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Intelligent interpretation and evaluation method for logging oil-gas-water layer

An evaluation method and water layer technology, which is applied in the field of comprehensive analysis software for mud logging data, can solve the problems of tedious and time-consuming manual interpretation, ignoring data information, intelligent interpretation and evaluation of undiscovered mud logging oil, gas and water layers, etc.

Inactive Publication Date: 2019-07-09
CHINA NAT OFFSHORE OIL CORP +1
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0002] Each individual technique in geochemical mud logging (rock pyrolysis analysis, thermal evaporation hydrocarbon analysis and light hydrocarbon analysis), NMR mud logging, and gas logging mud logging contains different characteristic parameters. Traditional interpretation methods generally select individual parameters for interpretation, and often ignore Lose the hidden information in the data, and manual interpretation is cumbersome and time-consuming
Judging from the references retrieved so far, no articles or patents related to intelligent interpretation and evaluation of mud logging oil, gas and water layers have been found

Method used

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  • Intelligent interpretation and evaluation method for logging oil-gas-water layer
  • Intelligent interpretation and evaluation method for logging oil-gas-water layer
  • Intelligent interpretation and evaluation method for logging oil-gas-water layer

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] The specific steps of the mud logging interpretation evaluation method based on the classification model are as follows:

[0051] 1), data preprocessing, delete and sort out the original data, delete outliers, including data preparation, data cleaning, data integration, data transformation and data reduction

[0052] 2), select the appropriate proportion of training set and test set, and create four classification models of Naive Bayesian, decision tree, BP neural network and support vector machine for training

[0053] 3) Verify and evaluate the classification results of the four classification models of naive Bayesian, decision tree, BP neural network and support vector machine

[0054]Using four classification algorithms based on the classification model, naive Bayesian, decision tree, BP neural network, and support vector machine, to classify the rock pyrolysis technology of Minghuazhen Formation heavy oil in a certain area, after step 1) Data preprocessing, the ro...

Embodiment 2

[0056] The specific steps of the mud logging interpretation evaluation method based on time series mode are as follows:

[0057] 1), select the standard display curve segment, including the standard gas curve of oil layer, oil-water layer, oil-bearing water layer and water layer ( Figure 6 )

[0058] 2), using the activity stratification method to process the gas logging curve of the whole well, and obtain the comparison curve segment

[0059] 3), carry out piecewise linear representation and equal-length transformation and reciprocal processing to comparison curve and standard curve ( Figure 7 , 8 ,9)

[0060] 4), calculate the distance between the comparison curve and the standard curve, including the distance based on the shape and slope, the Euclidean distance and the dynamic time bending distance, compare and analyze the different distances, and combine the manual identification to qualitatively compare the curve ( Figure 10 ) using the similarity search method bas...

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Abstract

The invention relates to an intelligent interpretation and evaluation method for logging an oil-gas-water layer. According to the method, logging parameters are scientifically classified on the basisof six classification models of Bayes, decision trees, neural networks, support vector machines, clustering analysis and correlation analysis in data mining Meanwhile, the time sequence database similarity search method based on the time sequence mode is used for quickly determining the gas logging curve, and compared with a manual interpretation method, the time sequence database similarity search method based on the time sequence mode is faster and more accurate and has obvious advantages.

Description

technical field [0001] The invention relates to comprehensive analysis software for mud logging data, in particular to a method for interpreting and evaluating mud logging intelligent oil, gas and water layers. Background technique [0002] Each individual technique in geochemical mud logging (rock pyrolysis analysis, thermal evaporation hydrocarbon analysis and light hydrocarbon analysis), NMR mud logging, and gas logging mud logging contains different characteristic parameters. Traditional interpretation methods generally select individual parameters for interpretation, and often ignore The hidden information in the data is lost, and manual interpretation is cumbersome and time-consuming. Judging from the references retrieved so far, no articles or patents related to intelligent interpretation and evaluation of mud logging oil, gas and water layers have been found. Contents of the invention [0003] The purpose of the present invention is to provide a scientific and eff...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F17/50
CPCG06F30/20G06F18/2411G06F18/24155G06F18/24323G06F18/241
Inventor 胡云谭忠健吴昊晟黄子舰尚锁贵吴立伟毛敏郭明宇张建斌倪朋勃李阳桑月浦荆文明袁胜斌李鸿儒
Owner CHINA NAT OFFSHORE OIL CORP
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