The Numerical Simulation Study of the Oil–Water Seepage Behavior Dependent on the Polymer Concentration in Polymer Flooding

This paper presents a 2D model of the Ghawar field and investigates the flow behavior in the field during secondary and tertiary recoveries using a simplified well scheme. For the latter, the focus is on chemical Enhanced Oil Recovery (EOR), using polymer solutions. The difference in efficiency between secondary and tertiary recovery and the influence of factors such as degradation are analyzed and presented. Furthermore, the influence of oil viscosity on the recovery factor is investigated as well as the efficiency of the well placement of the model studied. In order to do this, a combined shear-thinning/-thickening model, the Unified Viscosity Model (UVM), is used. COMSOL Multiphysics is used in order to study the model, combining the fluid flow and mass transfer in one study, showing the interdependence of both physics transport phenomena. The results show how the influence of the polymer properties and the rock formation affect the recovery behavior. The particle tracing study allows us to determine the percentage of the chemical agent recovered in the producing wells. This paper shows how EOR agents works coupled with advanced numerical models in real-scale fields.

Section: Modified Polymer Floodingsupporting

confidence: 63%

Simulation of Polymer Chemical Enhanced Oil Recovery in Ghawar Field

Berger¹,

Picchioni²,

Druetta³

2022

“…However, a differential calculation is involved in the J.B.N. method [29], which is difficult in practical operation, especially in the displacement process of amphiphilicpolymer flooding [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. There are two main reasons: (1) the produced liquid usually has an emulsification effect, and measurement errors for oil and water occur easily.…”

Section: Introductionmentioning

confidence: 99%

Iso-Permeability Point Trail Method to Determine the Relative Permeability Curve for a New Amphiphilic Polymer Flooding

Wang,

Ju,

Jin

et al. 2023

Amphiphilic-polymer flooding, which can increase water viscosity, decrease oil viscosity, and improve oil displacement efficiency, is a promising oil exploitation method for heavy oil. Due to oil–water emulsification, shear-thinning, and changes in oil viscosity when determining the relative permeability data of new amphiphilic polymers, the conventional J.B.N. method is not accurate. This paper presents a new method called the iso-permeability point trial method to determine the relative permeability curve by combining the J.B.N. method, the Corey model, and the relationship between water saturation and the relative permeability ratio. To avoid using polymer viscosity, a mathematical equation was derived based on the characteristics of the relative permeability curve. The results indicate that the new method is feasible and the obtained curve is more reasonable and smooth. The influence of concentration, permeability, and oil viscosity on amphiphilic-polymer displacement relative permeability was also analyzed, demonstrating that under the same water saturation, the water relative permeability is lower than that of water flooding but the oil relative permeability is bigger, which manifests as the iso-permeability point moves to the right and results in a lower residual oil saturation. In addition, the aforementioned trends are more obvious when the amphiphilic-polymer concentration is high, formation permeability is low, and oil viscosity is low.

A Prediction Method for Development Indexes of Waterflooding Reservoirs Based on Modified Capacitance–Resistance Models

Zhao

Chen

et al. 2022

Capacitance–resistance models (CRMs) are semi-analytical methods to estimate the production rate of either an individual producer or a group of producers based on historical observed production and injection rates using material balance and signal correlations between injectors and producers. Waterflood performance methods are applied to evaluate the waterflooding performance effect and to forecast the development index on the basis of Buckley–Leverett displacement theory and oil–water permeability curve. In this case study, we propose an approach that combines a capacitance–resistance model (CRM) modified by increasing the influence radius on the constraints and a waterflood performance equation between oil cut and oil accumulative production to improve liquid and oil production prediction ability. By applying the method, we can understand the waterflood performance, inter-well connectivities between injectors and producer, and production rate fluctuation better, in order to re-just the water injection and optimize the producers’ working parameters to maximize gain from the reservoir. The new approach provides an effective way to estimate the conductivities between wells and production rates of a single well or well groups in CRMs. The application results in Kalamkas oilfield show that the estimated data can be in good agreement with the actual observation data with small fitting errors, indicating a good development index forecasting capability.