Compositional Reservoir Simulation Research Articles

A new robust stability algorithm for three phase flash calculations in presence of water

Thermodynamic phase equilibrium calculations for systems containing water are inseparable parts of the compositional hydrocarbon reservoir simulation. In this regard, stability analysis of the phases for distinguishing the existing ones at specific pressures and temperatures is a principal part of such calculations. This study is aimed to develop a new stability algorithm with application to three phase flash calculations in the presence of brine. The developed scheme is capable of doing the phase behavior calculations in a more robust way compared to the other available algorithms. Henry's law is utilized to predict the aqueous phase properties, and a new initial guess is provided for three phase flash calculations that assures the convergence of the scheme. It is shown that the proposed procedure is able to handle the systems with high CO2 content while the available schemes in the literature fail.

An Experimental and Numerical Analysis of Water-Alternating-Gas and Simultaneous-Water-and-Gas Displacements for Carbon Dioxide Enhanced Oil Recovery and Storage

Summary This paper presents an experimental and numerical study that delineates the co-optimization of carbon dioxide (CO2) storage and enhanced oil recovery (EOR) in water-alternating-gas (WAG) and simultaneous-water-and-gas (SWAG) injection schemes. Various miscibility conditions and injection schemes are investigated. Experiments are conducted on a homogeneous, outcrop Bentheimer sandstone sample. A mixture of hexane (C6) and decane (C10) is used for the oil phase. Experiments are run at 70°C and three different pressures (1,300, 1,700, and 2,100 psi) to represent immiscible, near-miscible, and miscible displacements, respectively. WAG displacements are performed at a WAG ratio of 1:1, and a fractional gas injection (FGI) of 0.5 is used for SWAG displacements. The effect of varying FGI is also examined for the near-miscible SWAG displacement. Oil recovery, differential pressure, and compositions are recorded during experiments. A co-optimization function for CO2 storage and incremental oil production is defined and calculated by use of the measured data for each experiment. The results of SWAG and WAG displacements are compared with the experimental data of continuous-gas-injection (CGI) displacements. A compositional commercial reservoir simulator is used to examine the recovery mechanisms and the effect of mobile water on gas mobility. Experimental observations demonstrate that the WAG displacements generally yield higher co-optimization function than CGI and SWAG with FGI = 0.5 displacements. Numerical simulations show a remarkable reduction in gas relative permeability for the WAG and SWAG displacements compared with CGI displacements, as a result of which the vertical-sweep efficiency of CO2 is improved. More reduction of gas relative permeability is observed in the miscible and near-miscible displacements than in the immiscible displacement. The reduced gas relative permeability lowers the water-shielding effect, thereby enhancing oil recovery and CO2-storage efficiency. More water-shielding effect is observed in SWAG with FGI = 0.5 than in WAG. However, increasing FGI from 0.5 to 0.75 in the near-miscible SWAG displacement shows a significant increase in oil recovery, which is attributed to reduced water-shielding effect. So, an optimal FGI needs to be determined to minimize the water-shielding effect for efficient SWAG displacements.

Upscaling for Compositional Reservoir Simulation

Summary Compositional flow simulation, which is required for modeling enhanced-oil-recovery (EOR) operations, can be very expensive computationally, particularly when the geological model is highly resolved. It is therefore difficult to apply computational procedures that require large numbers of flow simulations, such as optimization, for EOR processes. In this paper, we develop an accurate and robust upscaling procedure for oil/gas compositional flow simulation. The method requires a global fine-scale compositional simulation, from which we compute the required upscaled parameters and functions associated with each coarse-scale interface or wellblock. These include coarse-scale transmissibilities, upscaled relative permeability functions, and so-called α-factors, which act to capture component flow rates in the oil and gas phases. Specialized near-well treatments for both injection and production wells are introduced. An iterative procedure for optimizing the α-factors is incorporated to further improve coarse-model accuracy. The upscaling methodology is applied to two example cases, a 2D model with eight components and a 3D model with four components, with flow in both cases driven by wells arranged in a five-spot pattern. Numerical results demonstrate that the global compositional upscaling procedure consistently provides very accurate coarse results for both phase and component production rates, at both the field and well level. The robustness of the compositionally upscaled models is assessed by simulating cases with time-varying well bottomhole pressures that are significantly different from those used when the coarse model was constructed. The coarse models are shown to provide accurate predictions in these tests, indicating that the upscaled model is robust with respect to well settings. This suggests that one can use upscaled models generated from our procedure to mitigate computational demands in important applications such as well-control optimization.

