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Advances in seismic acquisition, processing, computing hardware and theory continue to enhance seismic-image quality. However, an investment decision on seismic projects should be based not only technical criteria but a quantifiable expected value above all currently available field data including well information. This presentation will include a case history of a major carbonate oil field demonstrating how this value was estimated before a major reprocessing project and how this value is being achieved. This field contains over 1000 wellbore penetrations. A 3D seismic survey was acquired over the field during 2001–2002, but the reservoir development team believed that these data to date had added limited value. The motivation for evaluating the potential for further investment in seismic data was a multi-billion-dollar field-redevelopment plan. The Value of Information (VOI) exercise to justify a seismic project began with an evaluation of technical issues that limited the use of existing seismic data. Through a targeted fast track reprocessing effort it was determined that the existing survey had been designed and acquired adequately, and that the deficiencies in the dataset at the reservoir level are primarily caused by near-surface and overburden effects. The first-order impact is that mapped seismic surfaces exhibit a "roughness" primarily from the overlying "non-geologic" noise. There was concern that many subtle faults interpreted at the reservoir level could be "non-geologic" artifacts which resulted in reluctance to incorporate these into the reservoir model. Amplitude balancing issues in the original data precluded quantitative assessments such as porosity prediction. The targeted reprocessing also verified that existing algorithms and traditional workflows alone were insufficient to resolve the technical issues. Working with the reservoir development team the key business drivers for reprocessing were identified as follows: Increase individual well productivity and recoveryImage and define new opportunities in current poor-data areasSave on well cost by preventing re-drillsImprove overall field development plan Specific expected value metrics and risks were assigned to the above objectives and a VOI assessment was completed. It was estimated that successfully achieving the above business objectives would result in a potential value at least 15 times the cost of the reprocessing. This resulted in management approval of the full field reprocessing. Following completion of the seismic reprocessing, the project team objectively assessed whether the technical criteria had been achieved and if the business criteria will be achieved. In both cases the team determined that value metrics will be met. The reprocessing has impacted drill-wells as well as field development planning. In addition, the reprocessed seismic data will produce additional potential value as a result of opportunities not recognized at the start of the project.
Advances in seismic acquisition, processing, computing hardware and theory continue to enhance seismic-image quality. However, an investment decision on seismic projects should be based not only technical criteria but a quantifiable expected value above all currently available field data including well information. This presentation will include a case history of a major carbonate oil field demonstrating how this value was estimated before a major reprocessing project and how this value is being achieved. This field contains over 1000 wellbore penetrations. A 3D seismic survey was acquired over the field during 2001–2002, but the reservoir development team believed that these data to date had added limited value. The motivation for evaluating the potential for further investment in seismic data was a multi-billion-dollar field-redevelopment plan. The Value of Information (VOI) exercise to justify a seismic project began with an evaluation of technical issues that limited the use of existing seismic data. Through a targeted fast track reprocessing effort it was determined that the existing survey had been designed and acquired adequately, and that the deficiencies in the dataset at the reservoir level are primarily caused by near-surface and overburden effects. The first-order impact is that mapped seismic surfaces exhibit a "roughness" primarily from the overlying "non-geologic" noise. There was concern that many subtle faults interpreted at the reservoir level could be "non-geologic" artifacts which resulted in reluctance to incorporate these into the reservoir model. Amplitude balancing issues in the original data precluded quantitative assessments such as porosity prediction. The targeted reprocessing also verified that existing algorithms and traditional workflows alone were insufficient to resolve the technical issues. Working with the reservoir development team the key business drivers for reprocessing were identified as follows: Increase individual well productivity and recoveryImage and define new opportunities in current poor-data areasSave on well cost by preventing re-drillsImprove overall field development plan Specific expected value metrics and risks were assigned to the above objectives and a VOI assessment was completed. It was estimated that successfully achieving the above business objectives would result in a potential value at least 15 times the cost of the reprocessing. This resulted in management approval of the full field reprocessing. Following completion of the seismic reprocessing, the project team objectively assessed whether the technical criteria had been achieved and if the business criteria will be achieved. In both cases the team determined that value metrics will be met. The reprocessing has impacted drill-wells as well as field development planning. In addition, the reprocessed seismic data will produce additional potential value as a result of opportunities not recognized at the start of the project.
The ability to identify subtle structural and paleo geomorphological features within carbonates may significantly reduce wide range of drilling challenges including stuck pipe, breakouts, casing failure, lost circulation, hole collapse, washouts, etc. Current study emphasis on integrated approach to discuss drilling challenges, their possible mitigations and subsurface risk assessment. This study is a multi-disciplinary application of integrated borehole and advanced seismic attributes to identify hazards, mainly linked with drilling problems. In this regards, paleo structure mapping is initially utilized to broadly outline areas in the field that may be associated with potential karst collapse features development. These karst collapse features are mainly responsible for dynamic mud losses and may also cause other problems (e.g., casing failure, etc.). One of the main challenges observed to confidently characterize karst collapse and other subtle features is that seismic data contains a lot of overburden noise hence an improved approach is proposed to eliminate seismic noise and enhance S/N ratio. Advanced seismic attribute volumes are then produced to capture full field lateral as well as vertical distribution of subtle features. Integrated results are calibrated with borehole image, core, logs, PLT, mud losses, Hall plot and CUM injection in vicinity. A novel approach is introduced to calculate unmonitored injection area of influence and other associated subsurface risks assessment. An improved Integrated approach used in this paper shows promising results. Full field distribution of karst collapse features is outlined confidently and results are validated with dynamic data and diffraction seismic imaging. Vertical extent of karstified zone is clearly captured in cross sectional view, which ties with petrophysical zonation, PLT, core and dynamic mud losses. Furthermore, the novel approach of Injection area of influence calculation improves subsurface understanding and highlight other challenges e.g. pressure anomalies or future disposal wells planning, etc. Two examples are presented in this paper for reference. An approach defined in this paper improves confidence in subsurface hazards identification, well plan optimization and minimizing unexpected costs associated with mud losses, sidetracks, etc.
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