Black Oil Simulator Research Articles

Black-Oil Delumping Techniques Based on Compositional Information from Depletion Processes

Summary Black-oil reservoir simulation still has wide application in the petroleum industry because it is far less demanding computationally than compositional simulation. But a principal limitation of black-oil reservoir simulation is that it does not provide the detailed compositional information necessary for surface process modeling. Black-oil delumping overcomes this limitation by converting a black-oil wellstream into a compositional wellstream, enabling the composition and component molar rates of a production well in a black-oil reservoir simulation to be reconstituted. We present a comprehensive black-oil delumping method based primarily on the compositional information generated in the depletion process that is used initially to provide data for the black-oil simulation in a typical workflow. Examples presented in this paper show the accuracy of this method in different depletion processes: natural depletion, water injection, and gas injection. The paper also presents a technique for accurately applying the black-oil delumping method to wells encountering crossflow.

Predicting PVT data for CO 2–brine mixtures for black-oil simulation of CO 2 geological storage

Accurate modeling of the storage or sequestration of CO 2 injected into subsurface formations requires an accurate fluid model. This can be achieved using compositional reservoir simulations. However, sophisticated equations of state (EOS) approaches used in current compositional simulators are computationally expensive. It is advantageous and possible to use a simple, but accurate fluid model for the very specific case of geological CO 2 storage. Using a black-oil simulation approach, the computational burden of flow simulation can be reduced significantly. In this work, an efficient and simple algorithm is developed for converting compositional data from EOS into black-oil PVT data. Our algorithm is capable of predicting CO 2–brine density, solubility, and formation volume factor, which are all necessary for black-oil flow simulations of CO 2 storage in geological formations. Numerical simulations for a simple CO 2 storage case demonstrate that the black-oil simulation runs are at least four times faster than the compositional ones without loss of accuracy. The accuracy in prediction of CO 2–brine black-oil PVT properties and higher computational efficiency of the black-oil approach promote application of black-oil simulation for large-scale geological storage of CO 2 in saline aquifers.

A Rigorous Compressible Streamline Formulation for Two and Three-Phase Black-Oil Simulation

Summary Streamline simulators have received increased attention in the petroleum industry because of their ability to effectively handle multimillion-cell detailed geologic models and large simulation models. The efficiency of streamline simulation has relied primarily on the decoupling of the 3D saturation equation into 1D equations along streamlines using the streamline time of flight as the spatial coordinate. Until now, this decoupling has been strictly valid for incompressible flow. Applications to compressible flow have generally lacked strong theoretical foundations, and very often yielded mixed or unsatisfactory results. In this paper, for the first time we generalize streamline models to compressible flow using a rigorous formulation while retaining much of its favorable characteristics. Our new formulation is based on three major elements and requires only minor modifications to existing streamline models. First, we introduce an "effective density" for the total fluids along the streamlines. This density captures the changes in the fluid volume with pressure and can be conveniently and efficiently traced along streamlines. Thus, we simultaneously compute time of flight and volume changes along streamlines. Second, we incorporate a density-dependent source term in the streamline saturation equation to account for compressibility effects. Third, the effective density, fluid volumes, and the time-of-flight information are used to incorporate cross-streamline effects through use of pressure updates and remapping of saturations. Our proposed approach preserves the 1D nature of the saturation calculations and all the associated advantages of the streamline approach. The saturation calculations are fully decoupled from the underlying grid and can be carried out using large timesteps without grid-based stability limits. We demonstrate the validity and practical utility of our approach using synthetic and field examples and comparison with a commercial finite-difference simulator. A comparison of the number of pressure solutions and the CFL numbers for the streamline and finite-difference simulation indicates that our proposed compressible streamline approach is likely to offer substantial computational advantage. Introduction Streamline simulators have become increasingly popular for high-resolution reservoir simulation using multimillion-cell geologic models. For incompressible or slightly compressible flow and under convection-dominated conditions, streamline models are well known to outperform conventional finite-difference simulation in terms of computational speed. Streamline models can also result in improved accuracy because of subgrid resolution and reduced numerical dispersion and grid-orientation effects (King and Datta-Gupta 1998; Datta-Gupta 2000). To a large extent, the efficiency of the current streamline formulation is a consequence of the incompressibility assumption that allows us to easily and effectively decouple the pressure and saturation calculations during flow simulation. This decoupling has been greatly facilitated by the introduction of the streamline time of flight coordinate (Datta-Gupta and King 1995). Specifically, utilizing the time of flight as the spatial coordinate, the multidimensional saturation calculations are reduced to a series of 1D solutions along streamlines. These 1D solutions can be carried out independently and using relatively large timesteps, as they are not impacted by the underlying geologic grid-based stability limitations. This is the primary advantage of streamline simulation. In addition, for heterogeneity-dominated flow and adverse mobility ratio conditions, the streamlines need to be updated infrequently, leading to further savings in computation time (King and Datta-Gupta 1998; Datta-Gupta 2000).

