Asset Team Research Articles

Tight gas development in the Mezardere Formation, Thrace Basin Turkey

More than 600 m of Lower Oligocene and Upper Eocene marine sedimentary rocks contain tight gas resources in the Thrace Basin of Turkey. Positive hydraulic fracture stimulation results, along with the presence of many untested, off-structure stratigraphic traps, indicate there is a large potential for future tight gas development in the basin.Extracting value from these complex set of reservoirs needs the use of state of the art technologies. Many companies have recognized that this theme requires the Asset Team project management methodology wherein geologists, geophysicists, engineers, log analysts, and other professionals come together to combine their skills and insight to better understand, measure and predict reservoir properties in low-permeability reservoirs and to use that information in resource evaluation, reservoir characterization and management.This manuscript describes how such a multidisciplinary asset team approach was used to determine the petrography, reservoir and petrophysical properties of the tight gas reservoirs in the Thrace Basin Turkey. Geological details and detailed core studies were integrated into petrophysical analyses, along with mud logs to identify the unconventional pay zones for executing hydraulic fracture stimulation in the area. As a result, stimulations were designed to avoid frequent interlaced water-bearing sand stringers and resulted in numerous successful recompletions of the existing wells, drilling of vertical and horizontal wells with increasing recoverable reserve by over 40 Billion Standard Cubic Feet (BCF) in proved reserves during a 2 year project.

Unconventional Measures for Shale Reservoirs

Unconventional Measures for Shale Reservoirs

Production Optimization With Artificial-Lift ESP Pilot Systems in a Mature Oil Field

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 171917, “Production Optimization Over 20% With Artificial-Lift ESP Pilot Systems in Mature Oil Field: Case Study From Middle East,” by Hector Aguilar, Aref Ali Al Marzooqi, Tarek Mohamed El Sonbaty, and Leigber Villarreal, ADCO, prepared for the 2014 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 10–13 November. The paper has not been peer reviewed. A production-optimization strategy of an artificial-lift system resulted in the mitigation of challenges related to reservoir heterogeneities and completion design. An approach integrating reservoir dynamic data and electrical-submersible-pump (ESP) performance was established as a guideline for ESP surveillance and diagnostics and for targeting candidates for production optimization by implementing at least one of the possible solutions: upgrading ESP surface equipment, anticipating workovers for ESP-resizing and -deepening jobs, and reviewing well-design strategy. Introduction The field is an anticlinal structure 26 km long and 6 km wide with two main complex carbonate reservoirs, upper (U1) and lower (U2), exhibiting considerable lateral and vertical lithological changes and, consequently, variations of reservoir properties. Oil production started in 1983 through an initial-development phase. An artificial-lift project using ESP systems was implemented in 1994 to increase and sustain oil production. All producer wells are equipped with an ESP, a Y-tool, and a single completion string. All wells completed before 2014 have been operated on a fixed frequency of 50 Hz through switchboard (SWB) panels. A full-field development plan was reviewed to increase oil production by 40% by the end of 2013, to consider long-term sustainability in view of future expansion, and to stretch the target plateau beyond 2013. This target has been reached mainly by increasing the number of infill horizontal producer wells but also through the upgrading and expansion of surface facilities to handle increased volume of produced fluids. Optimization Strategy The asset team managing the field was presented with the challenge of increasing field production. An experienced project manager was assigned to lead a team representing different disciplines (development, engineering, operation, and ESP design and optimization) that cover all surface and subsurface aspects of the project. A detailed performance review was conducted per well for the entire field. It indicated that 27 wells were suitable candidates for potential production optimization, representing approximately 50% of the wells. The three well categories were defined as follows. Boost Production. This includes wells in which the ESP operates at a relatively high intake pressure. The only identified constraint has been the fixed frequency of 50 Hz delivered by the existing SWB panels. Reactivate Production. This includes wells that did not produce at stable flow rates or never produced because of shallow ESP settings. Sustain Production. This includes wells whose performance has been deteriorating because of backpressure or wells with increasing water cut. The optimization team has identified three possible optimization techniques to be evaluated and implemented in pilot wells on the basis of well category. Optimizing ESP Surface Equipment A methodology established priorities and qualified the best candidates to replace existing SWB panels with variablespeed drives (VSDs). The project was conducted in three phases. Phase I—Well Modeling. Wells were modeled through nodal-analysis software on the basis of historical production and actual performance data from recent available production tests to identify wells in which the backpressure effect becomes relevant and lifting capacity has deteriorated considerably. Phase II—VSD Trial Test Campaign. Three out of 27 wells were tested with VSDs by hooking up a portable power skid for a long-duration test.

