Improving Polymerflood Performance Via Streamline-Based Rate Optimization: Mangala Field, India

Abstract

This paper describes a novel streamline-based rate allocation approach to maximize oil recovery from polymerfloods and its application to an ongoing polymerflood in the Mangala field, India which is one of the largest polymerfloods in the world. With over 130 injectors and producers, the field-scale optimization is challenging because of the long simulation times, operational constraints at the well, group and field level and changing field conditions. The FM-1 unit which is the main producing zone of the Mangala field comprises of multi-layered single storied fluvial channel sands of thickness ranging 3-10m with excellent flow characteristics. The gross thickness of FM-1 is about 90m. The sand is under a five-spot pattern polymerflood with a well spacing of aproximately 200m. A finite difference simulator is used for modeling the polymerflood performance with all relevant physics (mobility control, adsorption, residual resistance factor, polymer rheology/shear thinning, inaccessible pore volume and time-dependent degradation). Streamlines are generated from the flux field extracted from the finite difference simulation and are used to calculate pair-wise efficiency for each injector-producer streamline bundle. The pair-wise efficiency quantifies how much oil is recovered given a barrel of water injection. The streamline-based optimizer iteratively reallocates the fluids to injectors and producers by diverting the injected fluid to high efficiency pairs located in unswept oil regions. After optimization, injection efficiency plots as well as streamline/time of flight plots are used to examine and visualize the flow pattern changes leading to the improved flood performance. The reservoir model is first calibrated with 10 years of waterflood history. The polymer injection concentration and tapering schemes are determined based on extensive laboratory experiments. The optimization focuses on reallocating the well rates while maintaining the well, group and field level constraints. Two optimization scenarios were studied to examine the potential benefits of rate allocation: (1) optimization of rate allocation for both injectors and producers, (2) optimization of rate allocation for injectors only. Both the scenarios yield improved oil recovery (~5 MMSTB), accelerated production and reduced polymer usage (utility factor). The streamline and injection efficiency plots clearly reveal regions of improved sweep efficiencies, providing an intuitive explanation of the enhanced performance.

Compositional Streamline-Based Modeling of Polymer Flooding Including Rheology, Retention, and Salinity Variation

“…A publication by Choudhuri et al 59 presented a full field SL simulation model of a large polymer flooding project in the Sultanate of Oman to facilitate the reservoir management decision-making and optimization of the polymer flood strategy. Chen et al 60 used a heuristic method with a SL-based rate allocation approach to maximize oil recovery in an ongoing polymer flood in the Mangala field in India; they applied a SL flow diagnostic for rate allocation and optimization of the polymer flood at field-scale and also developed a framework to incorporate dynamic field development schemes and operational constraints. Later, Li et al 61 introduced an application of SL-based polymer flooding injection optimization for the Mangala field, in which a systematic rate optimization workflow designed for practical field implementations was applied.…”