Optimization of Offshore Field Development To Minimize Investment
- T.T. Grimmett (Texas A and M U.) | R.A. Startzman (Texas A and M U.)
- Document ID
- Society of Petroleum Engineers
- SPE Drilling Engineering
- Publication Date
- December 1988
- Document Type
- Journal Paper
- 403 - 410
- 1988. Society of Petroleum Engineers
- 1.6.6 Directional Drilling, 2 Well Completion, 4.6 Natural Gas, 1.10 Drilling Equipment, 1.6 Drilling Operations, 7.1.10 Field Economic Analysis, 1.3.2 Subsea Wellheads, 4.2 Pipelines, Flowlines and Risers, 4.5.2 Platform Design, 7.1.9 Project Economic Analysis
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Summary. offshore oil and gas development is identified with high investment. Considerable incentive therefore exists To reduce investment and to improve field profitability. A computational method has been developed to optimize field development and to minimize investment.
Investment can be reduced through an optimal choice and arrangement of production facilities. The selection, size, and location of major facilities-such as platforms, templates, or subsea manifolds-heavily affect capital investment. The allocation of field wells to these facilities affects drilling and completion costs. An extremely large number of feasible development options exist that may result in a wide range of economic outcomes. Choosing the option that minimizes investment can be a major computational problem.
The solution of extremely large economic problems of this nature has not been reported previously. An integer mathematical programming computational tool, using a method called "zero-one implicit enumeration," was developed for modeling and solving this problem. This technique allows for efficient problem solution on a computer.
A model of an example field development was formulated. This model contains a mathematical function representing the investment to be minimized and includes design restrictions inherent to the development project. The model contained nearly combinations of development options. The application of a branch-and-bound algorithm allowed selection of an optimum development in a relatively short time on a computer.
An offshore development program may contain a complex mix of drilling and facilities construction options. Drilling options include wells drilled directionally or vertically from fixed or floating facilties. Facilities construction options can include selection of sub-sea templates, manifolds, and platforms. The selection and physical arrangement of these facilities can critically affect project economics.
The drilling and completion costs of directional wells is a function of vertical depth and horizontal deviation. Costs of platforms, templates, and manifolds are functions of type, location, and the number of wells connected to each facility. Also, investments in subsea flowlines connecting various facilities are functions of location and line size.
Physical restrictions on facilities locations-e.g., mud slide areas or shipping lanes-reduce the number of feasible development options. Safety and other policy restrictions may also limit options. In addition, limits on horizontal well deviation reduce the number of wells that can be drilled from a single location.
The many combinations of options and restrictions indicate that mathematical programming methods may be useful to determine an optimal mix that will minimize investment. Without such a rigorous approach, operators are reduced to studying only a few realistic scenarios with no guarantee that the absolute minimum- investment mix of options has been reached. We propose that the investment minimization problem be cast in a mathematical programming framework. The framework should be flexible enough to accommodate all known offshore physical cost and design factors.
Although the operations research and management science literature has introduced a large number of successful mathematical programming methods, relatively little attention has been paid to the economically important area of offshore oil and gas development.
In 1969, Devine and Lesso presented a method to find the number, size, and location of platforms to minimize offshore investment. They suggested first specifying the number of platforms, then solving the sizing and location problem using the "alternate-location allocation" algorithm. Because the number of platforms in a field may be limited and small, the problem can be solved several times for different numbers of platforms. A solution from the alternatelocation allocation algorithm depends on the initial allocation of wells to platforms. The procedure must be repeated in a trial-and- error fashion to ensure selection of the minimum cost configuration.
In 1973, Frair and Devine extended this concept to include the time-staging of wells with assumed production schedules. The problem was then designed to maximize net present value (NPV). The authors suggested that nonlinear, mixed-integer programming be used to solve the problem. Because a cost-effective mixed-integer programming package was unavailable at the time for a moderately sized problem, Frair and Devine suggested that the problem be segmented (decomposed) into two main independent subproblems. One subproblem would handle platform location and the allocation of wells. The other subproblem would schedule development drilling. Unfortunately, as a problem of this nature is extended to handle other production facilities in addition to platforms. the decomposition approach will become increasingly unwieldy and subject to suboptimization.
Lilien studied a problem involving minimizing drilling costs. The nonlinear optimization procedure that was proposed selected the number of bits and footage drilled between bit changes to minimize the sum of drilling (including tripping) and bit costs. Costa investigated the problems of Lilien and of Devine and Lesso and a dual-completion two-reservoir problem. He suggested and formulated several alternative approaches to these problems, including a dynamic programming approach to the problem of Lilien.
Because development plans may change with time as new wells are drilled, the entire offshore investment minimization problem could be cast in terms of a dynamic programming (nine-staged) problem. Durrer and Slater have stated that this approach eliminates having to know all well locations before the start of development work, as required by Devine, Frair, and Lesso.
However, in actual offshore planning, work must begin on platform and other facilities construction at an early stage because of long construction lead times. Mistakes in estimating reservoir quality and boundaries may (and often do) become apparent later. Decisions are always made on imperfect information. This is a natural part of the risk in oil and gas development.
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