Coupling of Rigorous Multiphase Flash with Advanced Linearization Schemes for Accurate Compositional Simulation

The properties of fluids flowing in a petroleum reservoir are quantified by understanding the thermodynamic behavior of each flowing phase in the system. This work describes proper techniques to formulate and execute a thermodynamic model for accurately predicting the equilibrium behavior of oil-gas-brine systems within the practical range of pressure and temperature. The three-phase flash algorithm is validated against published data from the available literature. The multiphase flash procedure is implemented to generate linearized physical properties by using an Operator Based Linearization (OBL) modelling technique allowing for a combination of multiple complex physics in the nonlinear solution of governing equations. This is the first implementation of three-phase flash calculations for hydrocarbons and brines based on fugacity-activity models coupled with an advanced highly efficient linearization scheme. Our approach increases the efficiency and flexibility of the modelling process of physical phenomena such as fluid flow in porous subsurface reservoirs.

A GPU-Based, Industrial Grade Compositional Reservoir Simulator

Recently, graphics processing units (GPUs) have been demonstrated to provide a significant performance benefit for black-oil reservoir simulation, as well as flash calculations that serve an important role in compositional simulation. A comprehensive approach to compositional simulation based on GPUs had yet to emerge, and some questions remained as to whether the benefits observed in black-oil simulation would persist with a more complex fluid description. We present our positive answer to this question through the extension of a commercial GPU-based black-oil simulator to include a compositional description based on standard cubic equations of state. We describe the motivations for the formulation we select to make optimal use of GPU characteristics, including choice of primary variables and iteration scheme. We then describe performance results on an example sector model and simplified synthetic case designed to allow a detailed examination of scaling with respect to the number of hydrocarbon components and model size, as well as number of processors. We finally show results from two complex asset models (synthetic and real) and examine performance scaling with respect to GPU generation, demonstrating that performance correlates strongly with GPU memory bandwidth.

Comparative Evaluation of Gas-Condensate Enhanced Recovery Methods for Deep Ukrainian Reservoirs: Synthetic Case Study

Low value of final condensate recoveries achieved under natural depletion require implementation of enhanced gas recovery (EGR) methods to be implemented for the efficient development of gas-condensate reservoirs. The study was performed using synthetic numerical 9-component compositional simulation model that approximated the typical conditions of deep gas-condensate reservoirs of Dnieper-Donetsk Basin in Easter Ukraine. Injection of water, methane, nitrogen, carbon dioxide, mixture of methane and nitrogen, mixture of methane, ethane and propane at different concentrations were evaluated at 50% and 100% voidage replacement for reservoir fluids with 100 g/m3, 300 g/m3 and 500g/m3 potential condensate yield. Condensate recovery studied at different stages after primary depletion, when reservoir pressure reached 25, 50, 75% from dew point and at pressure of maximum liquid dropout. Results comparison was done based on the two criteria: technical efficiency – incremental condensate recovery towards the base depletion cases and economic efficiency – cumulative NPV. Status of initial depletion as well as voidage replacement have a direct impact on breakthrough time and negative economic indicators. Despite providing the highest incremental condensate recovery by injecting CO2 at 100% voidage, it has a strong negative economic effect. Based on incremental condensate recovery EGR methods are ranked as following for all condensate potential yields and levels of primary depletion: CO2 100%; solvent gas mixture of C1 90%, C2 5%, C3 5%; solvent gas mixture C1 98%, C2 1%, C3 1%; C1 100%; mixture of C1 50% and N2 50%; N2 100%; water. Economically, the highest efficiency was shown for C1 100% injection, due to the fact, that produced re-cycled gas has a sales value as well. For the maximum incremental recovery it is advisable to start the injection as early as possible, while highest economic increments received for the cases of delayed injection, particularly when the reservoir pressure is equal to the pressure of maximum liquid condensation. The results of study can be used a guidance for rapid screening of applicable EGR method for gas-condensate fields depending on depletion stage and potential condensate yield.

A Graphics Processing Unit–Based, Industrial Grade Compositional Reservoir Simulator

Summary Recently, graphics processing units (GPUs) have been demonstrated to provide a significant performance benefit for black-oil reservoir simulation, as well as flash calculations that serve an important role in compositional simulation. A comprehensive approach to compositional simulation based on GPUs has yet to emerge, and the question remains as to whether the benefits observed in black-oil simulation persist with a more complex fluid description. We present a positive answer to this question through the extension of a commercial GPU-basedblack-oil simulator to include a compositional description based on standard cubic equations of state (EOSs). We describe the motivations for the selected nonlinear formulation, including the choice of primary variables and iteration scheme, and support for both fully implicit methods (FIMs) and adaptive implicit methods (AIMs). We then present performance results on an example sector model and simplified synthetic case designed to allow a detailed examination of runtime and memory scaling with respect to the number of hydrocarbon components and model size, as well as the number of processors. We finally show results from two complex asset models (synthetic and real) and examine performance scaling with respect to GPU generation, demonstrating that performance correlates strongly with GPU memory bandwidth. NOTE: This paper is published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.

