Methodology for the Development of Laboratory-Based Comprehensive Foam Model for Use in the Reservoir Simulation of Enhanced Oil Recovery

2018 ◽  
Vol 21 (02) ◽  
pp. 344-363 ◽  
Author(s):  
Maghsood Abbaszadeh ◽  
Abdoljalil Varavei ◽  
Fernando Rodriguez-de la Garza ◽  
Antonio Enrique Villavicencio ◽  
Jose Lopez Salinas ◽  
...  
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Reservoir Simulation ◽  
Foam Model

scholarly journals Quantitative Modeling of the Effect of Oil on Foam for Enhanced Oil Recovery

SPE Journal ◽  
2019 ◽  
Vol 24 (03) ◽  
pp. 1057-1075 ◽  
Author(s):  
Jinyu Tang ◽  
Mohammed N. Ansari ◽  
William R. Rossen
Keyword(s):  
Steady State ◽  
Pressure Gradient ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Flow Regimes ◽  
Multiple Steady States ◽  
High Quality ◽  
Foam Model ◽  
Model Oil ◽  
Dry Out

Summary The effectiveness of foam for mobility control in the presence of oil is key to foam enhanced oil recovery (EOR). A fundamental property of foam EOR is the existence of two steady-state flow regimes: the high-quality regime and the low-quality regime. Experimental studies have sought to understand the effect of oil on foam through its effect on these two regimes. Here, we explore the effect of oil on the two flow regimes for one widely used foam model. The STARS (CMG 2015) foam model includes two algorithms for the effect of oil on foam: In the “wet-foam” model, oil changes the mobility of full-strength foam in the low-quality regime, and in the “dry-out” model, oil alters the limiting water saturation around which foam collapses. We examine their effects as represented in each model on the two flow regimes using a Corey relative permeability function for oil. Specifically, we plot the pressure-gradient contours that define the two flow regimes as a function of superficial velocities of water, gas, and oil, and show how oil shifts behavior in the regimes. The wet-foam model shifts behavior in the low-quality regime with no direct effect on the high-quality regime. The dry-out model shifts behavior in the high-quality regime but not the low-quality regime. At fixed superficial velocities, both models predict multiple steady states at some injection conditions. We perform a stability analysis of these states using a simple 1D simulator with and without incorporating capillary diffusion. The steady state attained after injection depends on the initial state. In some cases, it appears that the steady state at the intermediate pressure gradient is inherently unstable, as represented in the model. In some cases, the introduction of capillary diffusion is required to attain a uniform steady state in the medium. The existence of multiple steady states, with the intermediate one being unstable, is reminiscent of catastrophe theory and of studies of foam generation without oil.

scholarly journals Simulation of Foam Enhanced-Oil-Recovery Processes Using Operator-Based Linearization Approach

SPE Journal ◽  
2021 ◽  
pp. 1-18
Author(s):  
Xiaocong Lyu ◽  
Denis Voskov ◽  
Jinyu Tang ◽  
William R. Rossen
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Uniform Mesh ◽  
Computational Performance ◽  
Foam Model ◽  
State Dependent ◽  
Highly Nonlinear ◽  
Simulation Results

Summary Foam injection is a promising enhanced-oil-recovery (EOR) technology that significantly improves the sweep efficiency of gas injection. Simulation of foam/oil displacement in reservoirs is an expensive process for conventional simulation because of the strongly nonlinear physics, such as multiphase flow and transport with oil/foam interactions. In this work, an operator-based linearization (OBL) approach, combined with the representation of foam by an implicit-texture (IT) model with two flow regimes, is extended for the simulation of the foam EOR process. The OBL approach improves the efficiency of the highly nonlinear foam-simulation problem by transforming the discretized nonlinear conservation equations into a quasilinear form using state-dependent operators. The state-dependent operators are approximated by discrete representation on a uniform mesh in parameter space. The numerical-simulation results are validated by using three-phasefractional-flow theory for foam/oil flow. Starting with an initial guess depending on the fitting of steady-state experimental data with oil, the OBL foam model is regressed to experimental observations using a gradient-optimization technique. A series of numerical validation studies is performed to investigate the accuracy of the proposed approach. The numerical model shows good agreement with analytical solutions at different conditions and with different foam parameters. With finer grids, the resolution of the simulation is better, but at the cost of more expensive computations. The foam-quality scan is accurately fitted to steady-state experimental data, except in the low-quality regime. In this regime, the used IT foam model cannot capture the upward-tilting pressure gradient (or apparent viscosity) contours. 1D and 3D simulation results clearly demonstrate two stages of foam propagation from inlet to outlet, as seen in the computed-tomography (CT) coreflood experiments: weak foam displaces most of the oil, followed by a propagation of stronger foam at lower oil saturation. OBL is a direct method to reduce nonlinearity in complex physical problems, which can significantly improve computational performance. Taking its accuracy and efficiency into account, the data-drivenOBL-based approach could serve as a platform for efficient numerical upscaling to field-scaleapplications.