Reconciling flowback and production data: A novel history matching approach for liquid rich shale wells

The recent downturn in petroleum prices poses a challenge to the oil and gas industry and in particular to the development of shale assets. This unfavorable economic situation calls for improved reservoir characterization and modeling that are necessary for the optimization of well design and cost. Current rate transient analysis (RTA) techniques are well-suited for the reservoir characterization of dry shale gas wells. However, they have limited accuracy for the more profitable liquid rich shale (LRS) wells. For example, RTA does not accurately model three-phase flow of gas, water, and condensate that can occur in the reservoir. Further, application of RTA typically ignores post-fracturing water flowback data that can be analyzed for important information pertaining to hydraulic and secondary fractures. In this work, the reservoir of LRS wells is characterized by simulating and history matching the three-phase flow of early flowback and long-term production.In this work, characterization and history matching are performed by utilizing a novel procedure that includes an equation of state (EOS), a compositional reservoir simulator, and a multi-objective optimization (MOO) algorithm. In addition, the simulation approach incorporates various water trapping mechanisms that are necessary to reproduce the water production rate trends. The procedure minimizes the misfit between observed and simulated production data. It starts by first tuning the EOS to a surface recombined sample. Then, a triple-porosity (i.e., hydraulic fracture, secondary/natural fracture, and matrix porosities) simulation model is applied that utilizes the multiple interacting continua (MINC) method and accounts for permeability jail, pressure-dependent permeability, capillary pressure, and gravity segregation. Finally, an MOO algorithm is used, namely the fast nondominant sorting genetic algorithm (NSGA-II), to solve the misfit minimization problem.The introduced procedure has a number of advantages. One advantage is the simultaneous matching of flowback and production data which improves rock and fracture characterization. Another advantage is the utilization of MINC combined with logarithmic gridding that can model transient flow in a triple porosity system. Moreover, it can model different fracture shapes by adjusting a shape factor parameter. In addition to these, the use of MOO does not require predetermined weights unlike the aggregate function approach. In this article, detailed description of all the steps of the history matching workflow are presented, and its applicability demonstrated with a field example from the Montney Formation.

Mechanistic Modeling of Low-Salinity Waterflooding Through Coupling a Geochemical Package With a Compositional Reservoir Simulator

SummaryLow-salinity waterflooding is an emerging enhanced-oil-recovery (EOR) technique in which the salinity of the injected water is substantially reduced to improve oil recovery over conventional higher-salinity waterflooding. Although there are many low-salinity experimental results reported in the literature, publications on modeling this process are rare. Although there remains some debate regarding the mechanisms of low salinity waterflooding process (LoSal EOR®)*, the geochemical reactions that control the wetting of crude oil on the rock are likely to be central to a detailed description of the process. Because no comprehensive geochemical-based modeling has been applied in this area, it was decided to couple a state-of-the-art geochemical package, IPhreeqc (Charlton and Parkhurst 2011), developed by the US Geological Survey, with UTCOMP (Chang 1990), the compositional reservoir simulator developed by The University of Texas at Austin.A step-by-step algorithm is presented for integrating IPhreeqc with UTCOMP. Through this coupling, we are able to simulate homogeneous and heterogeneous (mineral dissolution/precipitation), irreversible, and ion-exchange reactions under nonisothermal, nonisobaric, and both local-equilibrium (away from the wellbore) and kinetic (near wellbore) conditions. Consistent with the literature, there are significant effects of water-soluble hydrocarbon components—e.g., carbon dioxide (CO2), methane (CH4), and acidic/basic components of the crude—on buffering the aqueous pH value and more generally, on the crude oil, brine, and rock reactions. Thermodynamic constraints are used to explicitly include the effect of these water-soluble hydrocarbon components. Hence, this combines the geochemical power of IPhreeqc with the important aspects of hydrocarbon flow and compositional effects to produce a robust, flexible, and accurate integrated tool capable of including the reactions needed to mechanistically model low-salinity waterflooding.Different geochemical-based approaches to modeling wettability change in sandstones (e.g., interpolation on the basis of total ionic strength and multicomponent ion exchange through surface complexation of the organometallic components) were implemented in UTCOMP-IPhreeqc, and the integrated tool is then used to match and interpret a low-salinity experiment published by Kozaki (2012) and the field trial performed by BP at the Endicott field.