Rapid Flash Calculations for Compositional Simulation

Summary The computational time for conventional flash calculations increases significantly with the number of components, making it impractical for use in many fine-grid compositional simulations and other applications. Previous research to increase flash-calculation speed has been limited to those with zero binary interaction parameters (BIPs) or approximate methods based on an eigenvalue analysis of the binary interaction matrix. Practical flash calculations, however, nearly always have some nonzero BIPs. Further, the accuracy and speed of the eigenvalue methods varies depending on the choice and number of the dominant eigenvalues. This paper presents a new and simple method for significantly increasing the speed of flash calculations for any number of nonzero BIPs. The approach requires the solution of up to six reduced parameters regardless of fluid complexity or the number of components and is based on decomposing the BIPs into two parameters using a simple quadratic expression. The new approach is exact in that the equilibrium-phase compositions for the same BIPs are identical to those with the conventional flash calculation; no eigenvalue analysis is required. Further, the new approach eliminates the Rachford-Rice procedure (1952) and is more robust than the conventional flash-calculation procedure. We demonstrate the new approach for several example fluids and show that speedup by a factor of approximately 3 to 20 is obtained over conventional flash calculations, depending on the number of components. Introduction Gas injection into oil reservoirs results in complex interactions of flow with phase behavior that often are not modeled accurately by black-oil simulation. This is especially true for miscible or nearly miscible floods in which significant mass transfer occurs between the hydrocarbon phases. Such floods are best modeled by compositional simulation. A significant disadvantage of compositional simulation, however, is that it is much more computationally intensive than black-oil simulation. The primary reason for the increased computational time is the result of solving repeated flash calculations with cubic equations of state (EOS). Research has shown that EOS flash calculations can occupy 50 to 70% of total computational time in compositional simulations (Stenby and Wang 1993; Chang 1990). This is also true for other applications, such as multiphase flow in pipelines. The use of fewer pseudocomponents can reduce the flash computation time, but fewer components results in less accuracy (Hong 1982; Liu 2001; Egwuenu et al. 2005). This is especially true in multicontact miscible displacements, in which miscibility is developed by a combined condensing/vaporizing drive process (Zick 1986; Johns et al. 1993; Egwuenu et al. 2005). Fluid characterization by pseudocomponent models can be improved by tuning to the analytical minimum miscibility enrichment or minimum miscibility pressure (Johns et al. 1994), but those models still require significant computational time, even for fewer pseudocomponents. Another way to reduce computation time is to reduce the number of gridblocks. With coarse grids, however, numerical dispersion is large, which may cloud the results (Solano et al. 2001). Ideally, fine grids should be used that better match the level of dispersion found at the field scale. More recently, methods have been examined to find reduced parameters for flash calculations. Michelsen (1982a, 1982b, 1986) significantly increased flash-calculation speed by finding three reduced parameters, regardless of the number of components. His method, however, assumes zero BIPs, which is too restrictive for real fluid characterization. Michelsen also gave a practical method for stability calculations using the tangent plane distance (TPD) (Michelsen 1982b).

