Technology Focus: Reservoir Simulation (July 2014)

An important step in the design development of carbonate reservoirs is the understanding and simulation of well flooding mechanism particularly water coning. The significance of coning is due to the fact that an incorrect account of the flooding mechanism may lead to the following negative consequences: overstatement of the target oil production inaccurate forecast of remaining reserves and the mechanism of their production, selection of unsuitable well-workover methods and other negative results. The paper discusses different approaches to the water coning simulation: local grid refinement; non-neighbour connection with the bottom water; water flooding through a vertical fracture using method of allocating drains; use of additional completions; use of the non-diagonal permeability tensor; the verticallu directed change in rock permeability and pore volume with pressure decreasing; dual porosity model. It is recommended that in case of the typical orthogonal grid, local grid refinement should be used for hydrodynamic model water coning. It is possible to obtain appropriate results using dual porosity method and non- neighbour connections, but these methods have bad forecasting power. If water coning were not repeated then: oil production total would increase up to 10-15% (for a 5 year forecast) or up to 5-35% (for a 25 year forecast);water-free period well production would be prolonged;oil production rate would increase. The implementation of the recommendations made it possible to optimize new wells targeting and well operation, which provided an increase of water-free periods of the wells for the Urals-Volga region oilfields.

This paper describes application of Project INTERSECT, a next generation highly scalable reservoir simulator on real large scale field models. High resolution reservoir simulation is required to better define and describe fluid flow and enable improved field development and tactical operational planning. Massively parallel computing techniques overcome limitations of problem size and space resolution. This paper demonstrates that large-scale simulation models can be performed on commodity hardware taking advantage of evolution in multicpu hardware architecture and software engineering. This allows both geologists and reservoir engineers to include more realistic geologic and engineering detail for better and more reliable production optimization. Intense computer simulation is essential for effective reservoir management. The advances in reservoir characterization techniques and the industry drive towards the ‘smart oilfield’ with rapid model updates will require more efficient model processing to achieve timely field operational decisions. Parallel reservoir simulators have the potential to solve larger, more realistic problems than previously possible. The size and application of reservoir simulation problems have been limited by the availability of computing hardware, reservoir simulation architecture and of solution methods for solving large-scale heterogeneous problems. The next generation reservoir simulator demonstrates that key modeling challenges has been overcome by a software architecture and capability to model more realistic subsurface and surface models. Applications of the new reservoir simulator illustrates how typical reservoir engineering options such as local grid refinement, local grid coarsening, multilateral wells and aquifer modeling affect the overall parallel performance and scalability using highly heterogeneous large-scale models. Application of new modeling techniques highlight increased accuracy of modeling results and more reliable field development planning and reservoir management decisions.

This paper describes a 3D thermal reservoir simulator that models the injection of steam into heavy oil. The variables are pressure, energy and molar densities, and the equations are volume balance and component and energy conservation. The use of energy and molar densities means that there is no variable-switching, and the formulation combines the advantages of volume balance with a fully-implicit code. A number of example problems are presented, including a large full-field fine-grid model run on parallel processors. Introduction We describe a full-featured thermal simulator that works in a number of coordinate systems: cartesian or radial, rectangular or corner-point geometry, and PEBI grids. It calculates non-neighbor connections, and will solve both single- and dual-porosity models. Local grid refinements can be defined, and these are treated simultaneously and fully coupled in the linear solver. A nine-point method can be used to reduce grid orientation effects. Computer memory requirements are minimized by only storing properties and derivatives for active cells. The new simulator is based on an existing simulator that runs in either compositional or black oil mode. A choice has been maintained and we can either model dead or live oil. We define live oil as having at least one volatile component and dead oil as having none. This paper will describe the general formulation then give examples for the dead oil case. In practice, the dead oil model can be applied to oils that have a small proportion of volatile components as long as these components do not have a significant effect on the simulation. To solve the thermal effects in the reservoir we choose energy rather than temperature as our new variable. The main advantage of an energy variable is that we avoid the problems of variable switching. In the dead-oil case, for instance, we can use energy to describe the boiling of water at a constant pressure and temperature. By adding an energy variable and an energy conservation equation to the existing formulation, we can simulate the injection of steam or hot or cold water (or hot or cold gas) into the reservoir. The formulation differs from many others in calculating energy bounds for each state in each grid block. The energy in the grid block then defines its state and a flash is performed within that state. We use a conventional fully-implicit discretization of the flow equations. Once the non-linear equations have been set up, they are iterated using Newton's method. The linear equations are solved using nested factorization. The simulator can be run either in scalar or parallel mode, and results are presented for both cases.

