Method for establishing coal seam gas content prediction model, and device thereof, terminal and storage medium

A prediction model and technology of gas content, applied in prediction, neural learning methods, biological neural network models, etc., can solve problems such as long time, unable to be applied on a large scale, and high equipment requirements

Pending Publication Date: 2021-06-18
CHINA UNIV OF MINING & TECH (BEIJING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The accuracy of this method is very high, but this method is expensive, takes a long time, requires high equipment, and cannot be applied on a large scale

Method used

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  • Method for establishing coal seam gas content prediction model, and device thereof, terminal and storage medium
  • Method for establishing coal seam gas content prediction model, and device thereof, terminal and storage medium
  • Method for establishing coal seam gas content prediction model, and device thereof, terminal and storage medium

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Embodiment 1

[0067] Embodiment 1 of the present invention discloses a method for establishing a coal seam gas content prediction model, such as figure 1 as well as figure 2 shown, including the following steps:

[0068] Step S100, obtaining raw data; the raw data includes a plurality of characteristics of the preset coal seam logging and gas content data as a tag value; the characteristics include formation characteristics, geophysical logging characteristics, geophysical seismic characteristics and industrial group of coal at least one of the sub-characteristics;

[0069] Specifically, each feature is obtained by detecting the same depth of the logging; the features include: stratum features, geophysical logging features, geophysical seismic features, and industrial component features of coal.

[0070] Firstly, the coal seam gas content data in the study area is collected as the label value, and the formation characteristics (thickness, roof and floor lithology characteristics, etc.), ...

Embodiment 2

[0125] Embodiment 2 of the present invention also discloses a device for establishing a coal seam gas content prediction model, such as Image 6 shown, including:

[0126] The acquisition module 201 is used to acquire raw data; the raw data includes multiple characteristics of preset coal seam logging and gas content data as tag values; the characteristics include formation characteristics, geophysical logging characteristics, geophysical seismic characteristics and coal industrial at least one of the constituent characteristics;

[0127] A preprocessing module 202, configured to perform data preprocessing on the raw data to obtain sample data;

[0128] An analysis module 203, configured to perform principal component analysis on the sample data to obtain an analyzed characteristic data set;

[0129] A division module 204, configured to obtain a training set and a test set by dividing the feature data set;

[0130] The training module 205 is used to train the LSTM model bas...

Embodiment 3

[0154] Embodiment 3 of the present invention also discloses a terminal, which includes a processor and a memory, and an application program is stored in the memory. When the application program runs on the processor, the method for establishing a coal seam gas content prediction model in Embodiment 1 is executed.

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Abstract

The invention discloses a method for establishing a coal seam gas content prediction model, and a device thereof, a terminal and a storage medium. The method comprises the following steps: 1, acquiring original data; 2, performing data preprocessing on the original data to obtain sample data; 3, performing principal component analysis on the sample data to obtain an analyzed feature data set; 4, dividing the feature data set to obtain a training set and a test set; 5, training the LSTM model based on the training set to obtain a trained LSTM model; 6, testing the trained LSTM model by using the test set; and 7, if the test is passed, setting the trained LSTM model as a coal seam gas content prediction model. The coal seam gas content prediction model established through the scheme is high in coal seam gas prediction speed and high in efficiency, and large-scale application can be achieved.

Description

technical field [0001] The invention relates to the field of prediction of coal bed gas, in particular to a method, device, terminal and storage medium for establishing a prediction model of coal bed gas content. Background technique [0002] In my country's energy resources, coal accounts for a large proportion, and in the total energy consumption, coal also occupies an important position. With the continuous development of social economy, clean use of coal has become more and more mainstream. Among them, the use of coalbed methane is a An important clean use of coal. In this case, the accurate prediction of coalbed methane becomes an important part of the clean use of coal resources. At present, there are many methods for predicting the content of coalbed methane, one of which is to sample and core the coal seam, and then transport it to the laboratory for measurement. The accuracy of this method is very high, but the cost of this method is high, the time is long, and the...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/02G06N3/04G06N3/08
CPCG06Q10/04G06Q50/02G06N3/08G06N3/044
Inventor 师素珍齐佑朝段培飞韩琦
Owner CHINA UNIV OF MINING & TECH (BEIJING)
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