Analysis of Coalbed Methane Production by Reservoir and Geomechanical Coupling Simulation

Abstract An overview of coalbed methane (CBM) reservoir characteristics, its unique production mechanisms, and the influence of geomechanical processes on these production mechanisms are discussed from a reservoir engineering point of view. Models have been developed to predict changes in cleat porosity and permeability with in situ conditions (stress, pressure, gas sorption, and temperature). Explicit-sequential coupling simulations are conducted for conventional CBM depletion production. The study shows that during production, coal matrix shrinkage due to methane desorption results in an increase of permeability within coal seams in most regions close to the producer even though the mean effective stresses increase. The predicted production rate and cumulative production from explicit-sequential coupling simulations are higher than that from conventional simulations. The developed models also allow coalbed permeability anisotropy to be considered. Introduction Worldwide coalbed methane (CBM) reserves have been estimated at 84 ~ 262 trillion m3 (2,980 ~ 9,260 trillion ft3)(1). The majority of these CBM reserves are mainly located in Russia (17 ~ 113 trillion m3), Canada (6 ~ 76 trillion m3), China (30 ~ 35 trillion M3), Australia (8 ~ 14 trillion m3), and USA (11 trillion m3)(1). In the United States, CBM accounted for 10% of dry gas reserves and 8% of dry gas production in 2003(2). In other countries, such as China, Canada, and Australia, CBM projects are attracting more and more attention by resource companies. The production methods of CBM include conventional pressure depletion production and enhanced coalbed methane (ECBM) recovery. At present, CBM is mainly recovered by the former method. In ECBM, gases such as N2, CO2, or flue gas are injected to displace methane and maintain coalbed pressure. This recovery method is still in its infancy with only two field-scale ECBM projects (one injected N2 and the other injected CO2)(3), and one singlewell pilot project(4) worldwide. Productivity evaluation and prediction are important steps in the development of CBM reservoirs. Because gas storage mechanisms in coal seams (mainly adsorbing on the walls of pores) are different from that in conventional gas reservoirs (compressed in pores), conventional reservoir simulators generally do a poor job in predicting CBM production. Over the past decade, many models have been developed to characterize CBM production processes (5–7). Commercial simulators for CBM production can be categorized into two types: modified conventional black oil simulators and modified compositional simulators. With the recognition of the stress dependency of coal permeability and porosity and shrinkage/swelling of the coal matrix due to desorption/adsorption, some simulators have been modified to accommodate these characteristics(3). However, in these simulators the influence of in situ stresses is simplified with an analytic model or a monotonic relation between the permeability ratio and pressure changes. Durucan et al. developed a finite element model to simulate the in situ stress changes near wellbores and coupled the stress changes with fluid flow simulation by characterizing dynamic changes in permeability(8).

Application of Stream-Conversion Methods To Generate Compositional Streams From the Results of a Multimillion-Cell Black-Oil-Simulation Study of the Shaybah Field

SummaryDetailed compositional simulation of a giant reservoir with many components is not practical. However, detailed multimillion-cell black-oil simulation of giant reservoirs is now quite feasible. In this work, we apply an efficient method to generate the compositional rates from a black-oil simulation of the giant Shaybah field.In situations in which the reservoir recovery mechanism is not dominated by compositional effects, an equation-of-state (EOS)-based stream-conversion method can be used. This stream-conversion method relies on the fact that when laboratory pressure/volume/temperature (PVT) data measured on available well-stream compositions are used to generate the black-oil PVT tables, some of the compositional information is lost. The stream-conversion model retains this valuable compositional information and applies it to each producing-well completion in the black-oil simulation at every timestep.As proof of the concept, the stream-conversion method was applied to a black-oil simulation and to a limited (eight-component) compositional simulation to generate a 17-component compositional stream, and the results were compared to the respective full EOS compositional simulation for a relatively small sector (250,000 cells) of the giant Shaybah field. The compositional stream rates are in excellent agreement with the stream-converted black-oil results. As would be expected, the computational costs of using the EOS-based compositional simulator (with 17 components) are in excess of 40 times the black-oil-simulation time for the small-sector model. In general, the stream-conversion method can be used to generate the dynamically varying compositional streams from any black-oil simulation for use in the design and operation of surface facilities and in calculating the amounts of a certain cut [e.g., natural gas liquids (NGL)] from the production streams.

