PhD Optimal seismic monitoring for offshore storage and production Edinburgh Time-Lapse Project (ETLP)

Monitoring of subsurface fluid flow for the purposes of CO2 storage or the optimisation of hydrocarbon production relies on areal monitoring with time-lapse techniques. To address what acquisition strategy supports an optimal strategy with minimum cost is complex and requires in-depth investigation. Of importance is the economic value of the applied technique which is a function of the decisions to be made and the information content of the acquisition. The choice of the acquisition method is key (e.g. 4D seismic using towed streamer, OBN, PRM, DAS VSP, mini or focussed seismic, or non-seismic methods such as gravity or subsidence measurement). The details of the acquisition methods may also be adapted to fit the challenge, whether this is drilling risk, production challenges or CO2 plume detection. Of importance in the assessment of economic value is the timing and frequency of the monitoring strategy relative to the subsurface fluid movements. Here, an important role is played by fluid flow simulation and history matching.

Based on a Bayesian network and information theory, a range of reservoirs undergoing production or CO2 injection for storage will be studied using cost-benefit equations. This will include understanding the impact of acquisition type, design, shooting frequency, the optimal spacing of monitors and economic models. For production effects several case examples of fields undergoing water and gas injection will be considered. Attention will be paid to past examples of success as well as future projects in difficult fields. For CO2 studies both saline aquifers and depleted gas fields are considered, with examples from the UKCS and NCS for both short- and long-term monitoring. Issues include the optimal imaging of plume development, the evolution of pressure build up within the reservoir, and contributions to leakage and caprock integrity evaluation. The use of interpolators and blending based on machine learning will also be considered. Both O&G and CCS work will access past projects for which optimal designs for monitoring have been approved for reservoir management. These studies will focus on surveys in the offshore environment due to their relatively moderate cost and comprehensively proven track record when monitoring fluid changes in the North Sea.

You will join the ETLP research team that has twenty-five years of experience in quantitative 4D seismic interpretation and is funded by energy and service companies. The project leans on existing methodologies developed for modelling, rock and fluid physics, and seismic modelling and an existing monitoring toolbox developed over several decades. Field seismic data will be available from past projects which includes geological, petrophysical, geophysical and reservoir engineering information donated from companies working on CO2 projects.

For more information on ETLP activities please visit our website: https://etlp.hw.ac.uk. You will work on this PhD project supervised by a multi-disciplinary team led by Prof Colin MacBeth.