Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Dukhan Field affords an opportunity to assess alternative near surface velocity modeling workflows that specifically integrate Microgravity (MGR) and Vertical Electrical Sounding (VES). A pilot study of the Dukhan seismic data demonstrates that integration of MGR/VES into Pre-Stack Depth Migration (PSDM) improves the fidelity of seismic images and results in an improved depth match.In many giant carbonate reservoirs, variations in surface and near surface geology result in velocity issues that are not necessarily corrected by standard seismic data processing workflows. A novel approach integrates MGR and VES inversion into processing workflows. Initial calibration and testing of MGR/ VES data were computed on a pilot area (165 sq.km) at Dukhan which improved the near surface geological model between the surface and the first observed seismic reflector -Simsima Formation. Processing sequences utilizing microgravity and resistivity inversion resulted in a new velocity model. Combined with structural information, the VES resistivity model constrained the gravity inversion in depth. Gardner and Faust equations facilitated building the final near surface velocity model.The resultant MGR/VES PSDM pilot model improved the velocity model between the surface and top Simsima Formation based on 1) visible impact on the deeper structure obtained from imaging and 2) better fit between the seismic depth horizons and well measured depths. Based on the results of this study, QP acquired MGR/VES data over the entire Dukhan survey area and will utilize these data in any future PSDM full-field processing. Other giant carbonate reservoirs may benefit from utilizing this workflow to further refine and enhance seismic imaging.
Dukhan Field affords an opportunity to assess alternative near surface velocity modeling workflows that specifically integrate Microgravity (MGR) and Vertical Electrical Sounding (VES). A pilot study of the Dukhan seismic data demonstrates that integration of MGR/VES into Pre-Stack Depth Migration (PSDM) improves the fidelity of seismic images and results in an improved depth match.In many giant carbonate reservoirs, variations in surface and near surface geology result in velocity issues that are not necessarily corrected by standard seismic data processing workflows. A novel approach integrates MGR and VES inversion into processing workflows. Initial calibration and testing of MGR/ VES data were computed on a pilot area (165 sq.km) at Dukhan which improved the near surface geological model between the surface and the first observed seismic reflector -Simsima Formation. Processing sequences utilizing microgravity and resistivity inversion resulted in a new velocity model. Combined with structural information, the VES resistivity model constrained the gravity inversion in depth. Gardner and Faust equations facilitated building the final near surface velocity model.The resultant MGR/VES PSDM pilot model improved the velocity model between the surface and top Simsima Formation based on 1) visible impact on the deeper structure obtained from imaging and 2) better fit between the seismic depth horizons and well measured depths. Based on the results of this study, QP acquired MGR/VES data over the entire Dukhan survey area and will utilize these data in any future PSDM full-field processing. Other giant carbonate reservoirs may benefit from utilizing this workflow to further refine and enhance seismic imaging.
After 70 years of production, more than 30% of the Arab C STOOIP has been recovered through various mechanisms including natural depletion, water flooding, gas-lift implementation and horizontal well development. Extending production into future years requires a strategic approach, focusing on innovative development optimization in order to target the remaining oil saturation. An aggressive drilling and intervention programme is ongoing to tap into the remaining oil. In addition to coupling evergreen reservoir models and flood-front surveillance, enhanced waterflood and CO2 WAG hold the greatest strategic potential to maximize recovery. Integration of a recently acquired, high-resolution 3D seismic survey complements the data available for subsurface description and characterization, positively impacting reservoir model history matching metrics. Utilizing the models to set appropriate production and injection targets and vice versa adjusting the models to new data acquired in the field maintains a tight coupling between our models and surveillance monitoring. The evergreen models facilitate optimization of infill drilling locations targeting bypassed/remaining oil for sweep improvements. Surveillance monitoring of flood-front encroachment and pressure behavior indicates that the permeable and connected beach and shoal lime grainstones of the Lower Arab C are sweeping according to simulation predictions. Conversely, the Upper Arab C exhibits a less favorable waterflooding potential due to the thin-bedded (1-2ft) grain- and mud-prone peritidal deposits that maintain significant lateral and vertical permeability contrasts. Sensitivity tests in our high-resolution full-field models support the addition of a line drive pattern to the existing peripheral waterflood for the Upper Arab C. CO2 WAG has also been identified and tested in the model as a potential EOR mechanism to improve recovery. Engineering studies are underway to develop the infrastructural requirements for a CO2 pilot. It is envisaged that the combined development strategy of both enhanced waterflood and CO2 EOR will greatly assist in producing the difficult oil and maximizing recovery in the process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.