A field-scale investigation of residual and dissolution trapping of CO2 in a saline formation in Western Australia

In a typical carbon capture and storage project, residual and dissolution trapping is expected to play a significant role in minimising the risk associated with the containment. Various methods of maximising each trapping mechanism individually have been proposed in the literature. Yet, in actual projects, it is expected that these trapping mechanisms occur interactively. This area still remains unexplored.This paper presents the results of a numerical investigation of technically feasible engineering designs to co-optimise both trapping mechanisms. It integrates a geological model developed for an actual saline formation in Australia, along with other available reservoir engineering data using a compositional numerical reservoir simulator. The scenario involves injecting supercritical CO2 at a commercial rate into a thick, deep, layered, heterogeneous, high porosity, high-permeability sandstone formation that initially contains only water of high salinity. The design objective is to inject more than 200 million tonnes of CO2 over 40 years. Compositional interactions between formation water and injected CO2 are modelled using the Peng–Robinson equation of state. We examine different injection schemes to find out the scenario that maximises dissolution and residual trapping. These schemes include vertical wells, horizontal wells, water alternate gas injection (WAG) and simultaneous water and gas injection (SWAG).The results show that heterogeneity has a significant effect on the location of perforations. The middle region of the Wonnerup Member appears to be the optimum location for CO2 injection where desired amount of CO2 can be injected while a maximum benefit of residual trapping can be achieved. Horizontal wells appear to enhance residual trapping the most, whereas WAG enhances dissolution trapping the most. Furthermore, WAG scenarios result in the least mobile CO2, and therefore, show the highest cumulative potential for both residual and dissolution trapping. However, in terms of relative economics, vertical injection wells appear to be the most viable option.

The application of static load balancers in parallel compositional reservoir simulation on distributed memory system

Compositional reservoir simulation depicts the complex behaviors of all the components in gaseous, liquid, and oil phases. It helps to understand the dynamic changes in reservoirs. Parallel computing is implemented to speed up simulation in large scale fields. However, there is still many challenges in obtaining efficient and cost-effective parallel reservoir simulation. Load imbalance on processors in the parallel machine is a major problem and it severely affects the performance of parallel implementation in compositional reservoir simulators. This article presents a new approach to the reduction of load imbalance among processors in large scale parallel compositional reservoir simulation. The approach is based on graph partitioning techniques: Metis partitioning and spectral partitioning. These techniques treat the simulation grid, or the mesh, as a graph constituted by vertices and edges, and then partition the graph into smaller domains. Metis and spectral partitioning techniques are advantageous because they take into account the potential computational load of each grid block in the mesh and generate smaller partitions for heavy computational load areas and larger partitions for light computational load areas. In our case, the computational load is represented by transmissibility. After new partitions are generated, each of them is assigned to a processor in the parallel machine and new parallel reservoir simulation can be conducted. Traditionally, the intuitive 2D decomposition is frequently used to partition the simulation grid into small rectangles, and this is a major source of load imbalance. The performance of parallel compositional simulation based on our partitioning techniques is compared with the most commonly used 2D decomposition and it is found that load imbalance in our new simulations is reduced when compared with the traditional 2D decomposition. This study improves the efficiency of compositional simulation and eventually makes it more cost-effective for hydrocarbon simulation on mega-scale reservoir models.

