work is on-going to significantly optimize the Heimdal development. Active geosteering will be important to limit the use of pilot holes and improve Heimdal reservoir sand mapping. The reservoir simulation model is very computer time consuming. Coupled segment models have been constructed that replicates the full field simulation but with significant reduction in simulation time. A polymer flooding study has been initiated to realize the EOR potential.
An Improved Approach to Simulate Low-Permeability Fractured Reservoirs with Dynamic Hybrid Dual-Porosity Model
Authors: Li Xiaobo , Wu Shuhong , Li Qiaoyun , Li Hua , Wang Baohua
Published: June 2014

For traditional dual porosity/permeability model, the fracture system is assumed to remains a steady state which the width, length, density of the fractures in reservoir does not change during the whole production, and it is not possible to simulate fractures variation effect with these models. Hower, the above assumption does not hold in low permeability fractured reservoir where the fracture system will change with the formation pressure.

In order to simulate the unsteady state of fracture system, an improved approach to simulate low-permeability fractured reservoirs is proposed in this paper which a dynamic transitivity tensor model is overlapped to dual porosity model. It is assumed that the fracture network is the primary continuum for fluid flow, and the matrix of high storability is considered to be a sink or source to the fracture. In this approach, the fluid exchange between the matrix and the fracture is expressed by an exchange term, and the variation of fractured system is described by dynamic permeability, which is a function of pressure, stress, density of fractures.

The paper will detail the dynamic hybrid dual-porosity model such as its assumptions, equations, mechanisms and also its applications in the fractured reservoirs simulation. The simulation results show that the dynamic hybrid model has high potential to accurately simulate the dynamic fracture network for low-permeability resevoirs.
Improving the Operational Life of Riser Line Seals and Telescopic Joint Packers
Authors: Örjasaeter Oddvin , Delhaye Virgile , Haukenes John , Solberg Stian , Björneklett Borge
Published: June 2014

Dynamic seals for drilling risers have in some cases shown unpredictable performance – especially under demanding conditions. In future the "nice wells" will diminish in number and the challenging HT/HP and complex drilling situations will be the focus for future developments in the Middle East in particular and also worldwide in general.

The paper will present novel findings and development of full-scale testing of seals and packers: Short term damage (e.g. mounting), long term cyclic deterioration, materials applied, and differences between various seal types and produce are included.

The investigations quantified the relative importance of operational parameters and constraints on seals performance in full-scale seal tests. The results will used in the future developments of seals for demanding field environments.
Impact of Well Completion on the Uncertainty in Technically Recoverable Resource Estimation in Bakken and Three Forks
Authors: Ganpule Sameer , Cherian Bilu , Gonzales Veronica , Hudgens Paul , Reyes Aguirre Pascual , Mata Domingo , Olarte Diana Paola , Yunuskhojayev Alisher , Moore William Ray
Published: June 2014

The Bakken formation ranks as one of the largest oil developments in North America in the past 40 years. Various estimates place the total resources (recoverable and non-recoverable) with today's technology, from 2 to up to 24 billion barrels of oil (BBO). According to the North Dakota Industrial Commission (NDIC) there were 6,884 horizontal wells by end of 2012 in North Dakota with majority of these wells completed in the Bakken formation. The main target for exploitation has been the middle Bakken siltstone member which is sandwiched between Upper Bakken Shale and Lower Bakken Shale. However, targets below Lower Bakken Shale have shown commercial production notably from the Three Forks benches and sporadically occurring Pronghorn member. The close proximity of these targets coupled with the need for hydraulic fracturing, introduces uncertainty in the "source" of oil production in wells and hence in technically recoverable resource forecasts.

In this paper, we discuss models built to replicate well performance under various completion configuration and depletion pattern to demonstrate the challenges in estimating technically recoverable resource early in to the life of a well or group of wells. These challenges may arise from the stimulated reservoir volume (SRV) not contained within a single reservoir but straddling more than one reservoir at a time. Connectivity between multiple reservoirs and the wellbore may vary with time due to change in stress contrast related to fluid production or by hydraulic fracture conductivity degradation; such varying connectivity can further complicate production allocation from multiple reservoirs. A lack of understanding of SRV distribution and subsequent drainage from multiple reservoirs may lead to significant uncertainty in technically recoverable resource estimation - especially when using short-term production data.