An integrated approach to geostatistical depth conversion and gross rock volume estimation

Static, dynamic, and geomechanical models are typically built in depth because this is required when planning and drilling wells. These models are usually driven by seismic data via structural interpretation and seismic attributes, whose position is fixed in the time domain. To incorporate seismically derived data, or interpretations, time objects must be transformed to the depth domain using the process of depth conversion. The depth-conversion model should dynamically evolve during project life, from exploration to maturation. As more data become available and the geologic understanding improves, an evolving model can accommodate requirements for specific deliverables for various disciplines, e.g., gross rock volume (GRV) estimates, drilling uncertainty windows, and structural base case models. To meet the above specifications, we used a fully geostatistical method that enabled the incorporation of a large variety of data types and their associated uncertainties. We performed depth modeling simultaneously for all layers in the model, in which all layers were coupled. This imposed a dependency on depth surfaces, such that a depth surface was influenced by surfaces above and below, moving away from a classical top-down approach of depth conversion. A scriptable and mechanized method allowed for fast scenario modeling in which various geologic and geophysical concepts or model parameterization choices can be tested to provide discrete models and avoid anchoring at a single preferred model and associated probabilistic range. Depth results from multiple scenarios can be combined to provide common confidence intervals. The proposed method including scenario modeling has been successfully implemented in the UK Culzean HPHT gas field. The model successfully delivered input to the various disciplines in the asset team, providing depth structures for static model build, GRV estimates for each reservoir, and localized drilling uncertainty estimates.

Technology Focus: Horizontal and Complex-Trajectory Wells (November 2014)

Technology Focus The decision to construct horizontal or complex-geometry wells is driven by return on investment from technically supported predictions of incremental production or recovery. Variables that can be controlled during the construction phase, which contribute to a well’s performance over its lifetime, can be defined and set as “well-construction key objectives.” The well then can be designed and constructed using the ingenuity of knowledgeable people who are applying technologies and techniques to deliver on these objectives successfully. However, wells are often constructed under contractual arrangements that conflict with these objectives. A highly beneficial project outcome may not result in commercial success for all parties who contributed. Worse still, it is not uncommon for events that are undesirable and unfavorable to one party to benefit another party inadvertently, often resulting in misalignment. Therefore, to deliver what is important to the project, we rely on a range of integrity-centered human factors such as professionalism, pride in doing a good job, reputation, and relationships. This misalignment has been ongoing for years; however, there are notable exceptions to standard contractual arrangements. Interest in moving to contracts aligned to rewarding delivery of the desired result is increasing, but we might ask ourselves why the movement is slow. Certainly, designing project-specific “smart” contracts requires more effort, but, if all parties know what they want, the actual process of constructing the contract will benefit the project. Another factor that may explain the slow uptake is that, ideally, multiple parties should be incentivized on delivery of common key objectives across the asset team. This complicates matters because the tendering, evaluating, and awarding of different activities traditionally have different timelines (for example, tendering and selecting; drilling-rig contractor vs. drilling services vs. completions systems). Therefore, while we have knowledgeable, innovative, professional people with access to great technology, we should remember that the way a contract is constructed helps maintain focus on what really matters when it comes to delivering the best outcome. Well-conceived contracts may also accelerate development of new technologies, to deliver what is not currently achievable. In a nutshell, things tend to align under a well-considered contract. Horizontal- or complex-geometry-well construction projects are potentially good candidates to work out new contractual arrangements. Authorization to proceed with these projects is technically based, and measurable key variables can be defined. Performance of these wells is often more sensitive to the key variables; therefore, high focus on them by means of novel contractual arrangements should drive greater value. JPT Recommended additional reading at OnePetro: www.onepetro.org. IPTC 16813 Advancing Multistage Fracturing Using Horizontal JITP and Autonomous Completion Systems by Tim Benish, ExxonMobil, et al. SPE 163979 Challenges to Geosteering and Completion Optimization of Horizontal Wells in the Cotton Valley Formation, East Texas by S. Liu, BP_America, et al. SPE 167448 Production Optimization of a Long Horizontal Well Using Permanent Downhole Distributed-Temperature and Pressure Monitoring and Surface- Controlled Zones by Magnus Carlsen, Maersk Oil, et al.