The Role of CO2 in Carbonate Acidizing at the Field Scale – A Multi-Phase Perspective

Most lab-scale acidizing experiments are performed in core samples with 100% water saturation conditions and at pore pressures around 1100 psi. However, this is seldom the case on the field, where different saturation conditions exist with high temperature and pressure conditions. Carbon-di-Oxide (CO2), a by-product evolved during the acidizing process, is long thought to behave inertly during the acidizing process. Recent investigations reveal that the presence of CO2 dynamically changes the behavior of wormhole patterns and acid efficiency. A compositional simulation technique was adopted to understand the process thoroughly. A validated compositional numerical model capable of replicating acidizing experiments at the core-scale level, in fully aqueous environments described in published literature was utilized in this study. The numerical model was extended to a three-phase environment and applied at the field scale level to monitor and evaluate the impacts of evolved CO2 during the carbonate acidizing processes. Lessons learned from the lab-scale were tested at the field-scale scenario via a numerical model with radial coordinates. Contrary to popular belief, high pore pressures of 1,000 psi and above are not sufficient to keep all the evolved CO2 in solution. The presence of CO2 as a separate phase hinders acid efficiency. The reach or extent of the evolved CO2 is shown to exist only near the damage zone and seldom penetrates the reservoir matrix. Based on the field scale model's predictions, this study warrants conducting acidizing experiments at the laboratory level, at precisely similar pressure, temperature, and salinity conditions faced in the near-wellbore region, and urges the application of compositional modeling techniques to account for CO2 evolution, while studying and predicting matrix acidizing jobs.

Compositional Modeling of Impure CO2 Injection for Enhanced Oil Recovery and CO2 Storage

Injecting CO2, a greenhouse gas, into the reservoir could be beneficial economically, by extracting remaining oil, and environmentally, by storing CO2 in the reservoir. CO2 captured from various sources always contains various impurities that affect the gas–oil system in the reservoir, changing oil productivity and CO2 geological storage performance. Therefore, it is necessary to examine the effect of impurities on both enhanced oil recovery (EOR) and carbon capture and storage (CCS) performance. For Canada Weyburn W3 fluid, a 2D compositional simulation of water-alternating-gas (WAG) injection was conducted to analyze the effect of impure CO2 on EOR and CCS performance. Most components in the CO2 stream such as CH4, H2, N2, O2, and Ar can unfavorably increase the MMP between the oil and gas mixture, while H2S decreased the MMP. MMP changed according to the type and concentration of impurity in the CO2 stream. Impurities in the CO2 stream also decreased both sweep efficiency and displacement efficiency, increased the IFT between gas and reservoir fluid, and hindered oil density reduction. The viscous gravity number increased by 59.6%, resulting in a decrease in vertical sweep efficiency. In the case of carbon storage, impurities decreased the performance of residual trapping by 4.1% and solubility trapping by 5.6% compared with pure CO2 WAG. As a result, impurities in CO2 reduced oil recovery by 9.2% and total CCS performance by 4.3%.

Comparison of Different Gases Injection Techniques for Better Oil Productivity

There are many known enhanced oil recovery (EOR) methods and every method has its criteria to use it. Some of those methods are gas injection such as CO2 injection, N2 and hydrocarbon gas injection. Where the CO2 has been the largest contributor to global EOR. Gas injection can be classified into two main types; continues gas injection (CGI) and water alternating gas injection (WAG). The objective of this research is to propose initial gases injection plan of the X field to maximize the total oil recovery. The feasibility study of different gases to maintain pressure and optimize oil recovery have been examined on a simple mechanistic reservoir model of considerably depleted saturated oil reservoir. In order to maximize the total oil recovery, the simulation study was conducted on 3-phase compositional simulation model. For more optimization, a sensitivity study was conducted on the injection cycling and component ratios. A sensitivity study was also conducted on the following parameters to study their effects on the overall field’s recovery such as flow rate and bottom-hole pressure. Results obtained in this paper shows that, the WAG CO2 injection was found to be significantly more efficient than different gas injection and continues gas injection. The oil recovery depends not only on the fluid-to-fluid displacement but also on the compositional phase behavior.