This paper also highlights the effects of completion interference between a well and its infill offsets on uncertainty in estimating technically recoverable resource. We intend to emphasize the issues previously mentioned to the broader audience with the intention to promote further technical discussion on the role that well completion plays in resource evaluation of unconventional plays such as the Bakken Shale.
Stimulation Lab Tests to Increase and Maintain Well Production: Field Cases
Authors: Arevalo-Villagran J. A. , De Antunano-Munoz Y , Pumar-Martinez F. , Lysandrou-Costa M.
Published: June 2014

This article presents the development of laboratory tests and workflow methodologies at Pemex E&P to identify the type and mechanism of formation damage arising during the production life of oil and gas wells in carbonate and sand formations. More than 130 workflow procedures were designed and developed for matrix stimulation and fracturing treatments at Pemex E&P from 2006-2012 and, as a result, a 413% production increase was achieved, highlighting the importance of developing the TIDP (Tests to Identify Damage Type) laboratory test methodology, which may be applied throughout the life cycle of a well. To test the methodology, it was first applied to 100 fluid samples taken at the surface and at the bottom hole of oil wells in which the productivity had decreased, with the following results: 75% of the damage was from stable emulsions formed by oil, water and solids, 20% was from organic deposits, and 5% from inorganic deposits. The TIDP methodology was also applied to completion wells, analyzing 50 fluid samples taken mainly at the bottom hole, and indicated that 85% of the damage was a result of mud emulsion + solids + brine + well fluids, 10% resulted from mud emulsion + solids + well fluids, and 5% from mud emulsion + well fluids. Once the damage types and location in the reservoir and well production system were identified, 40 candidate wells were selected and treatment types were determined, depending on the laboratory test results and the formation type. From these 40 wells, it was concluded that through the identification of the damage types and mechanisms that were obtained with the methodology, it was possible in the short term to achieve 30-400% production increases in these wells and economic benefits of more than $2 million USD per day.
Multivariate Analysis of Job Pause Time Data Using Classification and Regression Tree and Kernel Clustering
Authors: Maucec Marko , Singh Ajay , Bhattacharya Srimoyee , Yarus Jeffrey , Fulton Dwight , Orth Jon
Published: June 2014

The well treatment program is an important part of the field development plan, and certain variables, such as job pause time (JPT), can affect its efficiency. JPT is the time during which pumping is paused between subsequent treatments of a job. The objectives of this work are to investigate whether, from existing data, it is possible to find patterns in significant variables that affect the extreme values of JPT in a particular region. The answers are sought by applying a classification and regression tree (CART) to both categorical and continuous variables in the database. The practical application of CART is presented using case studies first using classical CART analysis, then using CART analysis with enhancement tools such as the normal score transform (NST), and then dividing the large dataset into smaller groups using clustering. Significant variables are found that affect the response variables, and predictor variables are ranked in order of their importance. Such information can be used to control predictor variables that cause high JPT.

The results are outlined in an intuitive way, including categorical, continuous, and missing values. Because CART is a data driven, deterministic model, we cannot calculate the confidence interval of the predicted response. Confidence in the results is purely based on the historical values, and the accuracy of the result produced by a tree model depends on the quality of the recorded data measured in terms of volume, reliability, and consistency. The prediction capability of CART is enhanced by the use of NST and clustering techniques. The approach presented in this paper analyzes a dataset with limited information and high uncertainty and should lead to developing a method for generating proxy models to find future success indices (e.g., for drilling efficiency or production from a fracture). This could standardize stimulation and generate decision ‘best practices’ to save costs in field development and the optimization process.
Knowledge Intelligence (ki)
Authors: Saxby D.. , Burridge G..
Published: June 2014

Despite huge capital investment and over a century of experience, oil and gas companies are facing huge challenges in terms of the governance of their own expertise and knowledge. This challenge is exacerbated by the Big Crew Change, technological revolutions and high technical staff mobility.

