Field Development Plan by Optioneering Process Sensitive to Reservoir and Operational Constraints and Uncertainties

Abstract

A revised Field Development Plan (FDP) for Betty Field was prepared based on a process that was simultaneously sensitive to reservoir and operational constraints and uncertainties. This so called "Optioneering" process was an iterative, multidisciplinary optimization task that generated an action plan based on multiple options developed by reservoir, production, drilling and facilities engineering and ranked by economics. The process specifically involved first generating a series of unconstrained production options, which then considered drilling reach and anti-collision limitations, and finally had the appropriate facilities and regional evacuation constraints imposed. To achieve this, history-matched numerical reservoir models were first run within the framework of an infill well-location optimization software package. Then, drilling constraints were imposed with drilling planning software and facility constraints were included via a surface coupling system for multiple-reservoir models. Uncertainties in the reservoir characteristics and in the facilities/evacuation schemes were addressed by quantifying their impact on the ultimate recovery efficiency. During the optioneering exercise, more than 100 unconstrained options for seventeen stacked reservoirs were identified from the perspective of infill drilling, pressure maintenance by gas injection and/or waterflooding, high pressure gas production, horizontal wells and production enhancement work. Based on typical costs and economic rank, the high potential unconstrained production options for each reservoir were determined. After imposing the drilling constraints, all reservoirs were then coupled to account for surface facility constraints. In the final analysis, five sidetrack wells reaching 12 new drainage points (NDP) over 10 reservoirs were designed. This infill drilling scheme will increase current reserves by 128%. Furthermore, a gas injection scheme identified as the optimum plan for A6.0 reservoir will increase current reserves by 28%. Field wide recovery factor will be improved by 9%. Introduction Oilfield development and management decisions are usually made under high risk and uncertain conditions that stem from both surface and subsurface unknowns. The optimized field and reservoir management can be achieved through successful uncertainty management. Uncertainty management has two main aspects: minimizing uncertainty followed by estimating risks from remaining uncertainty. Minimizing uncertainty reduces the risks and improves project economics. Uncertainty can be managed by integrating multi-discipline multi-scale data and utilizing 3-D numerical models as predictive tools. Then, estimating risk from the remaining uncertainty allows us to make informed investment decisions. An ideal FDP should not only include recommendations for an optimum development strategy with its implementation plan, but the estimated risks involved in executing the proposed plan. So the ideal plan would have two parts: optimization and risk assessment, which are also interrelated. However, ranking and screening of options for the plan should be done only after taking the risk factors into account. Therefore, an iterative procedure is required which generally converges after several iterations. Converging to an optimized field plan involves identifying the best suited activity, and then designing that activity to its optimum level. Final risk exposures for the selected activity are estimated and reported, whereby potentially high risk aspects are known to the implementation team and accounted for in economic evaluations. Generating options, and screening them to achieve an optimum FDP with its associated risks requires an optioneering process.

The Use of Mathematical Programming to Determine Optimal Production and Drilling Schedule in an Offshore Oil Field, A Case Study From the Barents Sea

“…A crucial step before considering the uncertainty handling mechanism is to improve the efficiency of the optimization method. Finally, an ideal field development plan should not only include recommendations for an optimum development strategy with an implementation plan for a given scenario, but also provide good estimates regarding the risks involved in executing the proposed plan [31].…”