MCSEM data interpretation for hydrocarbon exploration: A fast interpretation workflow for drilling decision

In a hydrocarbon exploration workflow, marine controlled-source electromagnetic (mCSEM) data are usually acquired after seismic interpretation for prospect identification and close-to-the-drilling decision making. Therefore, the mCSEM interpreter must provide quick answers to the asset teams in a way that the EM interpretation can add value to that decision. To achieve that goal, Petrobras developed a fast-track mCSEM interpretation workflow that consists in identifying anomalies in the mCSEM data set by frequency normalization, and then performing 1D CMP inversions followed by 2.5D polygonal inversions. The proposed workflow was successfully applied to several mCSEM surveys offshore Brazil. We evaluated an application in a complex geologic setting where the reservoir dips toward allochthonous salt. The reservoir appears as a flat spot in the seismic section, but with no significant amplitude variation with offset response. The mCSEM analysis confirmed the seismic anomaly and extended it northward. Two drilled wells corroborated the mCSEM interpretation.

Standards in 4D feasibility and interpretation

Standards for 4D seismic feasibility estimation and interpretation aim to simplify the 4D seismic interpretation process, facilitate understanding of results, and accelerate learning between projects and between disciplines. Standards encode those best practices that have proved to have a more or less universal relevance in the subject area and provide a convenient starting point for individuals and teams new to 4D interpretation. Standards are about casting a result into a familiar format. The main result is a quality improvement of the integration process between different disciplines; a side effect is the efficiency improvement and time saving from increased skill levels within each discipline. There are currently accepted 4D standards in the fields of F = 4D feasibility (fluid effects) P = poststack processing I = seismic inversion and 4D A = 4D interpretation and attributes S = simulator-to-seismic The primary user group is subsurface professionals in asset teams, in particular reservoir engineers, geologists, and geophysicists. Although 4D seismic is seen as a tool originating in the geophysical domain, the fact that it is about observing reservoir dynamics makes it of primary interest to reservoir engineers and geologists alike.

Horizon Based Target Orientated Beam Demultiple with Examples from the North West Shelf, Australia

Complex inter-bed multiple in the North West Shelf, Australia, is a problem for depth velocity modelling and imaging of Jurassic reservoirs. Traditional Radon & 3D-SRME (3D Surface Related Multiple Elimination) demultiple techniques are now standard processes for removing long period and waterbottom related multiples. However, throughout the Browse Basin, deeper multiple generators and the small velocity discrimination between primary have rendered these techniques ineffective against inter-bed multiples. Beam Migration has specific advantages in its speed and high signal-to-noise levels that make it suitable for depth velocity modelling and final imaging. Wavelets can, based upon a combination of criteria, be weighted down or excluded from reconstruction. It is possible to reject wavelets that match a multi-dimensional multiple model. This model is based upon a combination of interpretation, normal moveout and spatial & temporal location. Data examples from the North West Shelf, Australia, illustrate the flexibility of this approach and demonstrate its effectiveness in the complex inter-bed multiple area of Browse Basin. Close interaction and good understanding of the objectives, especially between the imagers and the asset team is required for the project' success. Interactive or quick testing of multiple model scenarios (through combined depth velocity model building software) is necessary to aid this interaction.

