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Method and equipment for measuring sand content of drilling fluid based on neural network

A technology of neural network and measurement method, applied in the direction of neural learning method, biological neural network model, measurement device, etc., can solve the problems of low precision, long time consumption, poor real-time performance, etc., to improve model accuracy, increase robustness, Avoid the effect of well collapse

Active Publication Date: 2022-04-05
CHINA UNIV OF GEOSCIENCES (WUHAN)
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Problems solved by technology

However, the automatic detection of sand content in drilling fluid is still at the stage of manual detection, which takes a long time, has poor real-time performance and low accuracy

Method used

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  • Method and equipment for measuring sand content of drilling fluid based on neural network
  • Method and equipment for measuring sand content of drilling fluid based on neural network
  • Method and equipment for measuring sand content of drilling fluid based on neural network

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Embodiment 1

[0055] Embodiment 1 discloses a soft sensor technology for sand content in drilling fluid based on artificial neural network, including the following steps: acquisition of mud performance parameters, data analysis and screening, data preprocessing, data expansion and division, model training and For model accuracy evaluation, see the attached figure 1 .

[0056] Obtain mud performance parameters. When obtaining mud performance parameters, firstly determine the mud formula. The mud formula selected in the embodiment of the present application is: 5% bentonite + 0.5% soda ash + 0.4% xanthan gum, and 1L of mud is prepared for use.

[0057] When preparing mud, pay attention to turn on the mixer first when adding the medicine, and add the medicine while stirring to prevent the medicine from agglomerating and affecting the hydration effect of the mud. After the mud to be tested is prepared, it is stirred at high speed for one hour, and then left to hydrate for 24 hours before addi...

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Abstract

The invention provides a method for measuring the sand content of drilling fluid based on an artificial neural network. The method comprises the following steps: collecting performance parameters of a plurality of groups of mud with different sand contents; screening and analyzing performance parameters of the mud, calculating to obtain Heschell-Balkel three parameters according to the screened and analyzed performance parameters, and taking the screened and analyzed performance parameters and the Heschell-Balkel three parameters as input parameters; performing data expansion and division on the input parameters to obtain a training set, a verification set and a test set; constructing an ANN neural network model, and iteratively training and verifying the ANN neural network model by using the training set and the verification set; and evaluating the prediction effect of the trained neural network model by using the test set, and measuring the sand content of the drilling fluid by using the neural network model meeting the preset prediction effect. A small amount of limited existing data is analyzed, processed and expanded to obtain an accurate prediction model.

Description

technical field [0001] The invention relates to the technical field of neural networks, in particular to a method and equipment for measuring the sand content of drilling fluid based on neural networks. Background technique [0002] The main function of the drilling fluid is to suspend drilling slag, protect the well wall, cool the drill bit and lubricate the drilling tool. The change in the performance of the drilling fluid will directly affect the mechanical penetration rate, the life of the drill bit, the stability of the hole wall, and the purification in the hole. Excessively high content of useless solid phase will deteriorate the rheological properties of the drilling fluid, and the flow state will deteriorate, causing accidents such as drilling up and down stuck, pressure surge and so on. In addition, the wear and tear on pipes, drill bits, water pump cylinder liners, and piston rods will also increase, shortening the service life. Therefore, it is very important to...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N15/06G01N9/36G01N11/00G01N33/00G06N3/08
Inventor 张棣段隆臣高辉赵振刘乃鹏
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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