The main issue is the vertical resolution of water and gas, detection and separation of the pressure and saturation signals.

Another interest is the estimation of the dynamic signals for recovery mechanisms that are complex and cyclical such as water alternating gas (WAG) (Figure ). Examining ways of clearly separating the two responses on the amplitudes and time-shifts. For example, the case of one producing reservoir unit overlying another, with variable thicknesses and reservoir quality. Our hope is to extend the applicability of the method to reservoir situations in which the 4D dynamic signals overlap. This will combine with a critical assessment of what we cannot and can detect using the 4D seismic monitoring technique. Here our intention is to continue this trajectory by considering more applications to clastic and chalk reservoirs. Recent advances also include stochastic inversion and machine learning applications (Corte et al. To date, analyses have included AVO (restricted offset stacks), engineering consistent multi-attribute inversions, the use of inverted impedance changes and post-stack time- shifts. We also focus on better understanding the R factor and defining a rock mechanical model for 4D seismic geomechanics interpretation. The challenge here is to improve our current definition by careful inversion and modelling, and study of several geomechanically active datasets. Advances have been made in working with post-stack time shifts, however pre-stack TVO and AVO remain two additional dimensions to exploit to better understand the principal components of strain (and stresses) in the overburden and reservoir. The third topic for consideration is the familiar seismic geomechanics, for which much remains to be done. Our hope is to recover an understanding of reservoir connectivity and transmissibility to act as an aid in field management. Within this module we also consider engineering-based studies such as well pressure interference tests, which we will attempt to link to the 4D seismic data either by deterministic algorithms or machine learning. We find that the production setting is important and hope by application of our insights to field datasets to be able to extend our methods and understanding to situations such as a stacked reservoir environment or structurally complex field settings. Despite the maturity of estimation procedures much still remains to be achieved in terms of obtaining robust, high resolution estimates directly from 4D seismic signatures.

For example, pressure-saturation separation (seis2P&S) is one of the keys to understanding the reservoir connectivity and dynamics and forms invaluable input into a seismic history match. We maintain our research effort on these topics because we believe that there are still unresolved issues and current understanding is not complete. This module contains several well-recognised and popular topics from the 4D seismic and engineering world. Research Research programme Module 2 Module 2

Wag seismac