Identification of Complex Fluid Properties in Condensate Gas Reservoirs Based on Gas–Oil Ratio Parameters Calculated by Optimization Mathematical Model

Abstract

In the production development stages of volatile oil reservoirs and condensate gas reservoirs, especially in the early stages of production, the phenomenon of high gas–oil ratio often occurs. As a result, the prediction results of oil and gas are greatly deviated from the actual situation, which seriously affects the implementation of potential excavation and increases production operation for condensate gas reservoirs. Therefore, the accurate identification of condensate gas and volatile oil is the key to improve the development efficiency in condensate reservoirs. However, due to the similar geophysical logging response characteristics for condensate gas, volatile oil, and light oil reservoirs, the qualitative identification effect only based on conventional logging is not ideal. Therefore, we propose a method to calculate the gas–oil ratio by introducing gas logging information and use the gas–oil ratio quantitative calculation results to identify condensate gas and volatile oil layers. First, we establish a physical model of the formation components of the condensate gas reservoir. Based on this physical model, we establish the response equations of various logging tools and evaluate the correlation between the gas logging information and the production gas–oil ratio to establish the response equation of gas logging. Then, we comprehensively use the well logging and gas logging response equations to establish an optimization mathematical model, solve the optimization objective function, obtain the relative content of natural gas and movable oil in the formation to calculate the gas–oil ratio parameters, and finally use this calculation result of the gas–oil ratio to quantitatively identify the fluid type. The application results show that the gas–oil ratio quantitative calculation method that we proposed can calculate the gas–oil ratio parameter accurately, and the calculation results are consistent with the formation testing data, which provides technical support for the identification of complex fluid properties in condensate gas reservoirs.