For an industry such as Upstream Oil & Gas, harnessing all that the organisation knows and is capable of is a significant and pressing management priority. While the industry has dealt with the Information Age, it has yet to master Knowledge.

In this paper, we outline a methodology to benchmark a company’s maturity in this key aspectof organisational effectiveness through a parameter we call Knowledge Intelligence (Ki), measures of wealth of indicators in business process, technology and people performance within the organisation are all in this process. We use the measurement of Ki to map out solid implications for innovation, risk reduction and certainty augmentation, and ultimately, for organisational performance.

We illustrate this through a theoretical scheme showing the sequential importance of how Ki is built up from first principles of governance of data, information and knowledge and its mastery and the fact that its value derives from a systematic attention to all aspects of the Ki enhancement cycle.

To demonstrate the practical use of this methodology, we provide a case study of Ki for several different example organisations and the effect it has on their strategic KPI’s of risk, uncertainty and value generation.

The opinions represented in this paper are those solely of the authors and this work has been carried out independently of their organizations.
Innovative Solution to Produce Intelligently From a Multi-zone Gravel-packed Completion With a Multi Drop Hydraulic Module First in Offshore Malaysia
Authors: Mohammed Tawfik M. E. , Mohd S.. , Ogbonna C.. , Ahmad A.. , Raw Ian , Goh Gordon , Kaka Singh P. K.
Published: June 2014

The "M" field is located offshore East Malaysia, with a major lateral fault separating the field into North and South. The south area main reservoirs are I, K and L with strong water drive and highly unconsolidated formations. These reservoirs contain approximately 200 MMSTB STOIIP with a current recovery factor of 24%. The major challenges in this field are (1) high well deviation, (2) sand production and (3) early water break-through.

In order to dynamically mitigate these challenges, a pilot well with intelligent well technology was considered for one of the new highly deviated infill wells which targeted 3 producing zones. A combination of cased-hole gravel-packing and open- hole stand-alone screens (SAS) was installed at the reservoir sections.

This Intelligent Completion IC system is equipped with innovative multi-drop hydraulic modules. The first IC system, successfully installed 2 years ago in 2 wells of an offset field pilot, has had a significant impact on production to date. These systems used the conventional control line configuration of an N+1 system, where N = the number of zones to be completed. However, the newly installed IC system provides an engineering solution to reduce the required number of control lines from 4 to only 2 to control 3 zones, i.e. an N-1 control line configuration.

This innovative solution was essential to the project to avoid modifications to the wellhead due to the short lead-time before the installation. This solution also reduced the installation time compared to the first edition of the IC system.

This paper highlights the screening process for candidate selection and the successful installation of IC system in multi stack reservoirs with gravel pack assembly and also the lessons learned from the full collaboration between the project team and service provider.
Areal Field Surveillance – Applying The Right Solutions For Each Asset
Authors: Engbers Peter , Zwaan Marcel , Grandi Samantha
Published: June 2014

As part of Smart Fields, deployment of surveillance solutions adds a lot of value to further field development and well and reservoir management by providing insight into the reservoir behaviour and therefore enabling timely decisions. Solutions need to be tailored for the specific field, production type, purpose, or environment. We have developed a framework to ensure that we deploy the right Field Surveillance solutions for each type of field and asset.

In this paper, we describe how we screen, decide applicability, and deploy integrated Field Surveillance solutions for the Shell portfolio. As guidance, we make use of a newly build Solutions Advisory. This advisory, for example, highlights which solutions are standard in which environment, meaning that you would have to justify why not to implement. We will describe how this assessment and deployment works with a field example from an onshore EOR field. Substantial value has been added as a result of the optimized, fit for purpose surveillance program, linked to a decision-logic with identified control measures.
Intelligent Data Quality Control of Real-time Rig Data
Authors: Arnaout A.. , Zoellner P.. , Johnstone N.. , Thonhauser G..
Published: June 2014

There is an increasing requirement for centralized analysis of drilling data to improve performance. Typically, data from service companies is transmitted from the rig to the clients Real Time Operating Centre (RTOC). A major problem is the quality of this data, which can lead to incorrect analysis and a breakdown in trust between the rig and the RTOC. Currently real time data is, at best, only checked for completeness.

