A New Way to Forecast Gas-Oil Ratios GOR and Solution Gas Production from Unconventional Oil Reservoirs

Abstract

Unconventional reservoirs, characterized by their ultra-low permeability and porosity, have complicated production mechanisms yet to be fully understood. Gas produced from unconventional oil reservoirs are majorly classified as the secondary product, with the focus on oil. However, gas plays a vital role in the production of oil from unconventional plays and can be economically beneficial as well. Therefore, while oil production forecasting is highly important, it is equally imperative to figure out ways in which solution gas production can be forecasted. There has been very little information in the literature about forecasting solution gas production. The huge question is - can we possibly forecast gas-oil ratios and ultimately, solution gas production? And if we can, can we do that with some reasonable level of certainty? This paper attempts to answer these questions by exploring the use of an Asymmetrical Sigmoid Model (ASM) to forecast gas-oil ratios (GOR) and solution gas production. Asymmetrical sigmoid functions have been applied in several fields of study such as biology, finance, agriculture, etc. Research into the possibility of employing the use of this type of function for predicting future GOR values, arose from studies and observation of the nature of GOR profiles of wells in unconventional oil reservoirs. This paper presents a new approach to forecasting gas-oil ratios and solution gas production - the Asymmetrical Sigmoid Model (ASM). A commercial compositional reservoir simulator was used to simulate 30 years of production from multi-fractured horizontal wells (MFHW) with different reservoir fluids. Further, ASM was used to forecast producing gas-oil ratios from the wells with production histories ranging from six months to 3 years. The results were compared to simulated GOR data. Solution gas production were then calculated from the estimated producing gas-oil ratios using the trapezoidal rule and compared to simulated solution gas production data as well. This methodology was similarly applied to field data from various wells in different shale oil reservoirs and the results were compared to the available historical field data. In recent years, factors such as limited production data, complex flow mechanisms of liquid-rich shale reservoirs, production pattern of producing gas-oil ratios among others, have made the task of forecasting GOR and solution gas production difficult. However, ASM enables us to have a simple functional approach that empiricallymimicsthe basic pattern of producing GOR profiles in unconventional oil reservoirs quite well. ASM also helps to forecast gas-oil ratios and solution gas production with reasonable measures of accuracy. After the application of ASM to available historical data, and comparing the results with simulated and field data, there were relatively low error percentages in majority of the cases considered. Due to the continuous rise in global demand for energy, and its corresponding economic implications, the importance of research focused on improving and finding new ways of accurately forecasting oil and gas production cannot be downplayed. This work presents aninnovative and easyway offorecasting gas-oil ratios and solution gas production from unconventional oil plays. It is a valuable contribution to the ongoing efforts of research into better and simpler ways of forecasting production from unconventional reservoirs. Findings from this work can help to improve reserves estimation, reservoir management, field development planning and overall project economics.