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A fracturing data cleaning method based on genetic algorithm optimized bp neural network

A BP neural network and genetic algorithm technology, which is applied in the field of oil and gas fracturing construction, can solve the problems of slow detection and removal speed, high consumption of manpower, material resources and financial resources

Active Publication Date: 2022-07-12
SOUTHWEST PETROLEUM UNIV
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  • 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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  • A fracturing data cleaning method based on genetic algorithm optimized bp neural network
  • A fracturing data cleaning method based on genetic algorithm optimized bp neural network
  • A fracturing data cleaning method based on genetic algorithm optimized bp neural network

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Embodiment

[0072] The present invention is described below by taking the fracturing data collected in real time in the period of 587746s-589251s from the fracturing wells in the YY block of XX oilfield as an example.

[0073] (1) During the fracturing operation, some fracturing data are derived from the fracturing instrument car, and the reservoir data is taken as an example to illustrate. . The normal threshold range of fracturing data is determined by geological conditions, such as parameter open flow rate; the open flow range of most medium-production wells that have achieved good fracturing effect 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 is 10000 or 10 to the 4th power);

[0074] Table 1

[0075]

[0076]

[0077]

[0078]

[0079] (2) Manually judge whether these data are in the normal threshold interval for this column of data, and the mark in the normal threshold interval is "A=1"...

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Abstract

The invention provides a fracturing data cleaning method based on a BP neural network optimized by a genetic algorithm, which includes first manually judging whether a part of the fracturing data is abnormal and marking it, and then taking 75% of the marked data as the genetic algorithm-optimized data. The training sample set of the BP neural network, the remaining 25% of the labeled data is taken as the test sample set of the network; the "dirty data" existing in all fracturing real-time construction data is automatically identified by pattern recognition. The fracturing data cleaning method of the present invention is different from traditional manual cleaning. The method has a high degree of automation and can greatly improve work efficiency and accuracy. By analyzing the fracturing data after cleaning, it can further effectively guide the fracturing site construction and reduce Misjudgment in decision-making, and the purpose of judging the expected effect of fracturing and developing oil and gas fields reasonably and efficiently.

Description

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

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/215G06K9/62G06N3/08G06N3/12
CPCG06N3/08G06N3/084G06N3/126G06F18/2433
Inventor 梁海波王怡杨海李忠兵
Owner SOUTHWEST PETROLEUM UNIV
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