A Laboratory and Numerical-Simulation Study of Co-Optimizing CO2 Storage and CO2 Enhanced Oil Recovery

Summary This paper presents experimental observations that delineate co-optimization of carbon dioxide (CO2) enhanced oil recovery (EOR) and storage. Pure supercritical CO2 is injected into a homogeneous outcrop sandstone sample saturated with oil and immobile water under various miscibility conditions. A mixture of hexane and decane is used for the oil phase. Experiments are run at 70°C and three different pressures (1,300, 1,700, and 2,100 psi). Each pressure is determined by use of a pressure/volume/temperature simulator to create immiscible, near-miscible, and miscible displacements. Oil recovery, differential pressure, and compositions are recorded during experiments. A co-optimization function for CO2 storage and incremental oil is defined and calculated using the measured data for each experiment. A compositional reservoir simulator is then used to examine gravity effects on displacements and to derive relative permeabilities. Experimental observations demonstrate that almost similar oil recovery is achieved during miscible and near-miscible displacements whereas approximately 18% less recovery is recorded in the immiscible displacement. More heavy component (decane) is recovered in the miscible and near-miscible displacements than in the immiscible displacement. The co-optimization function suggests that the near-miscible displacement yields the highest CO2-storage efficiency and displays the best performance for coupling CO2 EOR and storage. Numerical simulations show that, even on the laboratory scale, there are significant gravity effects in the near-miscible and miscible displacements. It is revealed that the near-miscible and miscible recoveries depend strongly on the endpoint effective CO2 permeability.

Reservoir Screening for EOR Potential for the Western North Slope, Alaska

The Western North Slope of Alaska is an oil-rich zone located in the Colville river unit close to the Eastern boundary of National Petroleum Reserve Alaska. With an objective to find better enhanced oil recovery solutions and improve recoveries, four reservoirs from the Western North Slope were screened for different enhanced oil recovery methods to find the most suitable option. Based on the initial screening, gas injection was found to be the preferred method. This was followed by the determination of optimum injection gas compositions for Western North Slope reservoirs and their rank, thereby developing a new ranking methodology for gas flooding projects. The work was accomplished via a combination of two custom developed Excel spreadsheets for the determination of minimum miscibility pressure and enrichment respectively and several numerical experiments carried out using a compositional reservoir simulator, the results of which were applied for parametric ranking of the four Western North Slope reservoirs.

Physics based HLD–NAC phase behavior model for surfactant/crude oil/brine systems

Abstract Compositional simulation of surfactant flooding highly depends on accurate modeling of surfactant/oil/brine microemulsion phase behavior. This paper introduces a physics-based Hydrophilic–Lipophilic Difference (HLD) equation and the Net-Average Curvature (NAC) called thereafter HLD–NAC equation of state to model the phase behavior of surfactant/crude oil/brine systems. A non-iterative and physics-based algorithm is developed and validated by modeling the solubilization ratio curves and phase volume fraction of different microemulsion systems. The HLD values are calculated by the natural logarithm of salinity over optimum salinity when lacking of oil hydrophobicity and surfactant Characteristic curvature information. Together with lab measured head area of per surfactant molecule, the HLD–NAC model reproduces the microemulsion phase behavior of various formulations for surfactant flooding with only one fitting parameter, the length constant L, which physically represents the surfactant tail length size. Modeling results show that the fitted parameter increases with the surfactant or surfactant mixture tail length in the formulation. Moreover, the length parameter determined from one system can be readily applied to other systems, indicating the physical significance of the HLD–NAC model, which can to some extent predict the performance of one surfactant in various systems. The fitted length parameter for formulations with alcohol is underestimated because of this paper assuming all alcohol partition on the interface leading to overestimated interfacial area. The effect of cosolvent partitioning on the micelle structure and phase behavior modeling will be demonstrated in future studies. In this paper, the HLD–NAC equation of state is proved to be a simple and robust tool for modeling phase behavior of surfactant/crude oil/brine systems. The HLD–NAC model can shorten the surfactant screening process hence help chemical EOR formulation design and optimization, and can also be used in compositional chemical flooding reservoir simulation to improve the predictability of surfactant floods.

