The F6 field is one of many high porosity carbonate buildups developed in offshore Sarawak, Malaysia. With maximum porosities in excess of 30%, the reservoir experiences pore collapse during depletion. As a result, the predicted reservoir compaction and surface subsidence can be in the order of 25 ft or more. This poses a significant risk in terms of the platform subsiding into the wave-base, requiring shut in of production and prompting costly "jacking up" of the platform. To mitigate the risks it is recommended to build a field-wide 3D geomechanical model, constrained by available compaction and subsidence measurements, which are used to forecast future platform movement to end of field life.The F6 field finite element geomechanical model was constructed from the 3D static structural model and populated with the calculated in-situ stresses and pore pressure distribution in the field from the reservoir simulations. The rock properties assigned in the model were derived from both log data and numerous core tests, which also defined their deformation and failure behaviour.The F6 field has an on-going monitoring program, including compaction logging data in the reservoir, GPS data on the platform (both lateral and vertical movements), and sonar data for the platform height above sea level. Intermittent data gathered includes sonar seabed surveys of the subsidence bowl. This paper describes the data collected and how it is used to constrain the 3D finiteelement geomechanical model constructed of the F6 field. The key findings of this study include; firstly, the importance of hard data in terms of reservoir compaction (compaction logging) and how this is translated through the overburden to surface subsidence (GPS measurements). Secondly, the importance of an accurate pre-production baseline for the monitoring program; it is relatively easy to match the rate of subsidence predicted from the model with the monitoring data collected after production start-up, however, the lack of pre-production data can lead to significant differences in the predicted absolute subsidence at end of field life.The results of this study show the importance and value of geomechanical modeling constrained by historical observations from a field monitoring program and the necessity to have it included as part of the field development plan prior to start of production. Use of this data with geomechanical forecasting is now a significant component of production assurance for the asset and has lead to plans to increase coverage and frequency of data gathering over these highly compactable fields.
This paper describes the results of an integrated study to assess redevelopment options in a mature field with over 40 years of production. The field has been produced under gas cap drive and partly under an internal gas injection scheme to increase oil recoveries. The objective of the study was to confirm the effectiveness and possible expansion of the gas injection scheme and to assess merits of waterflooding.A two phased modeling approach was adopted and a coarse Phase 1 model for the entire reservoir stack was built using existing interpretations and data available from previous studies while seismic reinterpretation and petrophysical reevaluation to feed the detailed Phase 2 models was ongoing. The Phase 1 model helped to understand the plumbing between the sands and fault blocks and the key parameters impacting field level pressure and cumulative fluid history matches. In Phase 2, two separate models were built for groups of reservoirs at a much finer vertical scale to address sand specific saturation changes and individual well performance.A structured experimental design (ED) methodology using SUM (Shell proprietary software) was used to explore the full uncertainty space for potential history matches and use calibrated models with the remaining uncertainties to generate a range of forecasts. With the large number of reservoirs involved even a modest number of uncertainties resulted in a large number of ED parameters. The number of parameters and their associated uncertainties was partly narrowed down and constrained in Phase 1 allowing focusing on detailed reservoir specific parameters in Phase 2. In parallel with and complementing the simulation work, conventional contact mapping integrating the historical pressure, water cut and GOR data was carried out to locate potential areas with remaining oil. This paper will highlight how the phased modeling approach facilitated early integration of reservoir and well performance data for detailed static model construction, ways of managing uncertainty in a brown field with multiple reservoirs, large number of wells and more than 40 years of production history, and finally how traditional reservoir assessment techniques can complement reservoir modeling work. IntroductionThe studied field is located approximately 15 km offshore in water depths ranging from 10-40 m. The area of interest forms the northern part of a greater NNE-SSW trending highly faulted anticline and is separated from the main field by a major growth fault (Figure 1). The area of interest is divided into two main blocks, Block 1 and 2, by the main fault which is antithetic to a southern boundary growth fault. Block 1 shows crestal collapse faults, which were formed and affected by Mio-Pliocene inversion, that further divide it into compartments and form barriers and baffles to fluid flow. The southwestern flank of Block 1 has been intruded by two shale diapirs that have resulted in additional intrusion related fractures and faults. This hampers the aquifer connectivity to the west and southwest o...
The F6 field is one of many high porosity carbonate buildups developed in offshore Sarawak, Malaysia. With maximum porosities in excess of 30%, the reservoir experiences pore collapse during depletion. As a result, the predicted reservoir compaction and surface subsidence can be in the order of 25 ft or more. This poses a significant risk in terms of the platform subsiding into the wave-base, requiring shut in of production and prompting costly "jacking up" of the platform. To mitigate the risks it is recommended to build a field-wide 3D geomechanical model, constrained by available compaction and subsidence measurements, which are used to forecast future platform movement to end of field life.The F6 field finite element geomechanical model was constructed from the 3D static structural model and populated with the calculated in-situ stresses and pore pressure distribution in the field from the reservoir simulations. The rock properties assigned in the model were derived from both log data and numerous core tests, which also defined their deformation and failure behaviour.The F6 field has an on-going monitoring program, including compaction logging data in the reservoir, GPS data on the platform (both lateral and vertical movements), and sonar data for the platform height above sea level. Intermittent data gathered includes sonar seabed surveys of the subsidence bowl. This paper describes the data collected and how it is used to constrain the 3D finiteelement geomechanical model constructed of the F6 field. The key findings of this study include; firstly, the importance of hard data in terms of reservoir compaction (compaction logging) and how this is translated through the overburden to surface subsidence (GPS measurements). Secondly, the importance of an accurate pre-production baseline for the monitoring program; it is relatively easy to match the rate of subsidence predicted from the model with the monitoring data collected after production start-up, however, the lack of pre-production data can lead to significant differences in the predicted absolute subsidence at end of field life.The results of this study show the importance and value of geomechanical modeling constrained by historical observations from a field monitoring program and the necessity to have it included as part of the field development plan prior to start of production. Use of this data with geomechanical forecasting is now a significant component of production assurance for the asset and has lead to plans to increase coverage and frequency of data gathering over these highly compactable fields.
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