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Fracturing data cleaning method of BP neural network based on genetic algorithm optimization

A BP neural network and genetic algorithm technology, applied in the field of oil and natural gas fracturing construction, can solve the problems of slow detection and removal, consuming a lot of manpower, material and financial resources, etc.

Active Publication Date: 2021-07-09
SOUTHWEST PETROLEUM UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The manual cleaning method is simple to operate, but with the increase of the data scale, it needs a lot of manpower, material resources, and financial resources, and the detection and removal speed will be much slower

Method used

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  • Fracturing data cleaning method of BP neural network based on genetic algorithm optimization
  • Fracturing data cleaning method of BP neural network based on genetic algorithm optimization
  • Fracturing data cleaning method of BP neural network based on genetic algorithm optimization

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Experimental program
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Embodiment

[0072] In the following, the fracturing data collected in real time during the 587746s-589251s period of the fractured wells in the YY block of the XX oilfield is taken as an example to illustrate the present invention.

[0073] (1) During fracturing construction, part of the fracturing data is exported from the fracturing instrument vehicle, and the reservoir data is used as an example to illustrate. Some data are shown in Table 1, and are combined with the well history data of the fracturing well according to industry standards. According to geological conditions, the normal threshold range of fracturing data is determined, such as parameter open flow; the range of open flow of most middle-production wells with good fracturing effects in this block is (10-20) ×10 4 m 3 / d (that is, the PJKXD column in the table) (due to different industry standards, here 10 4 10000 is 10 to the 4th power);

[0074] Table 1

[0075]

[0076]

[0077]

[0078]

[0079] (2) Manua...

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Abstract

The invention provides a fracturing data cleaning method of a BP neural network based on genetic algorithm optimization. The fracturing data cleaning method comprises the following steps: firstly, manually judging whether part of fracturing data is abnormal or not and marking; then taking 75% of marked data as a training sample set of the BP neural network optimized by the genetic algorithm, and taking the remaining 25% of marked data as a test sample set of the network; performing automatic recognization on the dirty data existing in all fracturing real-time construction data in a mode of pattern recognition. The fracturing data cleaning method is different from traditional manual cleaning, the automation degree of the method is high, and the working efficiency and the accuracy rate can be greatly improved; by analyzing the cleaned fracturing data, the fracturing site construction can be further effectively guided, decision misjudgment is reduced, and the purposes of judging the expected fracturing effect and reasonably and efficiently developing an oil and gas field are achieved.

Description

technical field [0001] The invention belongs to the technical field of oil and gas fracturing construction, in particular to a method for cleaning fracturing data based on a BP neural network optimized by a genetic algorithm. Background technique [0002] Analyzing fracturing construction data is an important means to evaluate the effect of reservoir stimulation and judge the expected effect of fracturing. In the process of fracturing data collection, due to the failure of the collection equipment, human operation does not meet the specifications and other reasons will cause data abnormalities and input abnormalities, which makes some "dirty data" in the original data. Data cleaning is the process of detecting and eliminating "dirty data" by screening the data in the database for outliers. [0003] Data cleaning in massive amounts of data is undoubtedly a complex and arduous task. Existing cleaning solutions are usually formed for the characteristics of data in different in...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/08G06N3/12
CPCG06N3/08G06N3/084G06N3/126G06F18/2433
Inventor 梁海波王怡杨海李忠兵
Owner SOUTHWEST PETROLEUM UNIV