Research On Quantitative Analysis Method Of Oil And Gas Well Visual Detection Image

Oil and gas visualization detection technology collects perforation images in wells,which provides an intuitive and effective basis for the output efficiency and production cost of oil and gas wells.The analysis of perforation shape parameters can provide data support and theoretical basis for calculating erosion area,evaluating fracturing effect and defining fracture initiation depth.At present,the visual estimation method is generally used to qualitatively observe the perforation parameters,and the evaluation results are greatly affected by human subjectivity.In order to improve the objectivity and accuracy of perforation quantitative analysis,this paper establishes a mathematical model of perforation shape based on image processing technology,analyzes and studies the perforation shape,quantifies the perforation shape parameters,and transforms the qualitative description of perforation into a more specific and intuitive quantitative analysis and evaluation.The main work of this paper is as follows:(1)Design of perforation image quantitative analysis algorithm.Firstly,the specific parameters of quantitative analysis of perforation morphology are defined by defining aperture D,perimeter L,area S,aspect ratio A and roundness(47).Secondly,aiming at the problem of excessive or insufficient segmentation in traditional image segmentation algorithms,an adaptive region growing segmentation algorithm based on K-L divergence is proposed to realize semi-automatic segmentation of perforation area.Then,the eight-neighborhood boundary tracking method is used to extract the contour of the perforation area.In order to solve the problem of serrated edge after contour extraction,the perforation contour is smoothed by cubic spline interpolation.Finally,based on the pixel coordinates of the contour,the discrete geometric analysis is carried out to calculate the perforation shape parameters,and the calculation accuracy is verified by the theoretical graph of the known shape parameters.(2)Perforation image quantitative analysis software design.Taking the quantitative analysis algorithm of perforation image as the core,according to the quantitative analysis requirements of perforation parameters,the Py Qt5 framework and Open CV image processing technology are used to design and implement the quantitative analysis software of perforation image.The software function covers the perforation image preprocessing module,the target extraction module and the morphological parameter calculation module.It can realize perforation image enhancement,perforation image segmentation and contour extraction,and the measurement of parameters such as aperture,perimeter,area,aspect ratio and roundness.It has certain application value.(3)Perforation image quantitative analysis example application.The software is used to quantitatively analyze the perforation images of 20 sections in an oil and gas well,and the morphological parameters of perforation are counted and analyzed one by one.The measurement results show that the proportion of perforation aperture in the range of 14～35mm is 91.5%.The proportion of the circumference in the range of 40-90 mm is 89.8%;the proportion of perforation area between 100～150mm~2 is as high as 93.2%.The aspect ratio exists between[0.5,2],the roundness is mostly distributed between[0.5,1],and the overall near-circularity of perforation is higher.The quantitative analysis method can be used to assist the discrimination and identification of perforation morphology,and make the description of perforation morphology more accurate and objective.It provides an important basis for workover operation and well condition management,and provides effective feedback for the optimization of production increase plan and control cost,improves economic benefits and reduces a series of industry operation risks.