With 8 billion barrels of bitumen in place and more than 30 years of thermal piloting and demonstration projects, Peace River offers an excellent growth opportunity for Shell's ultra-heavy oil portfolio. In support of this initiative, integrated geological and reservoir modeling of two project areas was conducted. The key objectives were toimprove predictive modeling capability of cyclic steam stimulation (CSS) projects by history matching two groups of CSS multilateral wells anddevelop a history matched physical representation that not only validates empirical models but can be deployed to optimize CSS designs for full field development. Detailed geological models were created over two pad areas providing a geological framework large enough to have realistic boundary conditions, including impact of surrounding wells. The geological models were imported into CMG's STARS thermal reservoir simulator, and a relatively fine grid was extended over each project area. All available historical production, injection, pressure and temperature data were used in history matching. Steam-induced reservoir dilation, explicit fracturing, and relative permeability hysteresis were important aspects of the overall physical representation. Common physical parameters for dilation/re-compaction, fractures, permeability/porosity transforms, vertical to horizontal permeability ratios, and relative permeability hysteresis were used for both pads. Each pad area maintained its own unique geological, petrophysical, and fluid properties, in line with observed field trends. Excellent history matches (aided by experimental design) of injection and production volumes, injection wellhead pressures, estimated production bottom-hole pressures and temperature profiles were achieved not only for the entire Pad A and B groups of wells, but also for the individual wells. In summary, a predictive CSS simulation model has been developed and validated by history matching two areas of the Peace River field. The model is suitable for sensitivity studies of geological, petrophysical, and fluid properties. It is also capable of assessing impact of well configuration, spacing, steam quality, and steaming strategy. Introduction Peace River is 100% Shell owned heavy oil property located in north-western Alberta, Canada, approximately 700 km northwest of Edmonton (Fig. 1). It holds approximately 8 billion barrels of 7°API oil in place trapped in approximately 30 m thick semi-consolidated sand layer (Fig. 2a) buried at a depth of about 600 m, and spread over approximately 370 km2. The Bluesky reservoir has been broadly classified into two intervals, poorer quality Estuarine and good quality Deltaic (Fig. 2b). CSS is employed to extract the oil, most recently using closely spaced multi-lateral horizontal wells drilled from a central pad. Modeling Objectives Growth plans being considered cover development across the entire field. Optimizing such a development plan requires investigating a host of sensitivities, including well configuration, placement, spacing, steam quality, steam slug sizes, production cycle length etc. Thermal reservoir simulation is a viable tool that can be deployed to explore for the most optimum case. The challenge with such models is for them to be reasonably well history matched, while at the same time retaining their predictive capability. Injection above fracture pressure adds to physical complexities. Addressing this challenge became the primary modeling objective.
Peace River Carmon Creek is a 100% Shell owned ultra-heavy oil lease located in north-western Alberta, Canada, approximately 700 km northwest of Edmonton (Fig. 1). It holds nearly eight billion barrels of 7°API oil in place, spread over 370 km2. The Carmon Creek Project targets possibly about half of that oil for development by cyclic steam stimulation (CSS). There are growth plans for a significant increase in oil production over the next five years. The purpose of this study was to optimize CSS well configuration and steaming strategy for each distinct reservoir area by deploying previously improved and history matched simulation models1. A full field static model was built, comprising over 400 wells. More detailed static sector models were also built for each distinct geological area and translated into elements of symmetry thermal simulation models. The choice of design parameters and handling of uncertainties were addressed in a phased manner. First, the smallest possible element of symmetry simulation model and the most efficient discrete fracture realization were determined. The next phase involved optimization of the well configuration and steaming strategy for each field area (based on approximate Net Present Value, NPV). The final phase entailed uncertainty analysis for the optimized design concepts and determining P15, P50, and P85 forecasts for each area. Experimental Design and Monte Carlo simulations were applied to further reduce the runs required for each phase. Although different optimum CSS designs were determined for each geological area, the modeling results can be generalized as follows:Horizontal well near the base of the reservoir is the optimum well type for CSS at Peace River.Well spacing less than 75 meters appears more attractive in the higher reservoir quality areas compared to the current assumption of 150 meters. In summary, a series of predictive CSS simulation models, primarily for horizontal wells, have been developed. Heavily aided by experimental design, a unique phased modeling workflow was applied to optimize well design and steaming strategy. Some of the suggested design components are already being tested at Peace River. Introduction Historically, various thermal recovery schemes have been piloted at Peace River, including in-situ combustion, steam drive, steam foam, steam assisted gravity drainage (SAGD) and CSS. At present, CSS with injection above fracture pressure is employed to extract the oil, most recently using closely spaced multi-lateral horizontal wells drilled from a central surface pad. The CSS target is the Bluesky formation, an approximately 30 m thick semi-consolidated sand layer buried at a depth of about 600 m, characterized by a wide range of reservoir properties such as oil viscosity, vertical to horizontal permeability ratio and reservoir thickness. These varying reservoir features are expected to result in different optimum CSS well configurations and steaming strategies for each geologically unique portion of the field. The purpose of this study was to determine these optimums.