Limitations of Three-Phase Buckley-Leverett Theory

The broad objective of this study is to determine the limitations of the three-phase relative permeability estimation technique by using the experimental approach. In order to achieve this goal, three-phase relative permeability experiments were conducted on a Berea sandstone core plug by using brine, hexane and nitrogen gas. An unsteady-state analytical technique and a numerical technique where a black oil simulator was coupled with a global optimization algorithm in a least squares manner was used to compute three-phase relative permeabilities. It has been found that basic assumptions of linear flow and monotonic saturation changes, required for three-phase extensions of two-phase Johnson-Bossler-Nauman (JBN) theory, are violated in the displacement experiments, leading to errors in computed relative permeabilites even at high rates.

Optimization of Field Development Scheduling East Unity Oil Field, Sudan

In order to improve the reservoir performance in East Unity oil field Sudan, the studies focused on characterization, modeling and simulation of the actual performance and future development. A model was constructed using a three-phase, three dimensional, black oil simulator (ECLIPSE). In this study a data from East Unity oil field Sudan started production at July 1999 was used to perform the optimal oil rate and designing the best location of the new operating wells. Cumulative oil production, oil production rate, Water cut and recovery factor were used as key criteria to see if adding new wells in the area under study are economic risk.

Numerical Estimation of the Degree of Reservoir Permeability Heterogeneity Using Pressure Drawdown Tests

This study aims to correlate the response of pressure transient test to permeability distribution type. For this purpose, correlated permeability distributions in x–y direction are generated using fractional Brownian motion (fBm) as it has been shown in literature that permeability in carbonate reservoirs exhibits an fBm type distribution horizontally. 2-D fBm permeability distributions created using mid point displacement method are employed as data to a black oil simulator. The intermittence exponent, H or fractal dimension of the distribution, D, as defined by D=2 − H, characterizes the distribution type. All permeability distributions are normalized to represent the same arithmetic mean (20, 100, and 500 mD) and uniform variance so that only their fractal dimension that underlies the smoothness of the distribution distinguishes them. Many different realizations of permeability distributions are generated based on the random number seeds used and pressure transient (drawdown) tests are simulated using a black oil simulator package (ECLIPSE 100). Pressure transient analysis is performed using PanSystem package. As a base case and for the comparison purpose, the same procedure is repeated for the totally homogeneous case (the same permeability for all grids) and a random (normally distributed) permeability distribution with the same mean and uniform variance. The effects of permeability distribution type on the pressure response are clarified. A strong impact of heterogeneity is observed as an increase in skin effect with increasing fractal dimension of permeability distribution. This additional (or pseudo) skin effect due to heterogeneity is correlated to the fractal dimension of the permeability distribution. As a further step, the procedure is repeated for different flow rates applied during the drawdown test. The correlation between the fractal dimension of permeability distribution and additional skin is improved by incorporating the rate into it. The methodology followed can be used in the assessment of reservoir heterogeneity quantitatively using pressure transient response.

Streamline-based mathematical model for CO2 miscible flooding

According to the research theory of improved black oil simulator, a practical mathematical model for CO2 miscible flooding was presented. In the model, the miscible process simulation was realized by adjusting oil/gas relative permeability and effective viscosity under the condition of miscible flow. In order to predict the production performance fast, streamline method is employed to solve this model as an alternative to traditional finite difference methods. Based on streamline distribution of steady-state flow through porous media with complex boundary confirmed with the boundary element method (BEM), an explicit total variation diminishing (TVD) method is used to solve the one-dimensional flow problem. At the same time, influences of development scheme, solvent slug size, and injection periods on CO2 drive recovery are discussed. The model has the advantages of less information need, fast calculation, and adaptation to calculate CO2 drive performance of all kinds of patterns in a random shaped porous media with assembly boundary. It can be an effective tool for early stage screening and reservoir dynamic management of the CO2 miscible oil field.

