27

Nov 2024

PhD Dissertation

Forecasts and uncertainty quantification of oil and gas production from Shales

 

Abstract

Recent energy consumption forecasts indicate a significant increase over the next 30 years, driven primarily by water desalination, air conditioning, transportation, and the world’s growing population. These factors contribute to global warming and climate change, primarily caused by greenhouse gas emissions. Despite the urgent need for cleaner energy, the world is not yet ready to transition fully from non-renewable to renewable energy sources. The feasibility, cost, and current efficiency of renewables are insufficient to meet future global energy demands.

Shale gas and oil production have significantly transformed the energy sector, especially in the U.S. Natural gas production from shale reservoirs has reduced carbon emissions per unit of energy, making these reservoirs critical in the energy transition. Shale gas has become one of the largest primary energy sources in the U.S. However, questions remain about the long-term viability of production from these reservoirs and their economic impact on the transition to cleaner energy.

These uncertainties come from challenges in accurately estimating reserves in mudrock plays, where current methods often overestimate potential outputs. To address this, we use a robust physics-based forecast method that provides accurate estimates of gas and oil production from shale plays. This method effectively captures the physics behind the production from hydraulically fractured horizontal wells in mudrock formations. We explore how reservoir properties, hydraulic fractures, and natural fractures influence the forecast accuracy. Additionally, we demonstrate the predictive power of this method when combined with Generalized Extreme Value (GEV) statistics. We apply this approach to the Utica-Point Pleasant formation, highlighting its significance as a key contributor to the future of U.S. shale production.

Event Quick Information

Date
27 Nov, 2024
Time
04:00 PM - 05:00 PM
Venue
KAUST, Bldg. 4, Level 5, Room 5220