Low Salinity Water Injection Optimization in the Namorado Field Using Compositional Simulation and Artificial Intelligence

Abstract

Abstract This work aims to optimize the development plan involving Low Salinity Water Injection – LSWI for the Namorado Field (located in the Campos basin in Brazil). Multiple mechanisms have been proposed in the literature to represent LSWI, mechanisms that we are going to discuss in this paper. Additionally, it will be studied the impact to evaluate multiple geostatistical realizations at the same time with multiple development scenarios (Robust Optimization) to select the optimal Net Present Value (NPV) of the project considering the reservoir uncertainties. This methodology combines compositional simulation and a mathematical optimization tool that uses artificial intelligence to maximize the NPV of the project under evaluation. Considering that LSWI alters the initial chemical equilibrium in the reservoir and induces changes in the system, a geochemical model is included with aqueous reactions, dissolution / precipitation mineral reaction and ion exchange. The optimization project was carried out in three stages, first a multiple assisted history match, followed by a probabilistic forecast and finally, a robust optimization. As a result, an optimum operational strategy of LSWI was obtained in which the impact of changing the type, location and number of producer and injector wells as well as the volume of injected water (High Salinity Water Injection (HSWI) vs. LSWI) are considered. On average, the optimal scenario for LSWI obtained a recovery factor of 41%, compared to 34% if only conventional water is injected. The selection and optimization of the recovery strategy considered multiple geological realizations and multiple history matched models in the field development plan, this considers the uncertainty associated with the porosity, permeability and net to gross distribution, with the objective of increasing the accuracy and reliability of the results obtained for the recovery factor and the NPV. For the optimal LSWI case and considering five different selected geological scenarios (P10 to P90), the recovery factor obtained was between 37.89% (P10) and 42.21% (P90) and the project NPV between 807 MMUSD (P10) and 3315 MMUSD (P90). This adapted methodology allowed to obtain the optimal development plan considering the uncertainty associated in the reservoir, using multiple geostatistical realizations and multiple history matched models at the same time (usually just one history match is considered).