Application of a Local Grid Refinement Protocol in Highly Faulted Reservoir Architectures

Abstract A three-dimensional, three-phase black oil simulator is used to model the flow regimes and flow geometries around sealing/non-sealing flow barriers in hydrocarbon reservoirs with homogeneous property distribution. A local grid refinement technique is utilized in these numerical simulation models to accurately capture the flow regimes and flow geometries. Previous work examined a local grid refinement algorithm that was applied to study flow around impermeable barriers, water coning problems, and waterflood front-tracking in horizontal wells. In this paper, we extend the application of the algorithm to account for inclined faults. A system of faults in a large reservoir is considered in all of the cases studied. Sections of the reservoir are solved individually in the presence of geological discontinuities. The results from the static local grid refinement technique indicate a much higher level of accuracy over the results generated using a coarse grid approximation around faulted zones of the reservoir. This level of accuracy is characterized by comparing the results generated by a completely fine grid and/or by a conventional refinement protocol. The proposed model is capable of providing a better representation of faulted reservoir architectures using significantly less CPU time. The proposed model can also be used in pressure transient analysis of wells located near non-sealing fault structures. Introduction In most reservoir simulation studies, the scale of the base grid system is relatively coarse. For more accurate solutions, coarse grid blocks are subdivided into smaller grid blocks, resulting in a fine grid system. In a local grid refinement technique, only certain course blocks, representing specific regions of the area, are subdivided into smaller grid blocks. Local grid refinement applications can be grouped into three general categories: conventional grid refinement, static local grid refinement, and dynamic local grid refinement. In conventional grid refinement, certain regions in a coarse system are subdivided and grid lines are extended to the external boundaries of the reservoir. Static local grid refinement is the same as conventional grid refinement, but the grid lines are not extended to the boundaries of the reservoir. Finally, dynamic local grid refinement finds locally refined areas in the coarse system changing during the simulation. These grid systems are presented in Figure 1. Refinement of the coarse grid system near the faulted areas gives better approximation to the flow model under consideration. Therefore, in this study, only faulted areas and the immediate vicinity of the wells are locally refined. Use of the local grid refinement technique reduces the computational work significantly and results in almost perfect agreement with the fine and conventional grid system's solutions. In order to capture the flow geometries around inclined faults, 3D versions of black oil simulators and single-phase oil and gas models are used. In nature, most of the faults are inclined. Therefore, whether a numerical model can capture the physics and flow regimes around these inclined impermeable barriers will have a critical effect on the accuracy of the results. The local grid refinement technique developed by Biterge and Ertekin(1) is used in this study.

Estimating Oil Reserves of Fields With Oil/Water Transition Zones

Summary The amount of recoverable oil in an oil/water transition zone depends on the distribution of oil saturation as a function of depth and on the relationship between initial and final oil saturation in the transition zone (Soitz and Sortz), as well as the volumetric extent of the zone. Conventionally, it is assumed that Sortz is constant and equal to the residual oil saturation in the oil column (Sor) above the transition zone. However, limited data in the literature show that residual oil saturation depends on initial oil saturation as described by the trapped-oil relationship. Thus, Sortz should be a function of Soitz. The purpose of this paper is to present recent experimental corroboration of the trapped-oil relationship and to demonstrate the impact of the trapped-oil relationship on reserves determination in oil/water transition zones. The effect of the trapped-oil relationship on reserves determination is shown in two ways: first, with an analytical model that shows the maximum possible incremental benefit of including the trapped-oil relationship; and second, with an extended black-oil simulation that incorporates the effects of relative permeabilities on reserves determination.

