A CONNECTED DOMAIN IDENTIFICATION METHOD AND ITS APPLICATION IN QUANTITATIVE PICKUP OF CAVE INFORMATION USING ELECTRIC IMAGING LOGGING

Abstract

Solution caves are important fluid reservoir space in carbonate reservoir, and researching FMI images' caves connected domain labeling and extracting their information are meaningful. A high resolution color image can be obtained after data processing of FMI. After a series of processes which include image graying, median filtering and threshold segmentation for the color image, a binary image will be obtained which can reflect the characteristic of solution caves on the wall of a well. And on the image, caves are black spots which are labeled by same number. The labeling algorithm for image connected domain based on equivalence pair processing has the advantages of fast and no-repeat labeling, which can eliminate equivalent pairs while labeling connected domain. The solution caves in the binary image can be marked from small to large number accurately by this arithmetic, in addition, the information of every connected domain including holes' size, grading factor, area of connected domains (areal porosity) and roundness can be extracted and processed. Using the labeled binary image can calculate porosity curve which reflects development degree of caves, and based on this curve the image can be divided into several layers. On this basis, the information distribution of areal porosity, holes' size, roundness and grading factor of every layer can be calculated easily. At last, all of these informations will be used to quantitatively evaluate the carbonate reservoir which has strong heterogeneity and lots of solution caves. And this work is also a helpful exploration for quantitative extracting of cave information from FMI images.