INTERWELL CONNECTIVITY PREDICTION PROGRAM USING CAPACITANCE RESISTANCE MODEL (CRM) ON WATERFLOODED RESERVOIR

Abstract

This thesis present implementation of Capacitance Resistance Model in a python code environment. The objective of the research is to estimate interwell connectivity (𝑓) parameter and visualize connectivity parameter through a vector map. The connectivity parameter may be used to identify which injector is influencing certain producer. The acquired data may also be used as underlying logic to formulate an injection program and enhance injection efficiency.

Capacitance resistance model (CRM) is a simplified reservoir model that characterized flooded reservoir by the estimating interwell connectivity, time constants and productivity indexes. In CRM, several schemes are categorized: CRMT (single tank representation), CRMP (producer-based representation), and CRMIP (Injector-producer pair-based representation). Through history matching, connectivity and other parameter will be calibrated to appropriately represent the waterflooded reservoir.

In the research, model adaptation was done by transforming the structure of Capacitance Resistance Model’s Ordinary Differential Equation into State-Space Equation. The data used during the development are synthetic data and field data. The output of this research is the programming algorithm and parameter visualization of interwell connectivity in a vector map.