An Effective Numerical Model for Fracture-Stimulated Condensate Reservoir Production History Matching, Surveillance, and Prediction

Jia, Xinli (Halliburton) | Filippov, Andrey (Halliburton) | Khoriakov, Vitaly (Halliburton) | McNealy, Timothy (Halliburton)

OnePetro 

Abstract

The development of unconventional hydrocarbons has become a significant resource, leading to growth of worldwide oil and natural gas supplies. Hydraulic fracturing has been successfully employed for unconventional oil and gas recovery for decades. In recent years, the rapid progress of technology has led to reduced gas prices and a shift in focus to liquid extraction.

However, liquid flow, both in the wellbore and channels inside porous media or fractures, experiences more resistance compared to gas, resulting in significant pressure losses in the wellbore and fractures. Reservoir productivity also becomes more complex because of relative permeability effects. Forecasting production and estimating shale reserves is still not fully understood because of the limited knowledge of flow mechanics in ultralow-permeability rock.

Many analytical, semi-analytical, and numerical models have been developed to better understand flow in ultralow-permeability rocks and hydraulic fractures. Because analytical models only apply to mostly dry gas reservoirs, numerical reservoir simulation is generally believed to be the most rigorous and accurate method for liquid-rich formations. However, the drawbacks of using reservoir simulation are substantial. Some examples include the significant data requirements, level of expertise required to set up the model, and the demanding turnaround times for meeting the design, optimization, and decision-making cycle deadlines. Also, because each engineer is responsible for a large number of wells, full-scale three-dimensional (3D) reservoir modeling is impossible for a majority of wells.

Therefore, an approach is required that is less time-consuming than detailed reservoir simulation while still being sufficiently accurate to capture the physics of the process. It should be based on numerical modeling of multiphase flow in the interconnecting system of the wellbore and fractures, with the reservoir represented by a productivity index (PI) inflow model, as well as a physics-based pressure-volume-temperature (PVT) model for phase transition and phase equilibrium. The production decline and prediction should be analyzed based on reservoir depletion, relative permeabilities, and fracture conductivities.

This paper describes a numerical fracture production model (FPM) based on the previously mentioned physics that can be used to simulate production resulting from reservoir depletion and analyze historical production data. The outcome of the model focuses on a few primary input parameters that are dedicated to predicting future production and quickly analyzing the parametric effects and economic value of fracture-stimulated condensate reservoirs. The model is validated using two commercially available software programs, as well as historical production data of an Eagle Ford play. The outputs are then used for history matching, sensitivity analysis, parameter optimization, and future production prediction.