History matching is a very important activity during the development and management of petroleum reservoirs. Matched models are fundamental to ensure reliable future forecasts, and enhance the level of understanding of the field via geological and reservoir models. Automated history matching (Figure 1) uses a mathematical algorithm to help choose new parameter values so that models better match historical data. The algorithm may be deterministic such as a gradient based method or stochastic such as a genetic or neighbourhood algorithm (NA). The former finds optimal solutions rapidly but the overall search is limited. Locally optimum solutions are all that may be found and uncertainty analysis is not effective. Stochastic methods are quasi-global but can be quite expensive. In this work we consider an approach to speed up the convergence rate of the NA. A proxy model is used to direct the stochastic search using gradients more effectively than is usual for the NA (Arwini and Stephen 2010). We call the new method Neighbourhood Algorithm with Proxy derived Gradients (NAPG). This results in finding solutions with far fewer models. The approach is further improved by updating the proxy model as we progress with history matching and the initialization is optimized using experimental design methods. We apply the approach to the Schiehallion field where we also use time lapse (4D) seismic data as dynamic constraints to reduce uncertainty to get a more reliable model that we might use it afterwards for the forecasting.

Summary Unconventional shale–gas and tight oil reservoirs are commonly naturally fractured, and developing these kinds of reservoirs requires stimulation by means of hydraulic fracturing to create conductive fluid–flow paths through open–fracture networks for practical exploitation. The presence of the multiscale–fracture network, including hydraulic fractures, stimulated and nonstimulated natural fractures, and microfractures, increases the complexity of the reservoir simulation. The matrix–block sizes are not uniform and can vary in a very wide range, from several tens of centimeters to meters. In such a reservoir, the matrix provides most of the pore volume for storage but makes only a small contribution to the global flow; the fracture supplies the flow, but with negligible contributions to reservoir porosity. The hydrocarbon is mainly produced from matrix/fracture interaction. So, it is essential to accurately model the matrix/fracture transfers with a reservoir simulator. For the fluid–flow simulation in shale–gas and tight oil reservoirs, dual–porosity models are widely used. In a commonly used dual–porosity–reservoir simulator, fractures are homogenized from a discrete–fracture network, and a shape factor based on the homogenized–matrix–block size is applied to model the matrix/fracture transfer. Even for the embedded discrete–fracture model (EDFM), the matrix/fracture interaction is also commonly modeled using the dual–porosity concept with a constant shape factor (or matrix/fracture transmissibility). However, in real cases, the discrete–fracture networks are very complex and nonuniformly distributed. It is difficult to determine an equivalent shape factor to compute matrix/fracture transfer in a multiple–block system. So, a dual–porosity approach might not be accurate for the simulation of shale-gas and tight oil reservoirs because of the presence of complex multiscale–fracture networks. In this paper, we study the multiple–interacting–continua (MINC) method for flow modeling in fractured reservoirs. MINC is commonly considered as an improvement of the dual–porosity model. However, a standard MINC approach, using transmissibilities derived from the MINC proximity function, cannot always correctly handle the matrix/fracture transfers when the matrix–block sizes are not uniformly distributed. To overcome this insufficiency, some new approaches for the MINC subdivision and the transmissibility computations are presented in this paper. Several examples are presented to show that using the new approaches significantly improves the dual–porosity model and the standard MINC method for nonuniform–block–size distributions.

Summary Grid selection is one of the most difficult and time-consuming tasks in the simulation of geologically complex reservoirs. A grid is imposed on a reservoir so that we can solve the nonlinear flow equations that predict the reservoir's response to changes at wells or other boundaries. Therefore, I first discuss the role of grid geometry in the evaluation of each term in the flow equations. Then I describe several conventional and some new gridding techniques, as well as their advantages and disadvantages. Next I make recommendations based on my own experience and discussions with colleagues. My assessment is that grids should be as close to orthogonal as possible. Also, local grid refinement should be used with care; its inappropriate use can be counterproductive. Considerable progress has been made recently on the use of flexible grids, but efficient use of unstructured, locally orthogonal grids requires further research. Techniques that automatically align the grid with major reservoir features (e.g., faults) are being developed and are expected to simplify grid generation. Introduction A reservoir simulator predicts reservoir performance by solving flow equations on a discrete grid chosen by the simulation engineer to represent the reservoir. The grid normally is selected with one or more of the following considerations in mind.Reservoir geology and size and the data available for reservoir description.Type of fluid displacement or depletion process to be modeled.Past and anticipated field development (location and type of wells).Numerical accuracy desired.Available software options.Objectives of the simulation study.Competence of the simulation engineer or team.Available computer resources, time constraints, or project budget. In the early days of reservoir simulation, the last consideration often determined the number of gridblocks, and the available software limited the choice of grid type, usually to block-centered Cartesian or cylindrical grid. Research in reservoir simulation and hardware developments, especially over the past 10 years, has greatly extended the gridding options available.