scholarly journals Scaleup of Laboratory Data for Surfactant-Alternating-Gas Foam Enhanced Oil Recovery

SPE Journal ◽  
2020 ◽  
Vol 25 (04) ◽  
pp. 1857-1870
Author(s):  
Rodrigo O. Salazar-Castillo ◽  
William R. Rossen
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Water Saturation ◽  
Gas Injection ◽  
Laboratory Data ◽  
Mobility Control ◽  
Model Parameters ◽  
Fractional Flow ◽  
Foam Model ◽  
Irreducible Water Saturation

Summary Foam increases sweep efficiency during gas injection in enhanced oil recovery processes. Surfactant alternating gas (SAG) is the preferred method to inject foam for both operational and injectivity reasons. Dynamic SAG corefloods are unreliable for direct scaleup to the field because of core-scale artifacts. In this study, we report fit and scaleup local-equilibrium (LE) data at very-low injected-liquid fractions in a Bentheimer core for different surfactant concentrations and total superficial velocities. We fit LE data to an implicit-texture foam model for scaleup to a dynamic foam process on the field scale using fractional-flow theory. We apply different parameter-fitting methods (least-squares fit to entire foam-quality scan and the method of Rossen and Boeije 2015) and compare their fits to data and predictions for scaleup. We also test the implications of complete foam collapse at irreducible water saturation for injectivity. Each set of data predicts a shock front with sufficient mobility control at the leading edge of the foam bank. Mobility control improves with increasing surfactant concentration. In every case, scaleup injectivity is much better than with coinjection of gas and liquid. The results also illustrate how the foam model without the constraint of foam collapse at irreducible water saturation (Namdar Zanganeh et al. 2014) can greatly underestimate injectivity for strong foams. For the first time, we examine how the method of fitting the parameters to coreflood data affects the resulting scaleup to field behavior. The method of Rossen and Boeije (2015) does not give a unique parameter fit, but the predicted mobility at the foam front is roughly the same in all cases. However, predicted injectivity does vary somewhat among the parameter fits. Gas injection in a SAG process depends especially on behavior at low injected-water fraction and whether foam collapses at the irreducible water saturation, which may not be apparent from a conventional scan of foam mobility as a function of gas fraction in the injected foam. In two of the five cases examined, this method of fitting the whole scan gives a poor fit for the shock in gas injection in SAG. We also test the sensitivity of the scaleup to the relative permeability krw(Sw) function assumed in the fit to data. There are many issues involved in scaleup of laboratory data to field performance: reservoir heterogeneity, gravity, interactions between foam and oil, and so on. This study addresses the best way to fit model parameters without oil for a given permeability, an essential first step in scaleup before considering these additional complications.

A Laboratory Experimental and Reservoir Simulation Estimation on Minimum Miscible Pressure (MMP) for CO2 Injection in HIL Oil Field

2020 ◽  
Author(s):  
H. Hilal
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Reservoir Simulation ◽  
Energy Demand ◽  
Promising Result ◽  
Oil Field ◽  
Co2 Injection ◽  
Co2 Gas ◽  
Secondary Recovery ◽  
Simulation Estimation

As one of the Enhanced Oil Recovery (EOR) methods, CO2 injection is one of the methods used after secondary recovery to increase oil recovery. Based on the successful application of CO2 injection in some countries and the need of fulfillment of energy demand in Indonesia, CO2 injection can be the best method to be used for EOR. This method injects CO2 that has been observed in the laboratory through injection well to reservoir. In the reservoir, CO2 gas will be miscible with oil to decrease oil’s viscosity. But, to be miscible with oil and to avoid the reservoir problem, the Minimum Miscible Pressure (MMP) must be observed in the laboratory. Moreover, a reservoir simulation investigation must be performed to get a promising result. In this paper, the laboratory experimental and reservoir simulation on MMP to achieve CO2 gas miscibility on oil sample from HIL oil field has been performed. The MMP result from the laboratory experiment is 2385 psia and is increasing oil recovery up to 85% while the MMP from reservoir simulation is 2404 psia. With the differential value of just 19 psia or error of 0. 89%, this finding can be the basis for a recommendation to develop a CO2 project in the HIL oil field.

Accurate Modeling of Polymer Enhanced Oil Recovery Corefloods by Reservoir Simulation

2015 ◽  
Author(s):  
Shi Su ◽  
Marie Ann Giddins ◽  
Paul Naccache ◽  
Andrew Clarke ◽  
Andrew M Howe
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Reservoir Simulation
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