Data Driven Approach to Production / Injection Optimization in Oil & Gas field in Abu Dhabi

Production and Injection rate target optimization plays an important role in waterflooded field management in order to ensure hydrocarbon recovery. In line with ADNOC Digital transformation and waterflood excellence initiatives CRM and Optimization technology has been progressed to maximize opportunities in oil recovery increase. The optimization means that producing well delivers a maximum amount of oil with minimal water production along with maintaining proper Voidage Replacement Ratio (VRR) to support reservoir pressure. To reach such goal, the optimization procedure needs to run multiple rate scenarios to calculate the objective function value. The conventional way is to perform multiple runs on simulation model, which can be very time-consuming. The data driven approach described in this paper suggests faster and convenient methodology to solve this problem. The process applied to this approach consists of data preparation/ data cleansing stage, CRM (Capacitance Resistance Model) and optimization procedure based on the objective function with a penalty to imbalanced VRR at the pattern level. The CRM algorithm can calculate fraction of injection distributed from each injecting well to connected producing wells at any timestep. These calculated injection allocation factors are considered in the rate optimization procedure in order to define optimal injection and production rates along with balancing of VRR at the pattern level. The method also considers 3-phase flow across wells and reservoir intervals. The objective function calculates overall profit from oil production, costs for water and gas handling, and the penalty for the production injection difference at the producing well level. At the end, the output of this optimization process is to recommend production and injection rates targets for each well and short term forecast of the production based on fractional flow model. The data driven approach shows quite good efficiency in terms of time and efforts, the injection allocation factors based on CRM model are comparatively same as it is calculated in streamline simulation model but with better granularity at the pattern level. The optimization procedure works quite fast, and the results have shown decrease of water production rate and increase of recovery factor due to maintaining VRR close to the target level. The data driven approach described in the paper implements a new way to apply CRM in fields with waterflooding and gas injection with the enhancement of managing 3-phase flow. The in-house developed optimization function and its implementation is a novel approach in terms of practical application to the fields in Abu Dhabi area.