Fractured shale reservoirs are fundamentally unconventional, which is to say that their behavior is qualitatively different from reservoirs characterized by intergranular pore space. Attempts to analyze fractured shale reservoirs are essentially misleading. Reliance on such models can have only negative results for fractured shale oil and gas exploration and development. A realistic model of fractured shale reservoirs begins with the history of the shale as a hydrocarbon source rock. Minimum levels of both kerogen concentration and thermal maturity are required for effective hydrocarbon generation. Hydrocarbon generation results in overpressuring of the shale. At some critical level of repressuring, the shale fractures in the ambient stress field. This primary natural fracture system is fundamental to the future behavior of the fractured shale gas reservoir. The fractures facilitate primary migration of oil and gas out of the shale and into the basin. In this process, all connate water is expelled, leaving the fractured shale oil-wet and saturated with oil and gas. What fluids are eventually produced from the fractured shale depends on the consequent structural and geochemical history. As long as the shale remains hot, oil production may be obtained. (e.g. Bakken Shale, Green River Shale). If the shale is significantly cooled,more » mainly gas will be produced (e.g. Antrim Shale, Ohio Shale, New Albany Shale). Where secondary natural fracture systems are developed and connect the shale to aquifers or to surface recharge, the fractured shale will also produce water (e.g. Antrim Shale, Indiana New Albany Shale).« less

In this paper three different schemes for the finite-difference approximation of ( ) terms with irregular spacings of the grid points are investigated. Several methods of selecting the grid spacing are considered, and numerical results are presented for some carefully selected examples. presented for some carefully selected examples. Results indicate that one of the most commonly used finite-difference schemes may unnecessarily result in large discretization errors; the other two schemes discussed result in greater accuracy and are no more difficult to use. Introduction Finite-difference methods are used widely for solving partial-differential equations encountered in petroleum reservoir simulation. In many practical problems it is necessary to refine the grid in certain problems it is necessary to refine the grid in certain parts of the reservoir, thus resulting in an irregular parts of the reservoir, thus resulting in an irregular grid spacing for the system. For example, the local refinement of grid is usually necessary in the study of the flow behavior near a well, i.e., the case of coning problems. On the other hand, it is usually advantageous to make the grid locally coarse over aquifers and large gas caps. In spite of the importance of irregular grids in reservoir simulation and other engineering problems, little is known about the effect of various schemes on the over-all discretization error. Most literature on the subject of irregular grid spacings is concerned with the treatment of irregular boundaries. Here, the properties of several difference approximations to properties of several difference approximations to the second-order operator Au = [ ] are investigated. Operator A is encountered in all diffusion-type equations, such as multiphase flow in porous media and heat conduction with temperature-dependent conductivity. For simplicity, we limit our study to one space variable in this study. All results reported here can be extended readily to any number of space variables.

Grid orientation effect (GOE) is the appearance of preferential flow along grid coordinate directions in numerical reservoir simulation. GOE is most evident in simulations with strong adverse mobility ratios, such as immiscible gas injection and steamfloods. Motivated by previous work, an eleven-point finite difference formulation for multiphase flow is investigated and found to reduce errors for steamfloods using structured grids. The eleven-point formulation is implemented in a parallel, fully-implicit reservoir simulator with thermal, black-oil and compositional formulations, and the implementation supports both local grid refinement (LGR) and dual-porosity, dual-permeability (DPDK) modeling. Systematic tests are performed for compositional steamflood cases with different grid resolutions and grid coordinate angles between wells. A comparison of seven and eleven-point formulation results, using different grid scales and hybrid unstructured grids, demonstrate that the eleven-point scheme is effective in mitigating GOE and can leverage the benefits of structured LGR and DPDK options. Using grid-refinement as a means of reducing GOE is case dependent and is not always successful. Additional results suggest that using grid refinement with local application of the eleven-point scheme around only the injector does help mitigate GOE with increased computational efficiency, but GOE is not reduced as well as when the eleven-point scheme is used in the entire grid-system.