Proving the value of 4D seismic data in the late-life field – Case study of the Norne main field

The Norne Field, operated by Statoil, is a good example of improving oil recovery by using the information on fluid contact movement obtained from 4D seismic data for infill well planning. As the field enters the tail end of production, prolonging production and saving costs have become the focus of field operation and management. To fulfil the special needs of reservoir management at the current stage of the field life, the focus of 4D interpretation should also be adjusted. This imposes higher requirements for data quality and quantitative interpretation of the 4D seismic data. Here we describe the 4D-related work carried out by the Norne asset team and discuss why 4D seismic surveying is still an important tool for field operation and reservoir management in the tail-end production period.

Real-Time Evaluation of Carbon Dioxide Production and Sequestration in a Gas Field

Summary The production of a substantial fraction of carbon dioxide (CO2) in any hydrocarbon-gas stream poses a significant challenge in terms of separation and sequestration. Both environmental concerns and economic incentives encourage the operators to search for safe, cost-effective ways of disposing of CO2. This paper presents a case study in which a pragmatic solution of CO2 separation at surface and its disposal in a saline aquifer occur in close proximity to its source. A suite of both modern and classical analytical tools is used to understand the production behavior of individual wells. This understanding is imperative because production volume is dictated by the ability to dispose of the associated CO2 volumes to honor the fault-activation pressure limit. The analytical tool kit—transient-productivity index (PI), combined static and dynamic material-balance (MB) methods, and rate-transient analysis (RTA), among others—allowed for the rapid assessment of both the producing gas reservoir and the saline aquifer receiving the CO2 stream. The use of real-time data allowed a comprehensive assessment of in-place volumes for the source gas and the capacity of the aquifer. The injection of supercritical CO2 suggests that the terminal aquifer pressure has been reached by encountering less-than-expected storage volume and by the lowering of fracture-pressure gradient. On-time learning has allowed the asset team to search for alternative CO2-disposal solutions to ensure continuous gas production from this field.

Maturing Collaboration Can Accelerate and Provide Support for Intelligent Energy

This article, written by Editorial Manager Adam Wilson, contains highlights of paper SPE 150016, ’Collaboration as a Cornerstone of Intelligent Energy: How Collaboration Is Fundamental To Accelerate and Support IE Success,’ by Helen Gilman, SPE, and Michael Kuhn, SPE, Wipro, prepared for the 2012 SPE Intelligent Energy International, Utrecht, The Netherlands, 27-29 March. The paper has not been peer reviewed. Collaboration is a cornerstone of many successful intelligent-energy (IE) programs; however, as an industry, we are still in the early stages on the journey of where collaboration and IE could take us. The results from 24 IE assessments across different companies and assets point to collaboration as the most commonly recommended opportunity area for inclusion within IE initiatives. A collaboration-maturity model and roadmap explain the current state and potential future developments of collaboration across the industry. Current State of Collaboration Some examples of collaboration are cross-discipline teams, remote collaboration between locations, synchronous and asynchronous decision making, external-partner collaboration, and any combination of those. Early collaboration initiatives, such as drilling centers and remote asset centers, showed success, and, over time, these initiatives have grown into fundamental components of the IE vision for many oil and gas companies. From these early deployments, two basic types of collaboration environments have emerged: centralized specialist centers and cross-discipline asset centers. Centralized specialist centers usually focus on a small group of key operational processes to support across multiple fields. Subject-matter experts are dedicated to work in the environment supporting the field teams with process support and troubleshooting recommendations. Cross-discipline asset centers are dedicated environments that an asset team uses to support a wide array of decision-making processes. These two types of collaboration environments have emerged from different perspectives; however, actual collaboration-environment deployments may incorporate elements of both types into their solution. Capturing value as part of collabo-ration initiatives has been a subject of debate for many years. Futile efforts to allocate value across people, process, and technology in collaboration projects have caused some operators to reclassify collaboration as an enabler to value as opposed to the delivery mechanism. Although value remains difficult to quantify for collaboration initiatives, several themes have emerged that help companies continue to invest in and gain value from collaboration. Some of those themes are as follows: Significant upfront investment in facilities or infrastructure is no longer needed to improve collaboration. Collaboration requirements have increased beyond the colocated asset team or simple onshore/offshore connection. Collaboration is not seen as a standalone solution in the portfolio of IE solutions but as a key enabler to the broader IE vision. Additional benefits emerge as collaboration environments are used more widely throughout an organization.