Comparison of two volume balance fully implicit approaches in conjunction with unstructured grids for compositional reservoir simulation

In reservoir simulation, compositional modeling is one of the most commonly used approaches for enhanced oil recovery processes. The methods used to solve the equations arising from the modeling of fluid flow in the reservoirs involve the degree of implicitness and the selection of the primary and secondary equations; primary and secondary variables have a great impact on the computational time. In this work, we implement and compare two fully implicit methods based on volume balance approach. The two methods share the same set of primary variables: pressure and total number of moles of each component. The total number of moles of each component is solved with use its material balance equation, whereas the pressure is solved with use of a volume balance equation. The difference between the two methods is in the nature of the volume balance equation. Whereas for one of the formulations the volume balance equation is the volume constraint and hence the only terms that appear in the Jacobian matrix are those from the volume in which the volume balance is evaluated, the second formulation considers an expanded form of the volume constraint. The main advantage of this expanded equation is that the Jacobian matrix involves information from the volume in which the balance is performed and from all neighboring volumes. The element-based finite-volume method in conjunction with unstructured grids for 2D and 3D reservoirs is used to discretize the material and volume balance equations. For two dimensions, quadrilateral and triangular elements are considered, whereas for three dimensions, hexahedral, prismatic, tetrahedral, and pyramidal elements are considered. The implementations were performed with the UTCOMP simulator developed at the University of Texas at Austin. We compare the performance of the two above-mentioned fully implicit formulations with the implicit pressure explicit composition (IMPEC) formulation of the UTCOMP simulator. The results of several case studies are compared in terms of volumetric oil and gas rates and the total CPU time. The results show good agreement between the production rates and saturation fields for all formulations. Additionally, the performance of the fully implicit methods was superior to that of the IMPEC method as a larger number of grid blocks were used in the simulations.

An improved component retrieval method for cubic equations of state with non-zero binary interaction coefficients for natural oil and gas

Volumetric and equilibrium calculations for the natural gas and oil defined by a large number of components are not feasible in applications like compositional reservoir simulation. Therefore, the fluid mixture is grouped to reduce computational load and to make faster calculations. However, for several reasons, it is required to have the detailed fluid composition rather than the lumped one. In this work, an improved delumping method is presented to retrieve the phase composition of the detailed mixture based on the grouped mixture thermodynamic calculations. The method is based on previously proposed delumping techniques for non-cubic equation of state (Assareh et al. in Fluid Phase Equilib 339:40–51, 2013). To prepare lumped mixtures, a grouping technique, based on the components similarity, is used to classify the components with close critical properties and binary interaction coefficients in a pseudo-component (Assareh et al. in Int J Oil Gas Coal Technol 7(3):275–297, 2014). Afterward, a number of delumping parameters calculated from lumped system flash calculation are assigned to the components in a specific pseudo-component. The detailed mixture equilibrium ratios based on fugacity coefficient for a common cubic equation of state are calculated using these delumping coefficients. The accuracy of the method is verified on two petroleum reservoir fluids, a gas condensate and an oil reservoir fluid. The delumped equilibrium ratios were in good agreement with detailed ones with the absolute deviation of less than 2 %. The results confirm the applicability and accuracy of the presented method for detailed composition retrieval while simulating with pseudo-components.

