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 to optimizethe 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 two). This uncertainty was capturedin a range of earth (geologic) models. Additional uncertainty variables, including permeability, 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 quickly tested 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 testingthe robustness of any well count versus 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. Introduction The Agbami structure is a northwest/southeast trending four-way closureanticline, and is located on the Niger delta front approximately 65 milesoff-shore Nigeria in the Gulf of Guinea (see map in Fig. 1). Thestructure spans an area of 45,000 acres at spill point and is located in 4800ft of water. The Agbami No. 1 discovery well was drilled in late 1998. Theappraisal program was completed in 2001 and included five wells and onesidetrack drilled on the structure with each encountering oil pay. These fivewells and a sidetrack 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 4800 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:Recommended pressure maintenance scheme and gas disposition strategy for the17 million-year (MY) units is a combination of crestal gas injection withperipheral water injection.Recommended pressure maintenance scheme and gas disposition strategy for the14MY/16MY units are crestal gas injection only.Facility design capacity recommendations are:250,000 stock-tank bbl per day (STB/D) oil450,000 thousand cubic ft per day (Mcf/D) gas production250,000 STB/D water production450,000 STB/D liquid production450,000 STB/D water injection

This paper describes the methodology for incorporating uncertainties in the optimization of well count for the deepwater Agbami project. The lack of substantial reservoir description data is common in many deepwater discoveries. Therefore, the development plan must be optimized for a wide range of uncertainties. In the Agbami project, the design of experiments or experimental design (ED) technique was incorporated to optimize the well count across a wide range of subsurface uncertainties.Multiple well count development plans (high, mid, and low) were developed and used as a variable in ED. Also, multiple geologic models representing the broad range in uncertainty in oil in place (greater than a factor of two) and in net-to-gross were built and used as a variable. Additional uncertainty variables, including permeability, fault seals, and injection conformance, were studied concurrently. The ED technique allowed multiple well counts to be quickly tested against multiple geologic models. With the net present value (NPV) calculated for each case, not only was the well count for the overall highest NPV determined, but ED allowed discrete testing of each geologic model to determine the optimum well count for each model.A methodology was developed for optimizing well count development plans over a broad range of uncertainties including a range of geologic models, which vary in oil in place and net-to-gross. The process allowed testing the robustness of any well count versus any uncertainty (or set of uncertainties).A method was demonstrated quantifying the difference between perfect and imperfect knowledge of the reservoir description (geologic model) as it pertains to well locations.A total well count of 38 was concluded to be the optimum well count for the Agbami project based on NPV. This well count proved to be robust across the full range of uncertainties tested.

This paper describes a methodology for incorporating uncertainties in the optimization of well count for the deepwater Agbami field development. The lack of substantial reservoir-description data is common in many deepwater discoveries. Therefore, the development plan must be optimized and proven to be robust for a wide range of uncertainties. In the Agbami project, the design of experiments, or experimental design (ED) technique, was incorporated to optimize the well count across a wide range of subsurface uncertainties.The lack of substantial reservoir-description data is common for many deepwater discoveries. In the Agbami project, the uncertainty in oil in place was significant (greater than a factor of 2). This uncertainty was captured in a range of earth (geologic) models. Additional uncertainty variables, including permeability, fault seals, and injection conformance, were studied concurrently. Multiple well-count development plans (high, mid, and low) were developed and used as a variable in ED. The ED technique allowed multiple well counts to be tested quickly against multiple geologic models. With the net present value (NPV) calculated for each case, not only was the well count for the overall highest NPV determined, but discrete testing of each geologic model determined the optimum well count for each model. The process allowed for testing the robustness of any well count vs. any uncertainty (or set of uncertainties).A method was demonstrated quantifying the difference between perfect and imperfect knowledge of the reservoir description (geologic model) as it pertains to well locations.