Method for predicating productivity of nonhomogeneity ancient karst carbonate reservoir

Abstract

The invention discloses a method for predicating productivity of nonhomogeneity ancient karst carbonate reservoir. The method includes the steps of firstly clarifying the reservoir through reservoir parameter processing and conducting the reservoir thickness statistics according to the clarified reservoir, secondly determining key parameters related to the productivity, such as matrix porosity, stoneley wave energy attenuation, the surface hole rate and the reservoir thickness, thirdly working out the comprehensive evaluation index RQ of reservoir quality according to the determined key parameters, establishing a productivity predicating model according to the comprehensive evaluation index RQ of the reservoir quality, and finally conducting productivity predication of the nonhomogeneity ancient karst carbonate reservoir according to the established productivity predicating model. By means of the method, the fine depicting and representing of the nonhomogeneity ancient karst reservoir are achieved, the problem of permeability of the nonhomogeneity ancient karst reservoir is solved, the main control factor problem of the productivity of the nonhomogeneity ancient karst reservoir is solved, and quantitative calculation of the main control factor is achieved, so that accurate productivity prediction can be achieved.

Description

technical field

[0001] The invention relates to a method for predicting the productivity of a heterogeneous paleokarst carbonate reservoir, belonging to the technical field of geological exploration. Background technique

[0002] The Sinian Dengying Formation and Cambrian Longwangmiao Formation in the Central Sichuan Basin are the oldest oil and gas exploration strata. The reservoirs have multi-phase dissolution, multi-media, complex pore structure, karst development, strong siliceous filling and heterogeneous filling. The overlapping characteristics of homogeneous and quasi-homogeneous reservoirs result in a complex void space structure, and its productivity evaluation is even more difficult.

[0003] Usually, the porosity, permeability and oil and gas saturation of the reservoir are calculated by conventional logging data, and the reservoir is evaluated and the productivity is predicted by means of the neural network method. When the size and distribution of pores or diss...