In this work, we present a model for data quality control in real-time operating centres. The following points are considered in our suggested model: Monitoring the quality of real time data for:CompletenessContinuityTimelinessValidityAccuracyConsistencyIntegrityAlarming of all unexpected data;Generating daily data quality reports.

The suggested data quality control model has different groups of key performance indicators, calculated in real time from the streamed data. The model then takes the values of these performance indicators as input, and evaluates different properties of data quality as the output. Additionally, a new group of intelligent model-based key performance indicators is suggested. These indicators give the possibility to monitor actual quality and measure it against the expected one. The result is a measurement of Quality of Service (QoS) supplied by data provider at the rig.
Quantifying the Intelligent Field Added Values
Authors: Husain Z. B. , Al-Hajri M. A.
Published: June 2014

Saudi Aramco has embarked on an aggressive plan to implement the Intelligent Field infrastructure and workflows across all existing and new fields. Since the inception of the first Intelligent Field in 2003, the technology and processes have provided obvious benefits to Saudi Aramco and provide clear justification for a business case in favor of the Intelligent Field. Even with such obvious gains through the Intelligent Field implementations, very few, if any, attempts have been made to quantify the value and benefits of the program implementation in dollar terms. The exercise in quantifying the value is considered a step toward sharing the lessons learned within the dynamic environment of the energy sector. It also helps with understanding how new and improved sensors and communication technologies have combined with people and processes to transform the way business is done currently.

This paper discusses some of the reasons why the value determination in the Intelligent Field environment is such a challenge and why such an effort raises questions from all sides and how we can present more of such cases from around the world. Additionally, this paper will present some convincing cases, more relevant to the production engineering and operations environments, quantifying the benefits in dollar terms. By making comparisons between conventional fields and fully implemented Intelligent Fields using cases from within the company, the author highlights the value for the unconvinced individuals who still consider the Intelligent Field as somewhat of an additional load on their already stressed work schedules, where an overwhelming amount of data is available and where, sometimes, the most critical data is not available instantly.
Selection and Optimization Study on Passive Inflow Control Devices by Numerical Simulation
Authors: Zeng Quanshu , Wang Zhiming , Yang Gang , Wei Jianguang
Published: June 2014

In long horizontal wells, production rate is typically higher at the heel than that at the toe. The resulting imbalanced production profile may cause early water or gas breakthrough into the wellbore. Once coning occurs, well production may be severely decreased due to limited flow contribution from the toe. To eliminate this imbalance, inflow control devices (ICDs) are placed in each screen joint to balance the production inflow profile across the entire lateral length and to compensate for permeability variations.

Currently, there are three different passive ICD designs in the industry: nozzle-based, helical channel, and tube-type. They use restriction mechanism (nozzle-based), friction mechanism (helical channel) or cooperating the two (tube-type) to achieve a uniform inflow profile. However, the reality is that none of these ICDs alone meets the ideal requirements of an ICD designed for the life of the well: high resistance to both plugging and erosion, high viscosity insensitivity, and high density sensitivity. Therefore, the selection and optimization of ICDs for a specific reservoir requires for further study.

In this paper, three computational fluid dynamic based, numerical models of these ICDs with same flow resistance rating (FRR) were developed to characterize the flow performance. The results show that the throttle pressure drop depends on fluid properties, and geometries of each ICD. The weight of each factor that affects pressure drop was determined by maximizing deviations combining with analytic hierarchy process, and subsequently optimal ICD under specific reservoir condition was selected with the help of fuzzy comprehensive evaluation, thereby an ICD selection diagram was built. For a specific reservoir, we will have the selected ICD with best pressure drop composition by optimizing its structural parameter, which has best corrosion resistance and least viscosity sensitivity.
On The Stochastic Response Surface Methodology For The Determination Of The Development Plan Of An Oil & Gas Field
Authors: Valladão Davi M. , Torrado Ruben R. , Flach Bruno , Embid Sonia
Published: June 2014

