Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Reservoir classification method and device, electronic equipment and computer readable storage medium

A classification method and reservoir technology, applied in the computer field, can solve the problems of low classification accuracy and low work efficiency, and achieve the effect of improving accuracy and work efficiency.

Pending Publication Date: 2022-05-27
北京月新时代科技股份有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The manual-based reservoir classification method mainly relies on expert experience and will be affected by subjective factors. The accuracy of classification is low, and the work efficiency is also low in the face of a large amount of logging data.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Reservoir classification method and device, electronic equipment and computer readable storage medium
  • Reservoir classification method and device, electronic equipment and computer readable storage medium
  • Reservoir classification method and device, electronic equipment and computer readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0098] In order to facilitate the understanding of this embodiment, a method for classification of reservoirs disclosed in the embodiment of this application is first introduced in detail. figure 1 A flow chart of a method for classification of reservoirs provided by the embodiments of the present application is shown, as figure 1 shown, including the following steps:

[0099] S101: Acquire a target imaging logging image and target conventional logging curve data corresponding to a target depth area in a target well; the target conventional logging curve data includes target logs corresponding to multiple target logging curves at the target depth area data.

[0100] Substances such as oil and natural gas are stored in the target well, wherein the oil or natural gas is stored in the target well through the reservoir. The reservoir has interconnected pores that allow oil or natural gas to be stored in the target well through the reservoir.

[0101] The target well can be a ne...

Embodiment 2

[0238] Based on the same technical concept, the embodiments of the present application also provide a reservoir classification device, Figure 4 A schematic structural diagram of a reservoir classification device provided in an embodiment of the present application is shown, as Figure 4 As shown, the device includes:

[0239] The first acquisition module 401 is used to acquire the target imaging logging image and target conventional logging curve data corresponding to the target depth area in the target well; the target conventional logging curve data includes multiple target logging curves in the The corresponding target logging data at the target depth area;

[0240] The first input module 402 is used to input the target imaging logging image into the pre-trained first convolutional neural network classification model, and the target imaging logging is performed by the first convolutional neural network classification model The first image feature of the image is processe...

Embodiment 3

[0277] Based on the same technical concept, the embodiments of the present application also provide an electronic device, Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present application is shown, such as Figure 5 As shown, the electronic device 500 includes: a processor 501, a memory 502 and a bus 503, the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor 501 and the memory 502 communicate through the bus 503 , the processor 501 executes machine-readable instructions to perform the method steps described in the first embodiment. Refer to the description of Embodiment 1 for the specific execution method steps and principles, which will not be described in detail here.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a reservoir classification method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining a target imaging logging image and target conventional logging curve data corresponding to a target depth region in a target drilling well; inputting the target imaging logging image into a first convolutional neural network classification model, and outputting a first reservoir classification result of a target reservoir corresponding to the target depth region; inputting the target conventional logging curve data into a second convolutional neural network classification model, and outputting a second reservoir classification result of the target reservoir; inputting a splicing result obtained by splicing the first reservoir classification result and the second reservoir classification result into a target full-connection layer to obtain a target reservoir classification result of the target reservoir; and determining the category of the target reservoir according to the target reservoir classification result. According to the scheme, the reservoir is automatically classified through the convolutional neural network classification model, so that the working efficiency of reservoir classification and the classification accuracy are improved.

Description

technical field [0001] The present application relates to the field of computer technology, and in particular, to a method, apparatus, electronic device, and computer-readable storage medium for classification of reservoirs. Background technique [0002] Reservoirs are rock formations that store oil and gas, and contain interconnected pores. Classification of reservoirs can objectively and generally express the oil and gas storage capacity of the reservoirs, which is of great significance for accurate and quantitative evaluation of oil and gas reserves, and plays an important guiding role in oil and gas exploration and development. [0003] In the prior art, when classifying a reservoir, the reservoir is usually classified by manually analyzing parameters such as porosity, permeability, and lithology of the reservoir. However, artificial-based reservoir classification methods mainly rely on expert experience and are subject to subjective factors, resulting in low classifica...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06V10/764G06V10/82G06V10/34G06V10/56G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/047G06N3/045G06F18/2414G06F18/2415
Inventor 任钰申瑞彩张兴聪方杰徐东兴
Owner 北京月新时代科技股份有限公司
Features
  • Generate Ideas
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More