Intelligent-Field Management: Monitoring and Optimization of the Greater Ekofisk Area

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 150424, ’Intelligent-Field Management: Real-Time Monitoring and Proactive Optimization of the Greater Ekofisk Area,’ by Amit Madahar and Alannah McIntosh, Weatherford Production Optimization; Ilnur Mustafin, ConocoPhillips; and Nick McAlonan, SPE, Weatherford Production Optimization, prepared for the 2012 SPE Intelligent Energy International, Utrecht, The Netherlands, 27-29 March. The paper has not been peer reviewed. An online real-time production-optimization and monitoring system for the greater Ekofisk area (GEA) of Norway was installed in 2006. The system has evolved significantly since installation, with changes driven by multidisciplinary teams in coordination with the operator’s Production Optimization Centre (POC). This online system integrates data from the complete production system—reservoir to export meters. The system enables real-time monitoring of all wells and their associated instrumentation parameters along with field three-phase production allocated to the well level. The system alerts engineers when a well’s performance is outside predefined tolerances, thereby enabling continuous optimization of the combined field network. Introduction The GEA has a high level of activity in terms of well intervention and drilling programs. Therefore, communication about the current operation status across a large multifunctional organization is essential. The GEA has only three fiscal-metering points to measure production. Although sufficient for production allocation at the field level, it results in uncertainty at the platform level. This situation could lead to lost production-enhancement and optimization opportunities. The POC, subsurface-production-delivery, and reservoir-optimization teams are tasked with assessing real-time data from, nominally, 160 active producers and injectors to minimize losses and maximize field production. An important function of the asset team is to provide daily reports for wells and topside losses. It usually is difficult to compile this information accurately in a short time frame. Most GEA production wells use gas lift; therefore, it is important to use the finite lift gas efficiently. This optimization process uses an asset-network model. If the asset-network model is not updated frequently and maintained, it will lose its ability to predict well-production rates and pressure drops in the system accurately. To resolve these problems, the asset uses a multidisciplinary tool called intelligent daily operations. It is used as a real-time-monitoring tool within the POC and is used for daily well-performance monitoring by the production-delivery engineers. This tool facilitates daily well-production variance to detect under-performing wells and flag production-optimization and well-service opportunities. It provides automatic updates to the network model. The real-time-monitoring tool implements various workflows to enable the different departments to collaborate and share the most-up-to-date information and removes the large amount of manual effort in gathering and analyzing the data, thus allowing engineers to concentrate on increasing production and minimizing losses.

Advanced Workflow Package for Shale Assets Developed

Technology Update The growth in unconventional resource plays in the past several years has produced a burgeoning need for new software tools for organic shales. Geoscientists need tools to help them understand complex hydrocarbon generation, storage capacity, and migration paths in source rock reservoirs, enabling them to flag and map optimized pay. Engineers need tools to help them define optimum techniques to deliver the most shale gas and oil to the market and enable them to build the best reservoir models to exploit these resources. And for unconventional resource development to proceed as it should, these tools must work together in a common framework. An advanced integrated petrophysical evaluation software package, based on a calibrated workflow, was recently developed by Halliburton for organic shales. The concept behind it was to bring all the requisite pieces of an exploration shale play analysis into a single vantage point for an asset team. This is critical when very few vertical exploration wells are used to define the economics of these resource plays before full-scale horizontal development begins. The software’s workflow modules encompass the following capabilities: total organic carbon (TOC) and organic maturity estimation; fluid and minerals evaluation; advanced saturation modeling; mechanical properties and brittleness; 3D stress and stress orientation; permeability; and pay analysis. TOC Estimation and Organic Maturity To define the resource volume, one needs to determine an accurate volume of organic kerogen present in the rock. To determine potential hydrocarbon type, the level of thermal maturity must be established. To solve for kerogen, the TOC measured by core pyrolysis can be calibrated to logs, using eight industry accepted correlations. Organic maturity, VRo, is measured by actual vitrinite reflectance or calculated from pyrolysis-derived Tmax (temperature between 300°C and 600°C that generates peak hydrocarbons from existing kerogen). This maturity value is used to make the final TOC calibration and predict hydrocarbon type. Fluid and Minerals Evaluation The heart of the volumetric analysis is its probabilistic solver. Total porosity in organic shales can only be resolved by logs when relative amounts of geochemically derived minerals are measured and combined with the TOC calculation. Minimum requirements for this type of analysis include a triple combo log, neutron capture spectroscopy, and natural gamma spectroscopy. The software uses a probabilistic error minimization methodology to determine formation fluid and mineral volumes. The idea is to construct theoretical logs that closely replicate actual logs. Tool response equations are expressed in terms of fluid and mineral volumes and their corresponding tool response parameters. Most response equations are linear. Some, such as neutron, conductivity, and certain acoustic equations, are nonlinear. The inclusion of additional evaluation tools, such as the dipole sonic travel time curves DTC (compressional velocity) and DTS (shear velocity), helps add coherence to the analysis, as long as the correct acoustic equations are used for harder rock-clay shales.

