A Method to Correlate Interactions Between Injectors and Producers

Abstract

Abstract In reservoirs management, sometimes it becomes difficult to identify which injector is supporting which producer(s) by graphs visual inspection. Available built-in correlations like Pearson –within common spreadsheets-, only valid for strictly monotonic (only increasing or decreasing) trends. A situation that is nearly impossible to see in real production/ injection trends. To resolve this issue, we developed a correlative tool in spreadsheet based on Spearman's correlation to assess communication degree between wells using production/ injection data. The method essentially implemented then non-parametric Spearman's correlation - valid with non-monotonic trends- and used visual basic application (VBA) coding language to provide easy to use worksheet. The input data needed are: production/injection data of the well(s), with any desired parameter like oil rate, water rate, GOR or water cut. After running the code, the outputs are numbers between −1 and 1 reflecting correlation coefficients between WI-OPs production parameters or OP-OP parameters. Zero or close to zero means no correlation, number close to 1 mean very strong proportional correlation and a number close to −1 reflects inversely proportional correlation. The tool was built successfully and enabled quick injection/production correlation between one injector and several producers at once using available production data. Also, it can run production/injection correlations between one producer and several injectors. Currently, it can measures correlation between one injector with up to 32 producers, or with 32 different parameters of several producers like water cut, gas oil ratio (GOR), oil rate, water injection rate, and water production rate. Moreover, it can correlate between producer-producer to check for interference. The code was found to be fast. Results from this tool were compared to results obtained from streamlines models and tracer injection in two different fields, one was naturally fractured carbonate and the other was sandstone. Evaluation of the tool ability to find true interactions between wells was achieved by comparing results of correlations coefficient with underground flowing tracers and streamline simulations. Some agreement was found between, streamline models, tracer surveys and Spearman correlation in well known areas to have well-well communication. Some limitiations were identified. Nevertheless, the tool can be used as a quick scanning tool for communication between wells. This tool provides an addition to the inventory of existing investigative methods like tracers, streamlines, and diagnostic plots and gives more weight to results from these techniques on identifying which wells in communication. The tool is easy to build, simple to use and fast to run. The tool might help reservoir management teams to better manage reservoirs, and free more time for engineers to improve production and increase oil gain.