Multiphase equilibrium calculations using a reduction method

Phase equilibrium problems (phase stability testing and multiphase flash) have to be solved repeatedly, sometimes a very large number of times, in process simulators and in compositional reservoir simulation. The computational effort can be significant, particularly when a detailed description (with a large number of components nc) of the mixture is required. The reduction method represent an attractive technique in the attempt to reduce the computational time, by significantly reducing the dimensionality of the problem, from nc×(np−1) in the conventional methods to a maximum of (2c+3)×(np−1), where np is the number of equilibrium phases and c the number of components with non-zero binary interaction parameters (BIP). The number of independent variables does not depend on nc, but only on c, and the computation time increases linearly with nc. Traditionally, the reduction approaches use the reduction parameters and the phase mole fractions as independent variables. In this work, a recent improvement of two-phase reduced flash calculations (Nichita and Graciaa, Fluid Phase Equilib. 302, 2011, 226–233) is extended to multiphase equilibrium calculation with any number of phases. Two approaches are proposed: (i) a direct extension of the reduction method for two-phase flashes and (ii) a constrained minimization Gibbs free energy with respect to a specific set of variables and constraints (taking advantage of symmetry). The proposed algorithms are tested for several multiphase systems (with up to four phases and exhibiting complex phase envelopes) containing hydrocarbon components, carbon dioxide and hydrogen sulfide. Numerical experiments show that the reduction methods for multiphase flash calculations are robust and they become faster than the conventional methods when (i) the number of components increases, (ii) the number of equilibrium phases increases and (iii) the number of BIP families decreases. For mixtures with many components and few BIP families, the reduction method may be at least one order of magnitude faster than conventional methods.

Modeling of capacitance flow behavior in EOS compositional simulation

Abstract Gas injection is a widely used method for enhanced oil recovery. Oil bypassing by gas occurs at different scales because of micro and macroscopic heterogeneities, gravity segregation, and front instability. Part of the bypassed oil can be recovered by crossflow between the bypassed and flowing regions. This characteristic of reservoir flow is referred to as capacitance flow behavior in the literature. Modeling of such flow behavior at the sub-grid scale is challenging in the conventional flow simulation since fluids are perfectly mixed and in equilibrium within individual grid blocks under the local equilibrium assumption. This research investigates capacitance flow behavior in compositional reservoir simulation. An efficient two-step method is presented to model bypassed oil recovery in multiphase compositional flow simulation of gas floods. The oil bypassing is first quantified by use of the dual-porosity flow with two dimensionless groups; bypassed fraction and throughput ratio. To represent bypassed oil recovery in single-porosity flow, a new flow-based fluid characterization is applied to part of the heavy fractions of the fluid model used. Properties for pseudo components can be determined based on the throughput ratio estimated in the dual-porosity flow. Case studies for various reservoir/fluid properties show that single-porosity flow with the new method reasonably represents bypassed oil recovery observed in core floods and fine-scale heterogeneous simulations.

AN EOS-BASED NUMERICAL SIMULATION OF THERMAL RECOVERY PROCESS USING UNSTRUCTURED MESHES

In the past thirty years, the development of compositional reservoir simulators using an equation of state (EOS) has been addressed in the literature. However, the development of compositional thermal simulators in conjunction with the EOS formulation, in particular, has not been addressed extensively. In this work, a fully implicit, thermal, compositional EOS-based simulator in conjunction with unstructured meshes has been developed. In this model, an equation of state is used for equilibrium calculations among phases. Also, the physical properties are calculated based on an EOS, hence obviating the need for using steam tables for calculation of water/steam properties. The governing equations for the model comprise fugacity equations, material balance, pore volume constraint and energy equation. The governing partial differential equations are solved using the EbFVM (Element based Finite Volume Method). Results for several case studies consisting of 2D and 3D reservoirs are presented in order to demonstrate the applicability of the method.