Integrated production modelling of the Wheatstone-Iago fields: boon or bane?

Applying integrated production modelling (IPM) for decision making in the oil and gas industry has proliferated rapidly, evidenced by the amount of published information about successful applications of this approach. A reason for its popularity is to mitigate the risk of over(under)investment, which is driving asset teams toward jettisoning the practice of using fixed THP to account for backpressure effects or to use the limited surface network options available in most numerical reservoir simulators. This extended abstract describes the modelling of an offshore gas development by coupling multiple full-field, numerical reservoir simulation models with a shared surface network model. Such an approach enabled subsurface elements of the production system to be linked directly to surface elements (subsea and platform) yielding a fully coupled IPM. Key development decisions were tested and justified in a technically rigorous and economically robust manner. These decisions included the phasing of development wells, compression requirements and flow balancing in the pipeline system to maintain specified gas delivery rates. Experience from this approach has shown traditional reservoir engineering techniques can still yield the same outcome as an IPM with comparable accuracy—for some development decisions such as using a creaming curve and fixed THP to determine optimum well count; nevertheless, using simple methods to account for backpressure effects may not allow the same broad-based integration of design requirements needed at the design and engineering stage of large-scale projects. The PowerPoint presentation is not available to APPEA.

Web-Portal Reservoir Knowledge Base Integrates Engineering, Production, Geoscience, and Economics Data Sets

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 146166, ’Innovative Web-Portal Reservoir Knowledge Base Integrates Engineering, Production, Geoscience, and Economics Data Sets,’ by D. Rees, SPE, J. Reichardt, and A. O'Carroll, Knowledge Reservoir, prepared for the 2011 SPE Offshore Europe Oil and Gas Conference and Exhibition, Aberdeen, 6-8 September. The paper has not been peer reviewed. A Web portal has been created for a North Sea area knowledge base of reservoir and engineering data. This knowledge base can assist in evaluating prospects and projects, assessing development risks, and measuring prospects against other opportunities in the company portfolio. Operators in the deepwater Gulf of Mexico (GOM) have a similar resource when researching analog fields. With an extendable data model to manage structured and unstructured data, this framework can ensure that exploration and asset teams can access all data of immediate interest and can highlight other key knowledge related to a specific prospect, appraisal, or development evaluation. Introduction The North Sea continues to be an arena rich in potential exploration-and-development activity. Improved technology is a driving factor in improving the risk/reward ratio of these opportunities. However, with the levels of investment required, the complexity of the environment, and the changing market, it is critical to make an accurate appraisal of each prospect before making an investment decision. Before any lease sale or partnership proposal is made, a critical factor driving development decisions and the ultimate financial feasibility of a project is reservoir quality. Portfolio managers within each oil and gas company are constrained by corporate guidelines for assessing the risk/return profiles of every prospect and have ranking guidelines aligned with the company’s business objectives and risk tolerance. The first step is to identify correlation parameters and to use them in selecting comparable analog reservoirs. Without taking care in this filtering process, there is a risk of producing flawed comparisons and meaningless predictions. Normally, several key geotechnical parameters are considered. The first set of criteria is geological, including the geographical location, age, province, depth, depositional facies, and sedimentology. Other criteria include rock and fluid parameters, pressure, temperature, gradients, drive mechanism, and other physical or engineering parameters. Such analogs provide insights into potential production issues of the reservoir. Accessible Analog Data The analog aspect of a knowledge-based approach works well only when there are sufficient well-analyzed analog fields to provide the necessary correlations. In the deepwater GOM, the knowledge-based effort is supported by the large amount of high-quality historical data supplied by operators to the US Bureau of Ocean Energy Management, Regulation, and Enforcement and made available to the public under the US Freedom of Information Act. This information includes limited analyses by operators, particularly values for expected ultimate recovery. These values should be treated with caution because they are technical and financial indicators. Depending on the operator, there can be a large bias that reflects the company’s fiscal reporting policies. In the North Sea area, production data are available from the UK Department of Energy and Climate Change and from the Norwegian Petroleum Directorate.

