Deep compact sandstone reservoir evaluation method based on artificial intelligence reservoir diagenesis phase recognition

Abstract

The invention discloses a deep compact sandstone favorable reservoir evaluation method based on artificial intelligence reservoir diagenesis phase recognition. According to the method, end members of a QFL chart are modified, a new sandstone classification chart is established to divide the rock types of sandstone, all the rock types correspond to the lithogenous facies, a lithogenous facies division method based on the rock types is established, logging information of a coring well in a research area is utilized, logging response characteristics of all the lithogenous facies are obtained, a BP neural network is trained by using the well logging information of the determined rock facies to identify the lithogenous facies type of each well in the research area, the transverse distribution rule of the lithogenous facies in the deep compact sandstone reservoir is analyzed, the reservoir comprehensive evaluation index at each drilling well point in the reservoir is calculated, a reservoir comprehensive evaluation index plane distribution diagram is drawn, and a favorable area of the deep compact sandstone reservoir is predicted. According to the method, full-well-section system evaluation of the deep compact sandstone reservoir is achieved, the favorable area in the reservoir can be accurately predicted, and a foundation is laid for exploration and development of deep oil and gas.

Description

technical field [0001] The invention relates to the field of oil and gas field development geology, in particular to an evaluation method for deep tight sandstone reservoirs based on artificial intelligence to identify reservoir diagenetic facies. Background technique [0002] In the past ten years, deep oil and gas resources have become the main growth of global proven reserves. From 2008 to 2018, the world's new proven oil and gas reserves in formations deeper than 4000m were 23.4 billion tons of oil equivalent, exceeding 60% of the global new oil and gas reserves in the same period. The results of my country's fourth oil and gas resource evaluation (2017) show that China's deep and ultra-deep oil accounts for 20% of the total oil resources, and natural gas accounts for 49% of the total natural gas resources. Deep and ultra-deep reservoirs are characterized by low porosity (average porosity less than 10%), low permeability (average permeability less than 1mD), well-develop...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the problem of difficult evaluation of deep tight sandstone reservoirs, the present invention provides an evaluation method for deep tight sandstone reservoirs based on artificial intelligence to identify reservoir diagenetic facies

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