Application of Multiple-Mixing-Cell Method To Improve Speed and Robustness of Compositional Simulation

Summary Standard equation-of-state-based phase equilibrium modeling in reservoir simulators involves computationally intensive and time-consuming iterative calculations for stability analysis and flash calculations. Therefore, speeding up stability analysis and flash calculations and improving robustness of the calculations are of utmost importance in compositional reservoir simulation. Prior knowledge of the tie-lines traversed by the solution of a gas-injection problem translates into valuable information with significant implications for speed and robustness of reservoir simulators. The solution of actual-gas-injection processes follows a very complex route because of dispersion, pressure variations, and multidimensional flow. The multiple-mixing-cell (MMC) method, originally developed to calculate minimum miscibility pressure of a gas-injection process, accounts for various levels of mixing of the injected gas and initial oil. This observation suggests that the MMC tie-lines developed upon repeated contacts may represent a significant fraction of the actual simulation tie-lines encountered. We investigate this idea and use three tie-line-based K-value-simulation methods for application of MMC tie-lines in reservoir simulation. In two of the tie-line-based K-value-simulation methods, we examine tabulation and interpolation of MMC tie-lines in a framework similar to the compositional-space adaptive-tabulation (CSAT) method. In the third method, we perform K-value simulations based on inverse-distance interpolation of K-values from MMC tie-lines. We demonstrate that for the displacements examined, the MMC tie-lines are sufficiently close to the actual simulation tie-lines and provide excellent coverage of the simulation compositional route. The MMC-based methods are then compared with the computational time by use of other methods of phase-equilibrium calculations, including a modified application of CSAT (an adaptive tie-line-based K-value simulation), a method using only heuristic techniques, and the standard method in an implicit-pressure/explicit-concentration-type reservoir simulator. The results show that tabulation and interpolation of MMC tie-lines significantly improve phase equilibrium and computational time compared with the standard approach, with acceptable accuracy. The results also show that computational performance of the MMC-based methods with only prior tie-line tables is very close to that of CSAT, which requires flash calculations during simulation. The K-value simulations by use of MMC-based tie-line-interpolation methods improve the total computational time up to 51% in the cases studied, with acceptable accuracy. The results suggest that MMC tie-lines represent a significant fraction of the actual tie-lines during simulation and can be used to significantly improve speed and robustness of phase-equilibrium calculations in reservoir simulators.

Reservoir simulation and optimization of Huff-and-Puff operations in the Bakken Shale

A numerical reservoir model was created to optimize Huff-and-Puff operations in the Bakken Shale. Huff-and-Puff is an enhanced oil recovery method in which a well alternates between injection, soaking, and production. Injecting CO2 (or other gases) into the formation and allowing it to “soak” re-pressurizes the reservoir and improves oil mobility, boosting production from the well. A compositional reservoir simulator (CMG GEM) was used to study various design components of the Huff-and-Puff process in order to identify the parameters with the largest impact on recovery and understand the reservoir’s response to cyclical gas injection. It was found that starting Huff-and-Puff too early in the life of the well diminishes its effectiveness, and that shorter soaking periods are preferable over longer waiting times. Huff-and-Puff works best in reservoirs with highly-conductive natural fracture networks, which allow CO2 to migrate deep into the formation and mix with the reservoir fluids. Doubling the number of hydraulic fractures per stage results in considerably greater gas injection requirements without proportionally larger incremental recovery factors. Incremental recovery from CO2 Huff-and-Puff appears to be insufficient to make the process commercially feasible under current economic conditions. However, re-injecting mixtures of CO2 and produced hydrocarbon gases was shown to be technically and economically viable, and could significantly improve profit margins of Huff-and-Puff operations.