Increasing Drilling Efficiencies Through Analysis of Real-Time and Historic Drilling Data

This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 128722, ’Increasing Drilling Efficiencies Through Improved Collaboration and Analysis of Real-Time and Historical Drilling Data,’ by Catheryn Staveley, SPE, and Paul Thow, SPE, Schlumberger, originally prepared for the 2010 SPE Intelligent Energy Conference and Exhibition, Utrecht, The Netherlands, 23-25 March. The paper has not been peer reviewed. Estimated spending on drilling and completions was more than USD 250 billion in 2008. With rig costs estimated to consume 37% (or USD 92.5 billion) of that spending, every effort to reduce drilling time has a direct effect on the bottom line. Estimates of nonproductive time (NPT) ran from 15 to 40%, or USD 14 to 37 billion, depending on well type and operator. The causes were varied and included technical and nontechnical challenges. Obviously, any effort made to reduce NPT will affect bottom-line spending. Introduction The oil and gas industry spends millions of dollars each year collecting vast amounts of drilling data, yet has not made effective use of these data to improve drilling performance. Drilling analysis is a proven technique for improving the return on investment of drilling operations, but comprehensive drilling analysis has not been a regular part of well planning and operations. So why is it that comprehensive drilling analysis is not a consistent part of drilling best practices? In part, perhaps, because of the culture. One author suggested that 95% of drilling activities are operationally focused, placing emphasis on doing, rather than planning or analyzing. Many people in drilling operations thrive on operating by “gut instincts” and succeeding through heroic efforts. While experience dealing with unexpected events is crucial for success in an environment where uncertainty exists, surely it would make more sense to be taking pride in telling stories about the well where everything went according to plan. Furthermore, while most companies have health, safety, and environmental policies that are “zero-tolerance,” an acceptance of waste and inefficiency as being inevitable in drilling operations continues. It is difficult to imagine another industry that would accept 60% waste when it is widely known that something as simple as better planning can improve drilling results. Two other key obstacles to integrated drilling analysis are the inability to manage the volumes of data that potentially could be used in drilling analysis and the historical limitations of traditional well-planning software. The vision for integrated drilling analysis includes the ability to: Visualize and correlate low- and high-density data. Allow effective sharing of cross-discipline expertise. Provide continuous real-time updates. This integrated approach includes technologies to overcome data-management challenges and well-planning limitations, and to implement multi-disciplinary work flows to help facilitate planning and analysis across an asset team.

Bridging the stimulation and G&G worlds

Mark Farabee, Margaret Trenholm, and Rich Dodds of Halliburton argue that when considering how asset teams can leverage all the information they possess to make better decisions and improve production and recovery rates, they need a solution that allows stimulation data to be integrated with G&G data to understand how the reservoir will fracture and respond to stimulation treatment.

