APPLICATION OF FACTOR ANALYSIS IN LOGGING IDENTIFICATION OF FRACTURE-VUGGY CARBONATE RESERVOIRS

The fractures and vugs of the carbonate reservoirs in the Tarim Basin, China, have good prospects for exploration and development. However, the carbonate reservoirs of Tarim basin are characterized by the different scale, large regional differences and strong heterogeneity, which result in the big difficulties in logging identification. Types and characteristics of fractured-vuggy carbonate reservoirs can be visually and clearly identified by core and imaging log data the, but the cost of acquisition is high and the data are few. Conventional logging is low in cost and widely used. It is currently the key research direction to identify different reservoir types of carbonate rocks by using conventional logging data.

Factor analysis (FA) is a multivariate statistical method that integrates variables with complex relationships into a few independent factors to achieve information enrichment. It can reflect the relationship between the original variables and the factors, and each factor is highly explanatory. At present, there are relatively few studies on logging identification of fractured-vuggy carbonate reservoirs by factor analysis.

The fractures and caverns of the carbonate reservoirs in the second section of the Lianglitage Formation in the eastern part of the Tazhong area are developed, and the reservoir types are diverse and heterogeneous. Various reservoir types can be clearly identified on core and imaging logging, but it is difficult to identify in the absence of core and imaging logging data, which affects reservoir prediction and evaluation. In order to solve this problem, four reservoir types and two non-reservoir types are divided based on core, thin sections and image logging data. The reservoir types include fractured reservoir, vuggy reservoir, fractured-vuggy reservoir and cavern reservoir, and non-reservoir types include mud fillied non-reservoir and compact non-reservoir. According to these types, the conventional logging information is calibrated. Three principal factors are extracted from the six well logging parameters (GR、AC、REN、CNL、RD and∣RD/RS－1∣) by FA, which are interpreted as pore factors, fracture factors and mud factors. Finally, the factor score is calculated, and various reservoir and non-reservoir types can be effectively identified according to the factor score cross-plots. This method is used to identify the reservoir of XX well, and has high consistence with the core and imaging logging data.