Method and device for forecasting and pre-warning downhole abnormal working conditions in real time in shale gas fracturing processes

A technology for abnormal working conditions and real-time prediction, applied in prediction, earthwork drilling, wellbore/well components, etc., it can solve problems such as failure of real-time monitoring to be solved, and achieve the effect of improving prediction accuracy.

Active Publication Date: 2017-09-22
CHINA UNIV OF PETROLEUM (BEIJING)
View PDF4 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the real-time monitoring of downhole abnormal conditions during the fracturing process (including formation fractures, pressure channeling accidents and sand plugging accidents) has not yet been solved

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
  • Method and device for forecasting and pre-warning downhole abnormal working conditions in real time in shale gas fracturing processes
  • Method and device for forecasting and pre-warning downhole abnormal working conditions in real time in shale gas fracturing processes
  • Method and device for forecasting and pre-warning downhole abnormal working conditions in real time in shale gas fracturing processes

Examples

Experimental program
Comparison scheme
Effect test

no. 1 example

[0080] In this embodiment, the downhole operating conditions at the "pumping prefluid" stage during the fracturing process of the "Jiaoye Plate" shale gas well are used as the case object to verify the accuracy and applicability of the present invention. Wellhead pressure and displacement are characteristic parameters of abnormal working conditions during the "pump injection of prefluid" stage. Therefore, it is necessary to establish a prediction model for wellhead pressure and displacement. Next, take the wellhead pressure prediction model as an example to show the modeling steps.

[0081] 1. Establish a prediction model for monitoring parameters

[0082] 1.1) Build a training data set

[0083] Set the time window width t win =1min, prediction step length t st =1min, sampling period of wellhead pressure t c =2s, therefore, according to formula (1), the total number of time series data in each time window V=30.

[0084] Select H=10 sets of wellhead pressure time series data, respec...

no. 2 example

[0111] This embodiment provides a technical solution for a real-time prediction and early warning device for abnormal downhole working conditions during shale gas fracturing. In this technical solution, the device for real-time prediction and early warning of abnormal downhole operating conditions during shale gas fracturing includes: a model building module 91, a model training module 92, and an early warning module 93.

[0112] The model building module 91 is used to build a training data set based on offline data, and use a support vector regression machine to train a monitoring parameter prediction model.

[0113] The model training module 92 is used for extracting trend characteristics of offline data of characteristic parameters by calculating a plurality of discretized slope values, and establishing a downhole abnormal working condition monitor in the corresponding process stage based on the support vector classifier.

[0114] The early warning module 93 is configured to use t...

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

Embodiments of the invention disclose a method and device for forecasting and pre-warning downhole abnormal working conditions in real time in shale gas fracturing processes. The method comprises the following steps of: constructing a training data set on the basis of offline data, and training a monitoring parameter forecasting model by utilizing a support vector regression machine; extracting trend features of feature parameter offline data through calculating a plurality of discretized slope values, and establishing downhole abnormal working condition monitors under corresponding working procedure stages on the basis of a support vector classifier; and further carrying out real-time forecasting and pre-warning on downhole abnormal conditions on the basis of online monitoring data by utilizing the established monitoring parameter forecasting model and the downhole abnormal working condition monitors. According to the method and device r forecasting and pre-warning downhole abnormal working conditions in real time in shale gas fracturing processes, the precision of forecasting downhole abnormal working conditions is improved.

Description

Technical field [0001] The embodiment of the present invention relates to the technical field of process data pattern recognition, in particular to a method and device for real-time prediction and early warning of abnormal working conditions downhole during shale gas fracturing. Background technique [0002] Shale gas fracturing is the main technology for shale gas development. Abnormal working conditions in the fracturing process are extremely harmful. The high pressure formed in the tubing will in turn damage surface equipment, such as fracturing pumps, wellhead devices, etc., or even Destroy the formation seepage, leading to failure of fracturing construction. [0003] The prediction of abnormal downhole conditions during shale gas fracturing is essentially a pattern recognition problem. At the shale gas fracturing construction site, artificially predict the downhole working conditions in the future based on the change trend of the monitoring parameters on the data acquisition ...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06Q10/04E21B43/26
CPCE21B43/26G06F30/20G06Q10/04
Inventor 胡瑾秋张来斌张鑫
Owner CHINA UNIV OF PETROLEUM (BEIJING)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products