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New Method for Predicting Production Boosts Accuracy for Carbonate Reservoirs

The widely developed karst caves and fractures in carbonate reservoirs result in strong spatial heterogeneity. Consequently, the parameters obtained from cores and numerical simulation are limited in their ability to reflect the production possibility of the entire reservoir. To solve this problem, this paper proposes a new method of economic prediction on the basis of expert library and oilfield databases. The method takes into account geological factors and the effect of production factors on the economic prediction.

Introduction

The key parameters used for the economic prediction of a carbonate reservoir include well spacing, oil production, and annual decline rate. These parameters are mainly from core experiments in the laboratory or from the numerical simulation of wells, but caves and fractures are dispersed throughout the carbonate reservoir. This heterogeneity means the properties of a carbonate reservoir can be very different in different regions. Consequently, the commonly used parameters are limited in their ability to represent the whole reservoir, which leads to high risk in economic prediction.

The method proposed in this paper combines the Delphi method, the analytic hierarchy process (AHP), the technique for order preference by similarity to ideal solution (TOPSIS), the moving least-squares (MLS) method, and future net present value (FNPV) to create the DATMF method in an attempt to overcome these shortcomings. Through classical mathematics methods, the DATMF method combines expert library and oilfield databases to predict the economy of carbonate reservoirs. This prediction method reduces the size of the required database greatly, and its calculation process is based on professional geology theory and reservoir engineering. In addition, the DATMF economic prediction method can be applied directly to the stage of geological exploration, which removes the barrier between geologists and reservoir engineers and simplifies the procedure of economic prediction.

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 190868, “A New Method for Economic Prediction of Carbonate Reservoirs Based on Expert Library and Small Database,” by Wenbin Chen, SPE, Hanqiao Jiang, and Junjian Li, China University of Petroleum; Shan Jiang, PetroChina; and Hanxu Yang, SPE, and Yan Qiao, China University of Petroleum, prepared for the 2018 EAGE Annual Conference and Exhibition/SPE Europec, Copenhagen, Denmark, 11–14 June. The paper has not been peer reviewed.
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New Method for Predicting Production Boosts Accuracy for Carbonate Reservoirs

01 October 2018

Volume: 70 | Issue: 10

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