The economical performance of an oilfield operation is uncertain and highly influenced by strategic and operational decisions variables such as well placement, scheduling and control. Based on numerically intensive reservoir simula- tors, the evaluation of an extensive list of possible decisions across all possible realizations becomes computationally intractable and additional mathematical techniques are required. A common approach to dealing with this problem is the Response Surface Methodology (RSM) coupled with Design of Experiments (DoE) and sampling techniques. Existing approaches to construct surrogates depend on specific statistical/risk measures such as expected value and standard deviation. For example, in order to construct a surrogate for the standard deviation of NPV, one would compute the standard deviation associated with the simulation results over the selected geological realizations for each candidate production strategy and then fit a mathematical model to it. In this case, the idiosyncratic response of each geological realization with respect to the production strategy is lost, which may lead to a bad risk assessment and, consequently an inappropriate decision making process. In this paper, we propose Stochastic Response Surface Methodology (SRSM) to enhance the decision-making process over the determination of oil & gas production strate- gies while properly taking into consideration geological uncertainty. The SRSM does not depend on any pre-defined risk measure providing the necessary flexibility to evaluate the intrinsic risk-return trade-off associated with the economical performance of the reservoir. Our approach is based on the construction of surrogates for each geolog- ical realization selected by sampling procedure. We argue that constructing a different surrogate for each selected realization captures the idiosyncratic behavior of each representative geological setting and provides the flexibility of choosing any set of risk measures after the surrogate construction has been done. Based on the Brugge field, an SPE benchmark case study, we provide a numerical example to illustrate our methodology.
Advanced Optimization Techniques Applied to a Petrobras FPSO
Authors: Gunnerud Vidar , Ursin-Holm Stine , Furtado Teixeira Alex
Published: June 2014

In this paper, a new method for production optimization is tested on a Petrobras offshore floating production storage and offloading (FPSO) unit from Campos Basin, Brazil. The FPSO/platform has two subsea templates, with 7 and 3 wells respec- tively. In addition there are 7 topside wells. Both of the subsea templates have two pipelines connected to the platform, one production and one test pipeline. The purpose of the optimization method is to find the optimal routing of well streams, choke settings and gas lift rates for all wells such that total production of oil is maximized. The method makes sure that the pressure drops throughout the system are feasible and gas available for gas lift is limited and needs to be distributed properly among the wells. Further, it takes into account that the handling capacity of gas, water and liquid is limited and make sure that this is obeyed.

The method finds the optimal solution to this problem in less than 20 seconds, which are two orders of magnitudes faster than the current state-of-the-art methods available on the marked. This enables a totally different production engineer workflow, since instant re-optimizations could be conducted on-the-fly during e.g. a well optimization meeting. It essentially automates the what-if study conducted to find the best choke, routing and gas lift settings, and enables the production engineer to focus on other important questions like; what is the preferred operational envelope for each well, and is the inflow performance ratio predicting the well behavior accurately for the recommended (optimal) production strategy, etc.

The computational speed-up is achieved by utilizing the structure of the production network, and by using efficient well and pipeline proxy models inside the optimization algorithm. The paper outlines the principles of the optimization method and how it was applied to a real field problem. Further, it reports on the results and discusses the potential benefits of such a method.
Implementing Intelligent Energy - Change Management Experiences and Recommendations
Authors: Halland Thomas , Jensen Leif Kristian , Eike Martin , Solnørdal Dag
Published: June 2014

Over the last decade, change management has had significant focus in Statoil, and we have implemented a large number of major changes to our operational work processes in order to improve decision support and drilling efficiency. Deployment of new technology and new processes utilizing real-time drilling data affect not only Statoil as operator, but also service companies, contractors, application vendors, and standardization committees.

Implementing internal changes affecting day-to-day operations is in itself difficult. Implementing changes also affecting and changing other companies' processes and deliverables are even harder.

Change management in Statoil have had many different approaches with regards to implementation and results. In hindsight we see that some of the transitions have been very successful, whilst others have been more challenging. We also see that the objectives and characteristics of the various transitions heavily influence the optimum change management process. Small differences in the approach can drastically influence the outcome.