Development and Optimization of Parallel Code for Large-Scale Petroleum Reservoir Simulation

Abstract This paper discusses the use of large field-scale reservoir simulation to model multiphase fluid flow processes that occur in giant oil reservoirs. The goal of large-scale studies is to model fluid flow with sufficient details to account for reservoir heterogeneity, various reservoir-wellbore configurations, and complex fluid-rock interactions. In this paper, we developed a black-oil reservoir simulator for distributed-memory parallel environment. We ported serial code of a black-oil model to the CRAY T3E and IBM SP2 systems. We analysed the code and benchmarked the performance. To parallelize the code, we used a domain decomposition algorithm, whereby the reservoir is divided into several subdomains, with each subdomain assigned to a separate processor element (PE). The message-passing interface (MPI) is used to exchange information across subdomains. We validated the parallel simulator using data from the Society of Petroleum Engineers comparative solution projects. Because the linear equation solver accounts for over 90% of the CPU time in a typical reservoir simulation run, we evaluated the performance of several parallel algorithms in the project, including LSOR, Gauss-Siedel (GS) and strongly implicit procedure (SIP). We found that the convergence behaviour of the solver depends on the number of processors and on the permeability anisotropy of the reservoir. For the problems we tested, the SIP algorithms provided the best performance. We compared the computational efficiency of the parallel code against the serial code using models containing up to 350,000 grid blocks in 4-, 8-, 16- 32-, 64-, and 80-PE environments. The paper discusses programming and computational performance issues in large-scale reservoir simulation for parallel systems. Introduction The objective of large field-scale reservoir simulation is to model multiphase fluid flow processes that occur in giant oil reservoirs with sufficient details to account for reservoir heterogeneity, various reservoir-wellbore configurations, and complex fluid-rock interactions. The simulations often require using over one million grid blocks to accurately capture reservoir heterogeneity and multiphase flow behaviour in the full-field models. In the past, limited computer resources forced engineers to use coarse grid blocks for field-scale studies at the expense of accuracy. Advances in parallel computing technology provide engineers modern tools to solve previously computationally expensive problems at competitive costs. In this paper, we developed a black-oil reservoir simulator for distributed-memory parallel environment. The serial code of a black-oil model was ported to the CRAY T3E. After pre-parallelization analysis and optimization of the code for a singleprocessor performance(1), we used a multi-level, domain decomposition algorithm to parallelize the code. Domain decomposition involves dividing the reservoir into several subdomains, with each subdomain assigned to a separate processor element (PE). The message-passing interface (MPI) is used to exchange information between the multiple processors. The use of MPI permits the portability of the reservoir simulator from the massively parallel environments to network of workstations. We validated the code and analysed the performance of the parallel simulator using data from the Society of Petroleum Engineers comparative solution projects. The paper is organized in the following sections. First, we discuss the simulator development.

Solution-Gas Drive in Heavy Oil: Field Prediction and Sensitivity Studies Using Low Gas Relative Permeability

Abstract The favourable behaviour of heavy oil reservoirs under solution- gas drive has intrigued the oil industry for a long time. Many mechanistic models have been proposed to explain this behaviour. This paper investigates one of the theories that attributes the low producing GOR and high recovery of heavy oil to low gas mobility. A simulation study was carried out on a commercial black oil simulator to match the "typical" production data of heavy oil fields in Lindbergh and Frog Lake. Sensitivity studies were carried out to investigate the effect of gas relative permeability on oil recovery. The effect of sand production, which is an integral part of heavy oil production in Western Canada, was also investigated. A parameter was used in the simulator to account for the increased permeability due to sand production. The results indicate that the field performance can be matched by using low gas mobility and incorporating improved permeability due to sand production. Neither of them alone was sufficient for matching the field performance. The use of a low gas mobility was successful to explain high pressure-gradients in the field, by acting as a pressure maintenance mechanism, and leading to a high recovery under solution-gas drive. Intruduction PanCanadian has been one of the major operators in the Lindbergh and Frog Lake heavy oil fields of northeast Alberta(1). The production in these fields is from the Upper Mannville group. The producing formations contain oil of 12 – 14 ° API with in situ viscosities of 3,000 – 10,000 cp. The fields have shown recovery much in excess of what can be predicted by applying conventional flow equations. Many heavy oil wells under primary production have produced about 15% of the original oil in place (OOIP) in 10 years(1). The primary oil production in these fields is accompanied by sand production and is called "Cold Production." A typical well in the Lindbergh and Frog Lake fields under depletion has produced an average of 9,200 m3 of oil and about 230 m3 of sand in 1,000 days(1). Several tests have been carried out to determine the mechanism responsible for the favourable behaviour of these reservoirs. Metwally and Solanki(1) presented a simulation model to match the field production behaviour. The authors postulated that reservoir porosity and permeability are increased due to sand production. Additionally, the authors showed that a pressure support mechanism needs to be incorporated to match recovery data; an external aquifer was therefore incorporated into the model. Similar to Metwally and Solanki(1), we use a commercial simulator to match the production data. We show that the use of low values for gas relative permeability results in pressure maintenance and substantial oil production. Accounting for the low gas mobility along with the improved permeability resulted in a match of the field data. Sensitivity studies are reported, which show that both the effects of low gas mobility and improved permeability are required for a match.