Shale gas is an important type of unconventional natural gas resources. From a long-term energy development perspective, it is our strategic choice to develop shale gas resources to ensure natural gas supply, optimize energy structure and promote clean energy. The shale gas development in the USA already has a history of more than two decades, however the recovery mechanisms in the ultra-tight shale are still not fully understood, where key efforts are made to develop a better model to describe flow behavior in the shale reservoir. Due to the limited understanding of recovery mechanisms, further breakthrough is needed in laboratory analysis and reservoir simulation techniques. The shale gas development in China is in an early stage where the fundamental research of recovery mechanisms is necessary, which provides guidance and theoretical basis for key technologies in shale gas production. In the meantime, we should also pay attention to the environment issues of shale gas development. In this paper, we reviewed the research on the flow mechanisms in the nano-scale pores, the coupled fluid and rock interaction and the model description of the fractured reservoir, we also discussed the key issues in laboratory analysis, reservoir simulation and environmental impacts related to shale gas development, hopefully to provide insights on current research status and future emphases.

Carbon dioxide (CO2) injection at supercritical conditions using the huff-n-puff process has been proven to be an effective resource to mitigate the production impairment generated by near wellbore condensate banking in rich gas condensate fields. This approach decreases the density of condensate and at the same time increases the density of the gas, thereby generating a reduction in the interfacial tension between the two co-existing phases. This study evaluates the impact of CO2 injection under the huff-and-puff process on gas recovery enhancement using reservoir simulation. A compositional reservoir simulator was utilized to perform CO2 injection at supercritical conditions. Several sector models with local grid refinement (LGR) were constructed to evaluate the impact of CO2 injection at supercritical conditions (huff-n-puff) on the condensate banking in wells with rich gas condensate production. The evaluation considered numerous scenarios of injecting supercritical CO2 at different decreasing reservoir pressures in combination with sensitivities of CO2 injected volume, gas production rate, and soaking time duration. The results indicated a significant reduction of condensate saturation around the wellbore leading to improvements in gas productivity. In addition, an optimum CO2 injection frequency required to maintain low condensate saturation in the near wellbore region was established. Overall, the results indicated that injecting CO2 at supercritical conditions in carbonate reservoirs has the potential to mitigate the condensate banking problem. A positive correlation between reservoir depletion status and gas recovery was also established from the study: optimum treatment results are obtained at condensate saturation above 20%, and at reservoir pressures below the dew point. Condensate banking around the wellbore can significantly limit gas/condensate production and recovery. The injection of CO2 to overcome this problem has been more commonly used on sandstones while its use on carbonates is still under testing and development. This paper presents a reservoir simulation study using huff-n-puff CO2 injection in a carbonate reservoir to enhance well production and mitigate condensate formation around the wellbore region.

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 121038, "Evaluating Implica tions of Hydraulic Fracturing in Shale- Gas Reservoirs," by J. Daniel Arthur, SPE, Brian Bohm, Bobbi Jo Coughlin, and Mark Layne, SPE, ALL Consulting, prepared for the 2009 SPE Americas E&P Environmental and Safety Conference, San Antonio, Texas, 23-25 March. The paper has not been peer reviewed. Exploration, drilling, and production of shale-gas plays such as the Barnett, Fayetteville, and Haynesville have changed the unconventional-gas industry. Two technologies that enhanced shale-gas development are horizontal drilling and hydraulic fracturing. Hydraulic fracturing of horizontal wells completed in shale reservoirs often requires larger volumes of fracturing fluid than conventional vertical-well stimulations. Rapid development of shale gas across the country has created concerns about the use of infrastructure and about environmental effects. Introduction The Barnett-shale play began in the Fort Worth, Texas, area in the 1980s. Continued improvements in hydraulic-fracturing techniques and technology enhanced development of the Barnett shale. Development uses horizontal drilling and sequenced multistage hydraulic-fracturing technologies. Another source of technological advances in horizontal drilling and hydraulic fracturing is the Bakken shale of the Williston basin in Montana and North Dakota, which produces more oil than gas. Each shale-gas basin has a unique set of exploration criteria and operational challenges. However, the combination of horizontal-well completions and sequenced hydraulic-fracture treatments has been crucial in facilitating the expansion of modern shale-gas development to other shale plays. The low natural permeability of shale has been the limiting factor to production. Shale-Gas Geology Shale gas is natural gas produced from shale formations, and these shales function as both source rock and reservoir for the natural gas. Typically, shale gas is dry gas composed primarily of methane (90% or more). However, some shale-gas formations do produce water. Gas shales are organic-rich formations traditionally viewed as source rocks and seals for stratigraphic gas accumulations. The thin layers, as shown in Fig. 1, that make up shale result in a rock with limited horizontal permeability and minimal vertical permeability. Unfractured shales typically have permeabilities on the order of 0.01 to 0.00001 md, limiting production. The natural matrix permeability of shale sometimes is overcome by natural-fracture networks that developed when overburden pressure was reduced as a result of erosion of overlying rock formations. Other tectonic activity also can cause a change in the pressure, creating additional fractures. Often, fractures are key sources of permeability, facilitating the migration of fluids through fine-grained rocks such as shales.

