Tuanfeng Zhang

Memory-Efficient Categorical Multi-point Statistics Algorithms Based on Compact Search Trees

Multi-point statistics (MPS) has emerged as an advanced geomodeling approach. A practical MPS algorithm named snesim (simple normal equations simulation), which uses categorical-variable training images, was proposed in 2001. The snesim algorithm generates a search tree to store the occurrence statistics of all patterns in the training image within a given set of search templates before the simulation proceeds. The snesim search tree concept makes MPS simulation central processing unit efficient but consumes large amounts of memory, particularly when three-dimensional training images contain complex patterns and when a large search template is required to ensure optimal reproduction of the image patterns. To crack the memory-restriction bottleneck, we have developed a compact search tree that contains the same information but reduces memory cost by one order of magnitude. Furthermore, the compact structure also accelerates MPS simulation significantly. Such remarkable improvement makes MPS a more practical tool to use in building the large and complex three-dimensional facies models required in the oil and gas industry.

Structure- and Texture-Based Fullbore Image Reconstruction

Borehole image logs are produced by tools lowered into a well. Such logs provide oriented electrical and acoustic maps of rocks and fluids encountered in the borehole. Electrical borehole images, acquired in either water-based (conductive) or oil-based (nonconductive) muds, are generated from electrodes arranged in fixed patterns on pads pressed against the borehole wall. Depending on borehole diameter, gaps nearly always occur between pads. Because of these gaps, it is common to have nonimaged parts of the borehole wall. The existence of gaps in pad-based borehole images hinders efficient geological interpretation and accurate formation evaluation. A novel method to generate fullbore images combines an inpainting technique with FilterSim: a continuous-variable multipoint statistical approach. The inpainting algorithm detects dips and captures the trend of borehole image logs. The extracted smooth trend maps are fed into FilterSim to guide the construction of high-resolution textures that honor the original borehole image data, leading to seamless reconstruction of 360

Method to Generate Fullbore Images Using Borehole Images and Multi-Point Statistics

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Numerical Modeling Of Heterogeneous Carbonates And Multi-Scale Dynamics

∘ fullbore images. The proposed method has been tested using various borehole image patterns and proves to be a reliable and robust way to perform fullbore image reconstruction. The reconstructed fullbore images facilitate improved visualization and interpretation of borehole image logs in various ways, including automated dip picking for fractures and bedding planes, thin-bed analysis in deepwater formations, complex heterogeneity analysis, and accurate porosity estimation in carbonates.