A New Method for Evaluating Fracability Based on Cluster Analysis and Well Logging Petrophysical Facies Division

Abstract

The fracability of rock is a crucial parameter in determining the efficiency of fracturing in tight reservoirs. However, current methods for evaluating fracability have significant limitations. This paper proposes a new method for evaluating reservoir fracability based on cluster analysis of logging petrophysical facies. This method considers rock mechanics characteristics, petrophysical response characteristics, and reservoir physical parameters, among other factors. The Well X of the block was used as the research subject. Using the brittleness index and permeability evaluation index, the reservoir fracability of the target block is classified into five categories: high brittleness and low permeability rock, high brittleness and super low permeability rock, low brittleness and low permeability rock, low brittleness and super low permeability rock, and clay/shale. Geolog software is used to generate fracability prediction profiles for representative wells based on petrophysical facies. To further validate this evaluation method, the fracture construction data and microseismic monitoring interpretation results of Well Y in a tight block of an oil field were synthesized and analyzed to predict its fracability. The overall prediction accuracy reached 81.8%, indicating that the new fracability evaluation method has good application effect.