In this paper we will present some of our observations, learning's and experiences implementing new processes, new technology and new contracts within the domain of real-time drilling data. We will touch upon the following topics: Optimizing the collaboration: operators, service companies, contractors.Change management focus: Functionality vs. technology.Commercial technology vs. CustomizationsContract strategy

The cases in this paper will illustrate each learning experience, both good and bad.

Finally, we will present a summary of our experiences and recommendations, hoping that this may be of value to others working with change management processes within the exciting area of Intelligent Energy.
Development and Utilization of Integrated Artificial Expert Systems for Designing Multi-Lateral Well Configurations, Estimating Reservoir Properties and Forecasting Reservoir Performance
Authors: AlMousa Talal s. , Ertekin Turgay
Published: June 2014

Reservoir simulation is one of the main if not the most important tool reservoir engineers use to forecast a reservoir performance. Nevertheless, developing and operating a reservoir simulator tool in the first place can be an arduous task that requires a set of highly skilled individuals in science, advanced mathematics, programing, and reservoir engineering and powerful computational models (Ertekin, et al., 2001). The reliability of a reservoir simulator depends on the availability and the quality of the reservoir properties. These properties are obtained from open-hole logs, core studies and well testing analysis which can sometimes be prohibitively cost intensive. Another important component of the overall process affecting the reservoir performance is the multilateral well configuration. Achieving the right design of a multilateral well configuration is a complex problem due to the vast possibilities of well forms that need to be evaluated. In light of the above, this paper demonstrates the development and the application of a set of integrated artificial expert systems in the area of forecasting, reservoir evaluation and multilateral well design. The applied method is implemented to volumetric single phase gas reservoirs with a variety of rock and fluid properties spanning tight to conventional sands. The developed approach delivers a proxy to the conventional numerical simulator for predicting reservoir performance, an expert system for estimating reservoir properties from rate decline data, and an expert system for recommending multilateral well design parameters for a target recovery profile. Furthermore, graphical user interfaces (GUIs) in conjunction with the expert systems structured are developed and assembled together for standalone installation. These GUIs allow the engineer to edit and input data, produce results numerically and graphically, compare results with a commercial numerical simulator, and generate an interactive 3-D visualization of the multilateral well. It is expected that the developed expert systems will immensely reduce time requirements and effectively enhance the overall decision-making process. However it is emphasized that this paper is not suggesting the replacement of existing and well established procedures, protocols and know-how with the developed expert systems, but rather applying them as auxiliary, pre- screening or complimentary systems where and when applicable to ease of the computational overload, deliver a solution to the inverse-looking problems and enhance the overall decision-making process.
Spectroscopic Sensing for In-Situ Monitoring of Water Fraction in Natural Gas Flow
Authors: Enshasy Hesham , Omar Amjad , Cheng Mosong , Alnuweiri Hussein
Published: June 2014

The paper presents a microwave sensing method to detect and quantify the presence of water or saline water in natural gas pipelines. Efficient and safe operation of natural gas production lines depends on intelligent monitoring capabilities of specific chemicals harmful to the operations and to the environment. For example, high salinity formation water will erode the steel pipelines, thus requiring immediate actions. Quantifying such contents is as important as detecting them. Real-time, in-situ quantification of water fraction and salinity in the flow leads to reduced production cost and improved equipment safety. The gas pipe in this work is modeled as a waveguide that is filled with gas and different fractions of water. By measuring the magnitude and phase of the reflected and transmitted signals over a broad spectrum, the water fraction can be calculated using waveguide model. With water fraction increasing, signal magnitude changes and cutoff frequency shifts. Both signal magnitude and frequency shift can give accurate estimation of the water fraction inside.

The advantage of using microwaves is the ability to cover the whole cross section area of the pipe, without missing any water droplet inside. Other methods, like electrochemical, resistivity or capacitance probes, only capture local variations. HFSS software was used to simulate the wave characteristics for different water volume fractions inside the pipe and the experimental data showed that a water fraction as low as 1% can be quantified. A repeatability study was done in this work and it showed that measurements have good repeatability.

