Oil well failure intelligent analysis and decision system and method

A decision-making system and fault technology, applied in decision-making scheme, oil well fault intelligent analysis and decision-making system, oil well fault intelligent analysis and decision-making system and diagnosis, prediction field, can solve problems such as hidden safety hazards, time-consuming and labor-intensive, low work efficiency and so on

Active Publication Date: 2017-05-31
XINJIANG HUALONG OILFIELD TECHNOLOGICAL LIABILITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides an intelligent analysis and decision-making system for oil well faults and a method for diagnosing, predicting, and using decision-making schemes, which overcomes the above-mentioned deficiencies in the prior art, and can effectively solve the problem in the prior art that it cannot monitor oil well downhole faults in real time , there are potential safety hazards and it takes time and effort to find a solution after a fault occurs, resulting in low work efficiency

Method used

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  • Oil well failure intelligent analysis and decision system and method
  • Oil well failure intelligent analysis and decision system and method
  • Oil well failure intelligent analysis and decision system and method

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0099] Embodiment 1: as attached figure 1 , 2 As shown, the oil well fault intelligent analysis and decision-making system includes a data acquisition module, a remote measurement and control module, a server, a database connection module and a function module. The data acquisition module includes an electrical parameter acquisition module, a temperature sensor, a pressure sensor, a dynamic liquid level measuring instrument, Chemical dynamometer, flow sensor and combustible gas detector, the electrical parameter acquisition module, temperature sensor, pressure sensor, dynamic liquid level measuring instrument, integrated dynamometer, flow sensor and combustible gas detector are all connected with the remote measurement and control module Communication connection, the server is provided with a production database and an expert database, the remote measurement and control module is connected to the production database, the production database is connected to the data acquisitio...

Embodiment 2

[0104] Embodiment 2: as attached figure 1 , 2 , 3, 4, 5, 6, and 7, a fault diagnosis method of the above-mentioned oil well fault intelligent analysis and decision-making system comprises the following steps:

[0105] The first step is the conversion of the dynamometer diagram. The data acquisition module will transmit the acquired equipment parameters to the operation monitoring module. After updating the expert database, the fault diagnosis system unit will convert the dynamometer diagram measured on the ground into the dynamometer diagram of the downhole rod pump, and the completion is successful. Graph conversion, the steps are as follows:

[0106] Establish the wave equation, the formula is as follows:

[0107]

[0108] In the formula: u(x,t) is the displacement of the cross section of the sucker rod string at the depth x at time t; x is the depth; t is the time; a is the propagation velocity of the stress on the sucker rod string; c is damping coefficient;

[010...

Embodiment 3

[0145] Embodiment 3: as attached figure 1 , 2 , 8, and 9, a failure prediction method of the above-mentioned oil well failure intelligent analysis and decision-making system, comprising the following steps:

[0146] The first step is to extract the eigenvalues ​​of the recent 5 groups of normal dynamometer diagrams of a single well, and then enter the second step;

[0147] The second step is to compare the eigenvalues ​​of the recent 5 groups of normal dynamometer diagrams of a single well with the normal dynamometer diagrams in the template library, calculate the similarity, and then enter the third step;

[0148] The third step is to establish a dynamic model of the data, that is, the GM(h,n) model. Its differential equation is a continuous function in the time domain, h is the order of the equation, and n is the number of variables. The differential equation is shown in the following formula:

[0149]

[0150] Then the coefficient vector of the differential equation ...

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Abstract

The invention relates to the technical field of oil field monitoring, in particular to an oil well failure intelligent analysis and decision system and method. The oil well failure intelligent analysis and decision system comprises a data collecting module, a remote measuring and controlling module, a server, a database connecting module and a function module. The data collecting module comprises an electrical parameter collecting module, a temperature sensor, a pressure sensor, a dynamic liquid level measuring instrument, an integrated dynamometer, a flow sensor and a combustible gas detector. The electrical parameter collecting module, the temperature sensor, the pressure sensor, the dynamic liquid level measuring instrument, the integrated dynamometer and the flow sensor are all in communication connection with the remote measuring and controlling module. A production database and an expert database are arranged in the server. The production database is in one-way communication connection with the data collecting module. The expert database is in two-way communication connection with the database connecting module. By building the oil field intelligent analysis and decision expert system, real-time monitoring, analyzing, fault diagnosing and predicting are conducted on the production parameters of an oil well, the cost of the oil field is saved, and manpower and material resources are saved.

Description

technical field [0001] The invention relates to the technical field of oil field monitoring, and relates to an intelligent analysis and decision-making system for oil well failures and methods for using diagnosis, prediction and decision-making schemes, that is, the intelligent analysis and decision-making system and method for oil well failures. Background technique [0002] At present, most of the daily production management in oilfields requires manual well patrolling, mainly relying on the workers on duty to patrol regularly and at fixed points, and relying on the senses of eyes and ears to detect abnormalities in operating equipment. The inspection workload has a lot to do with the length of the route, changes in the geographical environment and climate. When the equipment stops running between two inspections due to failure, the personnel on duty will not be able to find out in time, resulting in an increase in unsafe factors in production. [0003] When analyzing the...

Claims

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Application Information

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IPC IPC(8): E21B47/00E21B47/07E21B47/06E21B47/047E21B47/009G06F19/00
CPCE21B47/00E21B47/009E21B47/047E21B47/06E21B47/07G16Z99/00
Inventor 敬兴隆杨力李江马晓军秦润梅李树荣文恒
Owner XINJIANG HUALONG OILFIELD TECHNOLOGICAL LIABILITY
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