Extraction of oil and gas can cause reduction in pore pressure, occasionally resulting in subsequent compaction that forms a surface subsidence bowl, especially in shallow reservoirs. In the last 10 years, there has been over 10 feet of subsidence in parts of the Lost Hills oil field in California (Bruno et al.,1992). The surface subsidence at Lost Hills not only causes damage to surface facilities and wells, but also reactivates faults and reduces rock permeability. Subsidence makes reservoir optimization difficult. Hence, it is important to assess or predict the surface subsidence and the reasons for subsidence early in the life of an oil field to make an optimization plan.
We use jointly the capacitance resistance model (CRM) (Alberoni et al., 2002 and Yousef, et al., 2006) that relies only on injection and production data, and the InSAR satellite imagery of surface subsidence. From CRM simulations, we estimate the connectivity between injectors and producers as well as general water flow directions from individual injectors. We then superimpose well connectivity and InSAR imagery to diagnose the reasons for the subsidence. Using new surface subsidence models, which are based on the continuity equation of CRM and rock mechanics, we are able to predict the average surface subsidence at Lost Hills from the injection and production rates.
Our work shows that there was significant volumetric rock damage at Lost Hills and the well connectivity changed dramatically with time because of reservoir compaction and the rock damage. We conclude that for a soft, fragile and nearly- impermeable rock such as the diatomite, high injection rate weakens the rock and creates dynamic water flow tubes or ‘channels’ without providing good pressure support to the reservoir. These high permeability ‘channels’ re-circulate most of the injected water between the injectors and producers.
Our CRM/InSAR approach is new and gives insights into the time-dependent and spatially variable fluid flow fields in a relatively shallow waterflood. Consequently, we may be able to suggest optimum water injection strategies to enhance oil production, while minimizing rock damage and surface subsidence. In addition, the proposed surface subsidence models are convenient and reliable to predict the average surface subsidence. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2011-12-4637 |
| Date | 20 February 2012 |
| Creators | Wang, Wenli, master of science in petroleum engineering |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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