Index Terms — Microwave Spectroscopic Sensing, NDT testing, Natural gas industry, Petroleum industry, Water fraction.
Predictive Maintenance and Deterministic Maintenance Scheduling for Continuous Process Industry Rotary Equipments
Authors: Dey Tapan , Chandramohan Sarika , Bansal Shefali
Published: June 2014

This paper explores and analyzes the methods for predictive maintenance and deterministic maintenance scheduling for continuous process industry rotary equipments. This paper consists of a brief introduction of various types of predictive maintenance techniques, maintenance schedules and the methodology to develop the optimization models. The paper also considers a turbine as a case example for an equipment type, analysis of results using the optimization model and conclusion from the analysis and future scope related to the optimization model. In the overall end-end flow, this paper outlines the use of analytical modeling techniques to first predict for example, the likelihood of a component of an equipment failing, the recommendations that can be generated based on the predictive model scores, and then use an optimization model to generate the maintenance schedule. The predictive model and the optimization model are modular and can also be used together or in isolation to provide different set of capabilities and advantages to the end customer.

Binary integer programming model is used to generate the maintenance schedule considering the deterministic part life, pulling back of events, non maintenance period of equipment and minimum number of outage. There are mainly two decisions in the optimization model which are occurrence of event for each part and outage for the equipment. Few of the business constraints are as part life for repair and replace, non maintenance period due to business requirement. The objective of the optimization model is to minimize total maintenance cost over time horizon.

The generated maintenance schedule using the optimization model reduces the wastage of part life and number of outage for equipment. This also increases the utilization of the equipment. This also reduces the downtime of equipment due to unscheduled and unnecessary maintenance. Over and above this minimize the total maintenance cost of the equipment. This model can be extended to stochastic model considering stochastic failure time of parts life. Net present value can also be included to calculate the maintenance cost for long term.

Production reduction is a major issue due to unscheduled maintenance. This optimization model gives an unique idea to generate the maintenance schedule for very complex machine such as turbine which has many sections, each section has many part-kit, each part-kit consist of many parts with various failure time for each type of event in a very efficient and effective way. This idea can be used for any industry which has very large and complex machine to get the maintenance schedule. Dragline in opencast mine, turbine, manufacturing industry, production industry are the suitable place to use this type of maintenance schedule.
Petroleum Development Oman Approach to Intelligent Production Measurement
Authors: Al Hanashi K. K. , Syed Mohammad Z.. , AL-Obaidani A. N. , AL-Hinai S. H.
Published: June 2014

Managing large number of flow meters, coupled with varying fluid properties and subsurface comingled production from multiple reservoirs, is challenging in terms of static design data and dynamic calibration data. Applying intelligent approaches to flow meters calibration and overall Production Measurement Management System can be of distinguished benefit. This paper presents examples of Petroleum Development Oman (PDO’s) intelligent approaches in remote flow meters calibration and overall performance monitoring of production measurement systems.

The first example looks at the challenge in keeping multiphase flow meters fluid and PVT data configurations up to date in a field undergoing a gas injection where gas properties are changing with time. The concept of automatic remote calibration for gas properties is discussed and field trial results are presented.

The second example describes the initiative for an integrated production measurement management system (iPMMS). By integrating engineering design data and current operating environment, the system brings transparency, reliability and integrity to all the data around a measurement system. Such a system will enable production data user to evaluate the quality of the data before making key business decisions. The system will also facilitate in managing lifecycle changes for measurement systems.
Energy Harvesting Powered Wireless Monitoring and Control in Oil and Gas
Authors: Ahmad Talha J. , Noui Mehidi Mohamed N.
Published: June 2014

Technological advancement in sensors, digital electronics and wireless communications have enabled development of low cost and low power wireless sensors and networks, thereby enabling a paradigm shift in autonomous monitoring and control for a wide range of applications in the oil and gas industry. These applications can be found all across the industry including supply chain, refineries/petrochemical plants, pipelines, exploration, drilling, production and transportation. One of the challenges is powering up these sensor/control devices. Despite the ultra-low power consumption of wireless nodes and the high energy density of batteries, they still have limited stored energy and, therefore, a limited lifetime. In many scenarios, the battery replacement of sensors could be a very time consuming task and even uneconomical and unmanageable. To tackle these issues and enable fully autonomous and maintenance free wireless sensing and control, a continuous source of energy is required.