A two-phase flow simulation of a fractured reservoir using a new fissure element method

Modeling of a fissure network is conventionally done using a dual porosity–dual permeability model, but this type of model involves large-scale approximate description of fluid transfers between the matrix and fissure. For understanding of the simplifications involved in the dual porosity approach, a fine description of the fissure network is necessary. To obtain this fine scale description, a new methodology was developed for the modeling of flow in fractured reservoirs. This technique called “the fissure element methodology” is based on application of a specific grid to the fractured medium. This unstructured grid is made of two kinds of elements, linear elements for the fissure network and triangular elements for the matrix. An appropriate finite volume scheme has been developed to provide a good description of the flow at the fissure–matrix interface and a good representation of the geometry. A specific numerical treatment of fissure intersections is proposed. The method has been validated by comparison with results from a classical black-oil simulator run on a finely gridded Cartesian model. Comparisons have been done also with a dual porosity–dual permeability model. The new tool will permit to run reference simulations for the validation of new formulations of the matrix–fissure exchange in dual-porosity simulators.

Megacell Reservoir Simulation

Reservoir simulation has moved into a new era with the rapid advancements in parallel-computer hardware and software technologies. In the past decade, the total number of gridblocks used in a typical reservoir study increased from thousands to millions. Mega (million) -cell simulation capability allows accurate representation of reservoirs because of its ability to include detailed information provided by logs, 3D seismic, horizontal wells, and stratigraphic studies. One of the main advantages of megacell simulation is that it minimizes or eliminates upscaling effects, making more-accurate reservoir-performance predictions possible. Further more, the speed of parallel computers significantly reduces the manpower-intensive history-matching process. Megacell simulators typically are developed on parallel computers With the current low-cost parallel computers, a million-cell simulation run covering 20 years of production history takes less than 1 hour, State-of-the-art computer graphics provide an effective means of visualizing large data sets covering million-cell descriptions of a reservoir and its performance. This paper presents an overview of megacell simulation technologies in the oil industry and academia.

HORIZONTAL WELL LENGTH OPTIMIZATION FOR A SOUTH OMAN FIELD

ABSTRACT Oman produces around 850,000 bbl/day of crude oil from around 85 fields of which 35% comes from horizontal wells. Horizontal drilling was started in 1986 with three short radius wells drilled in chalky oil reservoirs due to gas or water coning and low production rates. Results were not sufficiently encouraging to lead to future activity in the short term. Horizontal drilling technology evolved rapidly and in 1990, Oman embarked on a more ambitious program. The results, this time, were so impressive that the trial was extended and has led to almost continuous horizontal drilling. Some 100 horizontal wells per year are expected to be drilled for the foreseeable future. These wells exploit both clastic and carbonate reservoirs from Precambrian to Cretaceous age, thin and thick oil columns, light and heavy oil, and a wide range of reservoir quality. Multilateral drilling in Oman has also shown significant benefits in increased production rates, reduced costs and increased oil recovery from existing producing fields and previously uncommercial oil accumulations. Well costs have been reduced by optimising the well design and drilling operations. The most significant cost saving has been due to a reduction in hole size and casing scheme. The main focus of this project is optimizing oil recovery in a South Oman oil field using multilateral well technology. It mainly outlines both the effects of horizontal length and number of horizontal legs completed for different reservoir properties using Eclipse 100 black-oil simulator as a numerical tool. Eclipse black-oil simulator is utilized in order to formulate the reservoir models of the concerned field and two other synthetic reservoirs having different rock properties. In order to generalize the findings, correlations are developed for different rock properties. That way predictions for optimum well conditions for any particular field in Oman could be established.