Heavy oil reservoirs often require thermal enhanced oil recovery (EOR) processes to improve the mobility of the highly viscous oil. When working with steam flooding operations, finding the optimal steam injection rates is very important given the high cost of steam generation and the current low oil price environment. Steam injection and allocation then becomes an exercise of optimizing cost, improving productivity and net present value (NPV). As the field matures, producers are faced with declining oil rates and increasing steam oil ratios (SOR). Operators must work to reduce injection rates on declining groups of wells to maintain a low SOR and free up capacity for newer, more productive groups of wells. Operators also need a strong surveillance program to monitor field operational parameters like SOR, remaining Oil-in-Place (OIP) distribution in the reservoir, steam breakthrough in the producers, temperature surveys in observation wells etc. Using the surveillance data in conjunction with reservoir simulation, operators must determine a go-forward operating strategy for the steam injection process. The proposed steam flood optimization workflow incorporates field surveillance data and numerical simulation, driven by machine learning and AI enabled Algorithms, to predict future steam flood reservoir performance and maximize NPV for the reservoir. The process intelligently determines an optimal current field level and well level injection rates, how long to inject at that rate, how fast to reduce rates on mature wells so that it can be reallocated to newly developed regions of the field. A case study has been performed on a subsection of a Middle Eastern reservoir containing eight vertical injectors and four sets of horizontal producers with laterals landed in multiple reservoir zones. Following just the steam reallocation optimization process, NPV for the section improved by 42.4% with corresponding decrease in cumulative SOR by 24%. However, if workover and alternate wellbore design is considered in the optimization process, the NPV for the section has the potential to be improved by 94.7% with a corresponding decrease in cumulative SOR by 32%. This workflow can be extended and applied to a full field steam injection project.
The Mukhaizna thermal development is one of the Petroleum Development Oman(PDO) Enhanced Oil Recovery (EOR) projects. On aggregate these EOR projects areintended to move PDO from a current total-concession recovery factor of 12% inyear 2002 to a recovery factor in excess of 50% by 2030. This project is adeparture from the traditional low cost projects in PDO and will require largeannual investments. Cold production from existing wells is expected to reducethe reservoir pressure from 96 bar to less than 40 bar by 2005 to allow energyefficient steam injection. Steamflood development is expected to take place inphases. Phase I, although carrying a strong pilot component, is designed to beeconomic on its own, and is expected to deliver 1600 m3/d hot oil production, starting Q1/2006. The full field development plans encompass drilling andinstalling production facilities to reach a plateau production of 16000 m3/d in2013. Approximately 1200 wells will be required. In the base case a total of 84mln.m3 of oil will be recovered resulting in a recovery factor of 55 % in thesteam developed area. Introduction Mukhaizna is the third largest oil field in South Oman, figure 1, it has anexpectation STOIIP of 374 million m3. The field was discovered in 1975 and wasfound to contain heavy, viscous oil (14–16° API, 1500–2000 mPa.s in-situviscosity at a depth of 700mss) in the Upper Gharif Unit 2 (UG2) and the MiddleGharif (MG) reservoir, Figure 2. The technical difficulties posed by the heavy oil, in combination withrelatively high associated costs, precluded an early development. Economic colddevelopment was made feasible in 1992 by the introduction of horizontal wellsin Mukhaizna. The development strategy for the field includes an initial conventional"cold" development, which is economically attractive in its own right, and hasthe strategic objective of lowering reservoir pressures sufficiently toimplement an energy-efficient steam injection project. The field was brought onstream in mid-2000 and to date 60 wells have been drilled, of which 51 areproducing. It is producing an average of 2500 m3/d cold oil and approximately2% BS&W. Geology Based on Mukhaizna core evaluation and regional knowledge of the Gharif, thereservoirs in the Mukhaizna Field are interpreted as fluvial/alluvial depositsof the Permian age Gharif Formation. The overlying Khuff Red Beds form the topseal for the Mukhaizna Gharif reservoir, figure 3. Productive sands are foundin the UG-2 unit and the upper portion of the MG-R. The Middle Gharif Shale (MG-S) separating the UG-2 and Middle GharifReservoir (MG-R) is interpreted as floodplain mudstone containing thin, isolated sheetflood sandstones. The thickness and net to gross of the MG-S isvariable across the field, and this may explain why initial reservoir pressureand fluid contacts are similar above and below the shale. The UG-0 and UG -1 are interpreted as sheetflood and ephemeral channeldeposits. They show some saturation, but are deemed non-producible due toreservoir quality.
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