We have investigated Energy Harvesting as the potential solution for providing reliable and long-term power for sensors by scavenging various ambient energy sources such as environmental/machine vibrations, thermal sources, flow, solar, wind energy and converting it to useable electrical energy. This paper provides a survey of energy harvesting techniques including mechanical (piezoelectric, electrostatic, electromagnetic and magentostrictive), thermal (thermoelectric, pyroelectric), light, and various state-of-the-art technologies. The requirements and technical challenges, along with financial drivers and benefits, are addressed. Various ambient energy sources present at the surface and their usage for different applications in the oil and gas industry are identified and discussed in detail.

Finally, recommendations are made for improvement and achieving the goal of practical implementation of energy harvesting to enable self-powered remote and wireless monitoring and control in oil and gas. Although the energy harvesting market is rapidly increasing because of its growing demand in various industries, the technology hasn’t been thoroughly investigated for oil and gas applications.
A Real Case Study: "Well Monitoring System and Integration Data for Loss Production Management" Consorcio Shushufindi
Authors: Goyes J.. , Biedman D.. , Suter A.. , Navarre P.. , Tortolero M.. , Ostos M.. , Vargas J.. , Vivas P.. , Sena J.. , Escalona C..
Published: June 2014

The Ecuadorian State opened the industry to "Service Contracts" during 2012 with the main objective to increase production of its mayor fields through the implementation of new technologies. Consorcio Shushufindi (CSSFD), a consortium formed by Schlumberger, Tecpetrol and KKR, was awarded such a contract. Between the commitments done by the CSSFD is the implementation of the Asset Integrated Management Center (MIA) for Shushufindi Field as a means to improve collaboration between the different stake holders to increase production and make the operation more efficient.

The CSSFD contract is based on incremental production and therefore it is of the highest importance to produce its target reservoirs. In order to achieve this target is necessary monitoring continuously some operational parameters, with different frequencies, in the field. To obtain that scenario is necessary to create an integrated system that combines both frequencies to detect loss production in wells operated with ESP system.

In order to support the daily operation and the cumulative loss production calculation, it has created an integrated monitoring system called "Well Status". This system was designed to automatically update the resume for the current situation of the field, based on the well status. Beginning with the downtime, the production loss is calculated using the last well test. As is known, the well test supplies the potential production per day. This calculation is performed for wells with high and low frequency data, allowing prioritizing intervention to those wells which report unplanned shutdown and have higher potential.

This workflow allows the engineers in the field and Office to identify the loss production caused by some issues the ESP system, and this analysis is based on ESP status tag. This analysis is continuous using real-time data that is transferred from the field.
Intelligent Energy - Changing How Work Gets Done.
Authors: Quaadgras A.. , Edwards A. R.
Published: June 2014

There is more to Intelligent Energy than information and communications technology. Getting full value from digitization in oil production requires rethinking how groups get work done, and providing the organizational capabilities to support that change.

A study of six major oil and gas companies that have all been implementing Intelligent Energy for more than five years was carried out. In this study we find that in order to implement changes at the asset level, we need to focus not just on providing an information and communications technology backbone, but more importantly, on documenting and clarifying business and group interaction rules, roles & accountabilities, and on providing ongoing coaching and feedback to all participants.

We also find that implementing effective group operational decision making across a global firm requires active involvement of local groups as well as global support, in the form of specific global organizational units that sustain and scale new ways of working. These global units are not implementing change top-down; rather they are working center-out. They coordinate efforts around continuous improvement and integration of effective practices, adoption through business pull, global governance by top operational leaders, and multiple forms of ongoing coaching. This paper will summarize the results from the study and make recommendations for the effective implementation of Intelligent Energy.