SELECTIVE COMPLETION FOR HORIZONTAL WELLS DRILLED IN A FRACTURED OMANI RESERVOIR

ABSTRACT Reservoir simulation sensitivity analysis and unit technical cost analyses are used in order to determine the optimum well performance of a horizontal well that is selectively completed in one of the fractured Omani reservoirs. A black-oil model representing one heavily fractured Omani field was used in the analysis with a match box-like reservoir structure. The fractures are taken as thin streaks penetrating the reservoir vertically with high permeability along X, Y and Z- directions. Matrix block permeability values are drastically lower than those characterizing fracture block permeability. Eclipse 100 black-oil simulator was used throughout the study to analyze the effect of fracture frequency and to obtain the optimum completion by investigating different isolation length for fractured horizontal producers, injectors and both producers and injectors. The sensitivity analysis involves building numerous models for 2mD, 10mD and 50mD. That is because the range of permeability in the field is not very well defined. But, it is thought to be in the above selected range. The objective being to determine the optimum completion that gives the best performance associated with the lowest cost after several selective completion options are tested for different fracture frequency and for different type of wells (producers, injectors or both).

Effect of fractal permeability correlations on waterflooding performance in carbonate reservoirs

The objective of this paper is to investigate the response of correlated permeability distributions to field scale immiscible flooding and relate the output to correlation parameter. Synthetic cross-section porosity maps are generated using fractional Brownian motion (fBm) statistics in vertical direction and then the porosities are converted to permeabilities using an exponential correlation as data to black oil simulator. The intermittency coefficient, H, that characterizes the roughness of the distribution is varied between two extremes; 0.4 and 0.95. For each set of porosity distributions with different H value, different random number seed is used. Permeabilities are generated from the fBm porosities distributed between the same minimum and maximum values with uniform variance for all Hs. Then, simulations are carried out to explore the effects of H on the waterflooding performance. It is found that the displacement efficiency increases with increasing H of the distribution. The effect of the roughness of the permeability field is more significant on water–oil ratio and breakthrough time than on the cumulative oil production and oil production rate. At the end, an evaluation of a field case is provided. The performance of a five-spot waterflooding in a carbonate reservoir is evaluated for different distribution types, namely vertical and horizontal fBm distributions.

Fast Procedure for Upscaling Compositional Simulation

Summary Single-phase upscaling techniques have been in use for a number of years now to incorporate subgrid reservoir description information into reservoir simulation. There have also been a number of approaches to developing two-phase upscaling algorithms suitable for black oil simulation. The key barrier to the development of compositional upscaling techniques is algorithm speed. A straightforward extension of existing two-phase upscaling approaches would consume enormous amounts of computer time because of the number of additional components modeled and the need to perform flash calculations. This paper describes an upscaling method for simulations in which compositional processes play a key role, such as miscible gas injection or gas cycling schemes. We will describe the method to generate upscaled compositional fluxes in two or three dimensions, and the way in which the upscaled fluxes are incorporated into a compositional simulator. Our approach uses a streamline technique, which provides a tremendous gain in speed for the loss of a small amount of accuracy. The streamline technique produces upscaled fluxes almost identical to those obtained from postprocessing conventional compositional model runs in a fraction of the time. The results of applying these upscaled fluxes in a realistic example show that we can obtain close agreement between fine and coarse grid models of lean gas injection into oil at residual saturation. For an example problem with a 12-component equation of state (EOS), the component recovery curves with upscaled fluxes on a 5 × 5 grid agree well with the original 100 × 20 fine grid