Incorporating Uncertainties in Well-Count Optimization With Experimental Design for the Deepwater Agbami Field
- Gene M. Narahara (Chevron Energy Technology Co.) | John J. Spokes (Chevron Overseas Petroleum) | David D. Brennan (ChevronTexaco Overseas Petr.) | Gregor Maxwell (ChevronTexaco UK Ltd.) | Michael S. Bast (Chevron Energy Technology Co.)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- December 2005
- Document Type
- Journal Paper
- 548 - 560
- 2005. Society of Petroleum Engineers
- 5.4.2 Gas Injection Methods, 5.5.7 Streamline Simulation, 4.1.2 Separation and Treating, 5.5.5 Evaluation of uncertainties, 4.1.9 Tanks and storage systems, 5.6.9 Production Forecasting, 2.4.3 Sand/Solids Control, 5.1 Reservoir Characterisation, 5.7.5 Economic Evaluations, 4.6 Natural Gas, 4.3.4 Scale, 5.7.2 Recovery Factors, 4.2.4 Risers, 5.5.3 Scaling Methods, 6.5.2 Water use, produced water discharge and disposal, 4.2 Pipelines, Flowlines and Risers, 5.1.2 Faults and Fracture Characterisation, 5.5 Reservoir Simulation, 3 Production and Well Operations, 5.1.5 Geologic Modeling, 1.6 Drilling Operations, 4.1.5 Processing Equipment
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This paper describes a methodology for incorporating uncertainties in theoptimization of well count for the deepwater Agbami field development. The lackof substantial reservoir-description data is common in many deepwaterdiscoveries. Therefore, the development plan must be optimized and proven to berobust for a wide range of uncertainties. In the Agbami project, the design ofexperiments, or experimental design (ED) technique, was incorporated tooptimize the well count across a wide range of subsurface uncertainties.
The lack of substantial reservoir-description data is common for manydeepwater discoveries. In the Agbami project, the uncertainty in oil in placewas significant (greater than a factor of 2). This uncertainty was captured ina range of earth (geologic) models. Additional uncertainty variables, includingpermeability, fault seals, and injection conformance, were studiedconcurrently. Multiple well-count development plans (high, mid, and low) weredeveloped and used as a variable in ED. The ED technique allowed multiple wellcounts to be tested quickly against multiple geologic models. With the netpresent value (NPV) calculated for each case, not only was the well count forthe overall highest NPV determined, but discrete testing of each geologic modeldetermined the optimum well count for each model. The process allowed fortesting the robustness of any well count vs. any uncertainty (or set ofuncertainties).
A method was demonstrated quantifying the difference between perfect andimperfect knowledge of the reservoir description (geologic model) as itpertains to well locations.
The Agbami structure is a northwest/southeast-trending four-way closureanticline and is located on the Niger delta front approximately 65 milesoffshore Nigeria in the Gulf of Guinea (see the map in Fig. 1). The structurespans an area of 45,000 acres at spill point and is located in 4,800 ft ofwater. The Agbami No. 1 discovery well was drilled in late 1998. The appraisalprogram was completed in 2001 and included five wells and one sidetrack drilledon the structure, with each encountering oil pay. These five wells and asidetrack penetrated an average of approximately 350 ft of oil.
In this phase (Phase 3) of the development process, the key objectives areto construct a field-development plan and to obtain sanctioning. With drillingdepths of up to 10,000 ft below mudline in 4,800 ft of water, well costs atAgbami will be at the high end of typical deepwater costs. Therefore, animportant optimization parameter in the field development is the total wellcount.
Agbami is typical of many deepwater developments in that the seismic is lessthan perfect and the appraisal well data are sparse relative to the areacoverage. Therefore, subsurface uncertainty is high. In fact, the 5% probableoil in place is more than two times the oil in place at the 95% probability. Asa result, the development process is challenged with determining the optimumwell count for the field development across the wide range of subsurfaceuncertainty.
Several key development decisions were determined in the previous phase(Phase 2) of the development process. These decisions were taken as givens inthis study and are listed as follows:
• The recommended pressure-maintenance scheme and gas-disposition strategyfor the 17 million-year (MY) units is a combination of crestal gas injectionwith peripheral water injection.
• The recommended pressure-maintenance scheme and gas-disposition strategyfor the 14MY/16MY units is crestal gas injection only.
• The facility design capacity recommendations are:
- 250,000 stock-tank bbl per day (STB/D) oil.
- 450,000 thousand cubic ft per day (Mcf/D) gas production.
- 250,000 STB/D water production.
- 450,000 STB/D liquid production.
- 450,000 STB/D water injection.
|File Size||3 MB||Number of Pages||13|
1. Friedmann, F. and Chawathe, A.: "Uncertainty Assessment of ReservoirPerformance Using Experimental Designs," paper CIM 2001-170 presented at the2001 Canadian Intl. Petroleum Conference, Calgary, 29 September-2 October.
2. Damsleth, E., Hage, A., and Volden, R.: "Maximum Information at Minimum Cost:A North Sea Field Development Study With an Experimental Design," JPT(December 1992) 1350.
3. Friedmann, F., Chawathe, A., and Larue, D.K.: "Assessing Uncertainty in ChannelizedReservoirs Using Experimental Designs ," paper SPE 71622 presented at the2001 SPE Annual Technical Conference and Exhibition, New Orleans, 30September-3 October.
4. Mitchell, T.J.: "An Algorithm for the Construction of ‘D-Optimal'Experimental Designs," Technometrics (2000) 42, No. 1, 48.