Abstract

This paper presents a new procedure to determine inter-well connectivity in a reservoir based on fluctuations of bottomhole pressure of both injectors and producers in a waterflood. The method utilizes a constrained multivariate linear regression analysis to obtain information about permeability trends, channels and barriers.

Previous authors applied the same analysis to injection and production rates to infer connectivity between wells. However, in order to obtain good results, they applied various diffusivity filters to the flow rate data to account for the time lags and the attenuation. This was a tedious process that requires subjective judgment. Shut-in periods in the data, which were usually unavoidable when a large number of data points were used, created significant errors in the results and were often eliminated from the analysis.

This new method yielded better results compared to the results obtained when production data were used. Its advantages include: (1) No diffusivity filters needed for the analysis; (2) Minimal numbers of data points required to obtain good results; and (3) Flexible plan to collect data as all constraints can be controlled at the surface. The new procedure was tested using a numerical reservoir simulator. Thus, different cases were run on two fields, one with five injectors and four producers and the other with 25 injectors and 16 producers.

For a large waterflood system, multiple wells are present and most of them are active at the same time. In this case, pulse test or interference test between two wells are difficult to conduct since the signal can be distorted by other active wells in the reservoir. In the proposed method, interwell connectivity can be obtained quantitatively from multi-well pressure fluctuations without running interference tests.

Introduction

Well testing is a common and important tool of reservoir characterization. Many well testing methods have been developed in order to obtain different reservoir properties. Interference test and pulse test are used to quantify communication between wells. These methods are often applied to two wells as one well sending the signals (by changing flow rates) and the other receiving them1. However, for a large field such as a waterflood system, multiple wells are present and most of them are active at the same time. In this case, pulse test or interference test between two wells are difficult to conduct since the signal can be distorted by other active wells in the reservoir. In this method, data can be obtained from multi-well pressure test that resemble interference test. Thus, we can have several wells sending signals and the others receiving the signals at the same time. However, the wells that are receiving the signal can either be shut-in or kept at constant producing rates. The pressures at all wells are recorded simultaneously within a constant time interval. The length of the test will depend on the length of the time interval and the number of data points. Results of this method can be used to optimize operations and economics and enhance oil recovery of existing waterfloods by changing well patterns, changing injection rates, recompletion of wells, and in-fill drilling.

This work is based on previous work conducted by Albertoni and Lake2 using injection and production rates. In their work, Albertoni and Lake developed and tested different approaches using constrained multivariate linear regression analysis with a numerical simulator and then applied to a waterflooded field in Argentina. They used diffusivity filters to account for the time lag and attenuation of the data. In his thesis, Anh Dinh3 verified the method using different reservoir simulator and applied to a waterflood field in Nowata, Oklahoma. He also investigated the effect of shut-in periods and vertical distances on the results.

The main objectives of this work are to verify the results obtained from pressure data with results from flow rate data, to propose a new method to determine interwell connectivity and to suggest further research and study on the method.

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