Modeling of EOR in Shale Reservoirs Stimulated by Cyclic Gas Injection

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 169069, ’Compositional Modeling of EOR Process in Shale Oil Reservoirs Stimulated by Cyclic Gas Injection,’ by Tao Wan, Xingbang Meng, James J. Sheng, SPE, and Marshall Watson, SPE, Texas Tech University, prepared for the 2014 SPE Improved Oil Recovery Symposium, Tulsa, 12-16 April. The paper has not been peer reviewed. Cyclic gas injection combined with modern technologies such as horizontal drilling and hydraulic fracturing has achieved promising results in low-permeability formations. This paper focuses on the effects of injected-gas composition and fracture properties on oil recovery, concluding that cyclic gas injection in hydraulically fractured shale oil reservoirs is feasible for improving oil production substantially over primary production. Introduction Cyclic gas injection is an effective and quick-responding enhanced-oil-recovery (EOR) method in intensely naturally fractured or hydraulically fractured reservoirs. The short payout is a characteristic that should attract industry’s interest in investing in these types of projects. Recent studies showed that cyclic gas injection could be a viable method to improve the oil recovery in shale oil reservoirs, but those studies were performed on the basis of black-oil models without detailed analysis of the phase behavior of the reservoir-oil/injected-gas system. The reliability of using the blackoil model to simulate the cycling of gas/ condensate reservoirs is questionable because the two-component description may not be able to represent the active compositional phenomena adequately. This paper describes the use of an equation-of-state (EOS) approach to model the phase behavior of the oil and injected-solvent system. Description of Models The reservoir-fluid-composition data are from the published data of the fifth SPE comparative solution project, which aimed to illustrate the comparison of results between a four-component black-oil miscible-flood simulator and a fully compositional reservoir-simulation model. Minimum-Miscibility-Pressure (MMP) Determination Local displacement efficiency by gas or solvent injection is closely dependent on the MMP. Most gas- or solvent-injection cases operate in a regime in which true miscibility is not achieved; however, high recoveries still could be attained. The analytical method for MMP determination focused on finding the key crossover tie-lines for a dispersion- free displacement when one of the key tie lines becomes a critical-tie line (a tie-line of zero length). This paper shows the use of a cell-to-cell simulation method to determine the MMP of the given solvent composition and reservoir fluids. The pseudoternary diagram is generated from the calculations to study the vaporization or extraction process and interprets MMP as 3,440 psi. The multiple-contact miscibility occurs at approximately 3,400 psi, and a very small increase in recovery is observed at higher pressures. A slimtube simulation model also was developed that has good agreement with the MMP calculated by the tie-line method.

A 3D Total Variation Diminishing Scheme for Compositional Reservoir Simulation Using the Element-Based Finite-Volume Method

Interpolation function is a key parameter for numerical simulation using finite-difference, finite-element, and finite-volume methods, especially when the advective terms of the conservation equations are considered. Due to the flow orientation, a first-order interpolation scheme such as upwind introduces a considerable degree of numerical diffusion in the numerical solution. In this work, we present a second-order total variation diminishing scheme in conjunction with 3D compositional reservoir simulation using the element-based finite-volume method (EbFVM). The results of several case studies using the hexahedron element are shown in terms of oil, water, and gas production, as well as saturation field.

PVT modeling of reservoir fluids using PC-SAFT EoS and Soave-BWR EoS

Cubic equations of state, such as the Soave–Redlich–Kwong (SRK) and the Peng–Robinson (PR) EoS, are still the mostly used models in PVT modeling of reservoir fluids, and almost the exclusively used models in compositional reservoir simulations. Nevertheless, it is promising that recently developed non-cubic EoS models, such as the Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) EoS and the Soave modified Benedict–Webb–Rubin (Soave-BWR) EoS, may partly replace the roles of these classical cubic models in the upstream oil industry. Here, we attempt to make a comparative study of non-cubic models (PC-SAFT and Soave-BWR) and cubic models (SRK and PR) in several important aspects related to PVT modeling of reservoir fluids, including density description for typical pure components in reservoir fluids, description of binary VLE, prediction of multicomponent phase envelopes, and PVT calculation of reservoir fluids. Extensive data are used in the comparison and the four models are treated as equally as possible. We adopt the method of Pedersen et al. as the framework for heptanes plus characterization and the same correlations for estimating the critical properties for SRK, PR and Soave-BWR. For PC-SAFT, new correlations for estimating its model parameters in heptanes plus are developed. The results reveal that the non-cubic models are clearly advantageous in density calculation of pure components. For binary VLE and multicomponent phase envelopes, the results are similar for the four models. For PVT prediction, the non-cubic models show advantages in some high pressure high temperature (HPHT) fluids but no clear advantages in general, indicating the necessity for further improvement of the characterization procedure.