Integrating Data Mining and Expert Knowledge for an Artificial-Lift Advisory System

This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 128636, ’Integrat ing Data Mining and Expert Knowledge for an Artificial Lift Advisory System,’ by E. De la Vega, G. Sandoval, and M. Garcia, SPE, Pemex, and G. Nunez, SPE, A. Al-Kinani, SPE, R.W. Holy, SPE, H. Escalona, SPE, and M. Mota, Schlumberger, originally prepared for the 2010 SPE Intelligent Energy Conference and Exhibition, Utrecht, The Netherlands, 23-25 March. The paper has not been peer reviewed. The full-length paper describes a new workflow to accelerate and improve decisions regarding where and when to apply an artificial-lift system in fields with a considerable number of active wells. The workflow deploys a hybrid combination of a user-driven expert system and a data-driven knowledge-capturing system calibrated with historical data. The two systems interact to determine the right point in time to support a particular well with an artificial-lift system. Introduction Typically, asset expertise is stored in spreadsheets that define the limits for condition parameters within which a specific artificial-lift system needs to be installed. As a first step toward decision automation, these limits are implemented in a rule-based reasoning system deploying if-then-else logic to automate the knowledge. After successful validation of the rule-based approach, the information about the limits and the combination and interaction of the parameters is fed into a Bayesian belief network (BBN) capable of performing a more robust reasoning process under uncertainty or missing parameters. The setup process of the BBN requires frequent interaction with the asset team to ensure the validity and consistency of the system recommendations. While the iterative validation is necessary for the BBN setup, it also enables the asset team to review and visualize their complex decision-making process thoroughly and helps to define more-efficient decision logic. In parallel, a data-mining analysis on historical data is performed to find the decision logic as it was applied in the field. The data-mining study incorporates operational data (e.g., tubinghead pressures, line pressures, and calculated gas rates), well-test data, and information from well-intervention reports. The objectives of the data-mining analysis are: To identify patterns in operational and well-test data that lead to the decision of a new artificial-lift system. To identify potential correlations of well-intervention activity and incremental production after intervention to quantify the success of a specific artificial-lift installation under specific conditions. Case Study Activo Integral Burgos (AIB) is a typical example of a large gas field where production declined as a result of gas-loading backpressure and reduced permeability in the target formation. The fast decline of the gas wells during their first year of production drove a change from a reactive to a proactive management approach to monitor the field and select candidates for workovers and artificial-lift systems. However, the large number of wells in AIB (approximately 3,500 active wells) and the fact that 95% of the data is obtained by manual surveillance suggest the need for some level of automation to aid decision making.

Western Asset Arbitrage

The case introduces students to the nature of collateralized debt obligations (CDO) and the CDO origination process, with emphasis on the corporate structure of the special purpose vehicles, cash flows to various CDO tranches, and motivation behind CDO origination. Students will learn to quantitatively evaluate the risk-return profile of CDO tranches with emphasis on the equity tranche (also known as “toxic waste”). This is ideal for MBA and advanced undergraduate level courses on financial markets, financial institutions, and investments. In the case, an associate at the Debt Capital Markets desk of Lehman Brothers prepares a CDO issuance for Western Asset. Western Asset had been contacted by a group of commercial banks eager to sell senior secured bank loans and high-yield corporate bonds to lower their capital requirements and free up capital for additional lending. Excerpt UVA-F-1577 Rev. Feb. 15, 2012 Western Asset ARBITRAGE Jenny Kim was sitting at her desk late one afternoon in May 2007 and wondering how many deals brought to her desk were born over a business lunch. Kim, an associate at Lehman Brothers' Debt Capital Markets desk, had spent the last week structuring and preparing a proposal for a collateralized debt obligation (CDO) issuance. The deal was conceived at a popular Thai restaurant in midtown Manhattan where her boss Jason Keyes had lunch with his longtime friend Michael Stone, a senior collateral manager of Western Asset Management Company (Western Asset). Just as any other deal that was drawn out on a cocktail napkin, this one had too many open questions that Kim had to be prepared to answer the next day during the meeting with the Western Asset team. She knew that Western Asset was not new to the structured finance world, which made the task in front of her easier and harder at the same time. Kim was anxious to ensure that the presentation went well. . . .

Platform leadership: providing collaborative workflow solutions to upstream E&P

Clay Harter, OpenSpirit, discusses the benefits of service-oriented middleware for enabling effective communication between applications and data stores in the upstream E&P business where the needs of multi-disciplinary asset teams have to be met.