Well drilling slope level azimuth angle error compensating method based on neural network

A drilling inclinometer and azimuth error technology, which is applied in the application field of inertial technology, can solve the problems of increasing table construction time, large workload of table construction, affecting the accuracy of compensation, etc.

Inactive Publication Date: 2007-01-03
BEIHANG UNIV
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AI Technical Summary

Problems solved by technology

Selecting too many test points will increase the time to build the table, and selecting too few test points will affect the accuracy of compensation
The table look-up method currently used ignores the impact of the tool face angle on the azimuth angle. If the inclination angle, azimuth angle and tool face ang

Method used

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  • Well drilling slope level azimuth angle error compensating method based on neural network
  • Well drilling slope level azimuth angle error compensating method based on neural network
  • Well drilling slope level azimuth angle error compensating method based on neural network

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Embodiment Construction

[0033] For the technical scheme proposed above, take the following steps to realize the present invention:

[0034] (1) Establish a neural network model

[0035] The present invention takes the inclination angle of the drilling inclinometer, the tool face angle and the azimuth angle of preliminary calculation as the input variable of the neural network, and the real azimuth angle is used as the output variable of the neural network, and four layers (i.e. input layer, hidden layer 1, hidden layer 1, hidden layer 1) are selected. Layer 2, output layer) structure of the forward neural network. The number of nodes in the input layer of the neural network is 3, and the number of nodes in the output layer is 1. Considering that the influence of the inclination and azimuth of the drilling inclinometer on the azimuth is more complicated, the number of nodes in the hidden layer 1 is selected as 8, and the number of nodes in the hidden layer 2 is selected as 8. The neural network struc...

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Abstract

The present invention relates to a borehole clinometer azimuth angle error compensation method based on neural network. Said method includes the following four steps: 1), according to the characteristics of borehole clinometer azimuth angle output signal defining structure model of neural network; 2), obtaining training sample of neural network; 3), making neural network training and obtaining optimum neural network model parameter; and 4), utilizing inclination angle, primarily-calculated azimuth angle and tool face angle to calculate real azimuth angle.

Description

technical field [0001] The invention relates to a drilling inclinometer, in particular to a system error compensation method of the drilling inclinometer, which belongs to the application field of inertia technology and is suitable for directional drilling, well trace measurement and the like. Background technique [0002] The gyro inclinometer is an instrument that can be used for sidetracking and measuring well tracks in oilfield production. The window is actually opened in the direction of the oil layer, so that the old wells and old wells can be redeveloped, which not only saves expenses, but also greatly saves manpower and material resources. The currently widely used drilling inclinometer is composed of a two-degree-of-freedom flexible gyroscope and two quartz accelerometers. It adopts the working mode of the gyro compass and calculates the borehole inclination angle and tool face angle from the output of the accelerometer. On this basis, the azimuth angle can be calc...

Claims

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Application Information

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IPC IPC(8): E21B47/02
Inventor 郦吉臣房建成张延顺李红王群威俞文伯刘百奇杨胜李金涛
Owner BEIHANG UNIV
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