This paper describes the benefit of using modeling and simulation tools to aid educational process in teaching computer network engineers. These techniques motivate students and encourage them to be original and creative. The obtained results are promising to reduce the gap between the education in universities and real work environments. This in turn makes students prepared to face real-world problem during their future real jobs. Packet tracer, GNS2, OPNET, and fat-tree simulator tools are used in this paper.

Raudhatain field located in North Kuwait produces hydrocarbons from over 230 wells into Gathering Center X with varying complex geometries, completions and downhole equipment. NK asset team is executing a project of modeling the entire NK production system starting with wells in Raudhatain field producing to GC-X, involving building models for the wells and the gathering surface network of flow lines. There are numerous challenges that the NK asset team is facing in meeting production targets, including controlling water/gas breakthrough in horizontal wells. Mitigation measures include installation of inflow control devices (ICDs). Since inception a decade ago this proven technology has long been used in many oilfields around the world and is increasingly being installed in horizontal wells in Kuwait. To date there are several horizontal wells in Raudhatain field completed with ICDs. Reservoir modeling and simulation approach is frequently used in the industry capturing the behavior of existing ICD wells. This approach uses conventional modeling tools that are typically more intricate and require expert skills in capturing the dynamic behavior of the wellbore and the reservoir which is less appealing to the operations and practicing engineers. Limited with time and resources in this project, the NK team took a relatively simpler and fast approach in modeling existing ICD wells in Raudhatain field with the aim of enabling the engineers to capture the behaviour of the wells using existing production engineering tools at their disposal. The approach can be summarized as follows: ➢Establishing the well performance➢Modeling the individual ICD sections in accordance to the approximate flow distribution/geometry along the horizontal well➢Matching the well with well test data Key benefits of this approach are: ➢Enabling the engineers to quickly model the ICD wells.➢Facilitated the use of existing tools to deliver engineering models fit for use in the production system.➢Serves the purpose of high level modeling of complex ICD wells and in the future this exercise will certainly be undertaken to capture wellbore hydraulic effects.➢ICD well models are timely added into the gathering network which would otherwise have been delayed using a conventional method.

Data-Driven subsurface modeling technology has been proven, for the past few years, to yield technical and commercial success in several oil fields worldwide. A data-driven model is constructed for the first time for an oil field onshore Abu Dhabi, and used for evaluation of a reservoir with substantial reserves and comprehensive development plan; for the purpose of predicting production rates, dynamic reservoir pressure and water saturation, improving reservoir understanding, supporting field development optimization and identifying optimum infill well locations. The objective is to provide the asset with a decision-support tool to make better field development planning and management. The subject reservoir is a low permeability carbonate reservoir and characterized by lateral and vertical variations in its reservoir rocks and fluid properties. More than 8 years of Phase-I development and production/injection data and extensive amount of well tests and log data (SCAL, PVT, MDT) from more than 37 wells were used to construct the Data Driven Model for this asset. This new modeling technology, (TDM), integrates reservoir engineering analytical techniques with Artificial Intelligence, Machine Learning & Data Mining in order to formulate an empirical and spatiotemporally calibrated full field model. In this work, it is leveraged with other conventional reservoir modeling and management tools such as streamline modeling, isobaric maps and flooding conformance. Several analyses were performed using the full field data-driven model; complementing the existing conventional numerical model. The accomplishments of the data-driven reservoir model for this project included, but not limited to, comprehensive history matching (including blind validation) and then forecast of Oil rate, GOR, WC, reservoir pressure and water saturation, injection optimization, and choke size optimization. The results generated by the data-driven model proved to be quite eye-opening for the asset management; as the model was able to identify potential areas of improving field efficiency and cost reduction. When combined with numerical techniques, the calibrated data-driven model assist to obtain a reliable short term forecast in a shorter time and help make quick decisions on day-to-day operational optimization aspects. The use of facts (all field measurements) instead of human biases, pre-conceived notions, and gross approximations distinguishes data-driven modeling from other existing modeling technologies. Its innovative combination of Artificial Intelligence and Machine Learning (the technologies that are transforming all industries in the 21st century) with reservoir engineering, reservoir modeling and reservoir management clearly demonstrates the potentials that these pattern recognition technologies offer to the upstream oil and gas industry for its realistic digital transformation.