Reservoir pressure monitoring via surface deformation inversion: integrating numerical modelling with evolutionary optimisation
Reza Abdollahi A * , Abbas Movassagh B , Dane Kasperczyk B and Manouchehr Haghighi AA
B
Reza Abdollahi is a PhD student at the University of Adelaide, specialising in the geomechanics of underground storage sites and oil and gas reservoirs. His research primarily explores using deformation data as an indirect method to estimate the intensity of reservoir activities. By analysing surface deformation patterns, he aims to develop predictive models that enhance the monitoring and management of reservoir dynamics, ensuring operational safety and optimising resource extraction. |
Abbas Movassagh is a Research Scientist at the CSIRO Energy Business Unit. His expertise lies in geomechanics and environmental and uncertainty analysis, including wellbore and underground reservoir integrity. He earned his PhD from the University of Adelaide and has over 15 years of experience in reservoir engineering and geomechanics. |
Dane Kasperczyk is the Subsurface Technologies Team Leader in the CSIRO Energy Resources Group. His focus areas include subsurface monitoring for energy storage, rock pre- and post-conditioning and the application of digital tools for impact analysis. He holds degrees in civil engineering and climate science from the University of Melbourne. |
Manouchehr Haghighi is an Associate Professor of Petroleum Engineering at the University of Adelaide. His research and teaching focus on unconventional reservoirs, reservoir simulation, geomechanics, well testing and formation evaluation. |
Abstract
Reservoir pressure distribution is crucial for optimising extraction, ensuring safety, enhancing recovery and mitigating environmental impacts. However, acquiring detailed distribution of pore pressure data presents challenges. Methods for directly measuring pressure, such as well-tests and bottom-hole gauges, are expensive and offer limited spatial coverage. A practical alternative involves deducing pore pressure from surface displacement observations. This technique utilises a geomechanical forward model to compute deformation based on pore pressure and employs an optimisation algorithm to address the inversion problem’s inherently ill-posed characteristics. While deformation estimation through forward models is well understood, the application of surface displacement data for mapping reservoir pressure remains underexplored. Previous research has applied various approaches – including analytical, semi-analytical and numerical models – in combination with optimisation algorithms. Analytical and semi-analytical techniques often oversimplify reservoir complexities, while advanced numerical methods may require substantial computational resources. Furthermore, these techniques often depend on prior data, which are not always readily available. This research overcomes these limitations by combining advanced numerical modelling with evolutionary algorithms to estimate pressure distribution from tiltmeter data, eliminating the need for pre-existing information. The forward model incorporates a discrete Green matrix, derived by integrating finite element simulations with scripting tools. This matrix captures the interplay between reservoir properties and geometry with the resulting displacement field, enabling efficient deformation analysis under various pressure distributions. By precomputing the Green’s matrix, computational demands are significantly reduced, enhancing the optimisation process. Testing on synthetic data demonstrated the method’s accuracy with a reasonable error.
Keywords: artificial bee colony, discrete Green matrix, evolutionary optimisation, finite element model, genetic algorithm, geomechanics, particle swarm optimisation, reservoir pressure monitoring, surface deformation inversion.
Reza Abdollahi is a PhD student at the University of Adelaide, specialising in the geomechanics of underground storage sites and oil and gas reservoirs. His research primarily explores using deformation data as an indirect method to estimate the intensity of reservoir activities. By analysing surface deformation patterns, he aims to develop predictive models that enhance the monitoring and management of reservoir dynamics, ensuring operational safety and optimising resource extraction. |
Abbas Movassagh is a Research Scientist at the CSIRO Energy Business Unit. His expertise lies in geomechanics and environmental and uncertainty analysis, including wellbore and underground reservoir integrity. He earned his PhD from the University of Adelaide and has over 15 years of experience in reservoir engineering and geomechanics. |
Dane Kasperczyk is the Subsurface Technologies Team Leader in the CSIRO Energy Resources Group. His focus areas include subsurface monitoring for energy storage, rock pre- and post-conditioning and the application of digital tools for impact analysis. He holds degrees in civil engineering and climate science from the University of Melbourne. |
Manouchehr Haghighi is an Associate Professor of Petroleum Engineering at the University of Adelaide. His research and teaching focus on unconventional reservoirs, reservoir simulation, geomechanics, well testing and formation evaluation. |
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