Tools for decision-making in reservoir risk management

7,512,543

10/328212

December 23, 2002

The present invention discloses a method for performing a stochastic analysis of one or more hydrocarbon reservoir exploitation strategies taking into consideration one or more uncertain parameters. The method optimizes an objective function that considers the gain in value of a reservoir management goal attributable to these exploitation strategies. The methodology may be used to decide whether or not to implement a strategy. Alternatively, it may be used to decide which competing strategy will yield the maximum benefit. In another embodiment of the present invention, the value of information obtained from the installation of additional sensors or new measurements is also considered.

Raghuraman, Bhavani (Wilton, CT, US); Couet, Benoit (Weston, CT, US)

Schlumberger Technology Corporation (Ridgefield, CT, US)

1. A method for managing risk associated with one or more hydrocarbon reservoir exploitation strategies used for determining one or more risk management decisions, the method comprising: a. developing a reservoir model that incorporates a stochastic model of one or more uncertain model parameters; b. identifying one or more goals for optimization; c. identifying said one or more hydrocarbon reservoir exploitation strategies for achieving said one or more goals based on said reservoir model and associated uncertain parameters; d. identifying control variables and constraints associated with each of said one or more hydrocarbon reservoir exploitation strategies; e. identifying a set of equally probable reservoir model scenarios; f. formulating an objective function based on said one or more goals to determine the gain in value attributable to said one or more hydrocarbon reservoir exploitation strategies; and g. optimizing said objective function via at least one processor by using said set of scenarios and said control variables and constraints for each of said one or more hydrocarbon reservoir exploitation strategies to determine the optimum gain in value at a plurality of risk levels; h. creating a risk reward summary to analyze the determined optimum gain in value at said plurality of risk levels corresponding to said one or more hydrocarbon reservoir exploitation strategies that identifies said one or more risk management decision to optimize reservoir production value; and wherein said objective function is defined as F λ =μ−λσ wherein [mathematical expression included] [mathematical expression included] [mathematical expression included] such that, F is said objective function, λ is a risk aversion level, μ is a mean of the gains in value of the goal and the standard deviation, σ is the standard deviation of these gains, N is the set of equally probable scenarios, g i , is the gain for i th scenario; n is the number of discrete points in each of said one or more uncertain parameters; and m is the number of uncertain parameters.

2. The method of claim 1 , wherein said one or more optimized goal is selected from the group consisting of maximizing net present value, maximizing hydrocarbon production, maximizing return on investment, minimizing cost, and maximizing reservoir hydrocarbon drainage.

3. The method of claim 1 , wherein said one or more hydrocarbon reservoir exploitation strategies are selected from the group consisting of installing control technology, drilling additional wells, upgrading surface facilities and performing well workovers.

4. The method of claim 1 , further comprising: i. collecting additional information; j. determining a second set of scenarios based on said additional information; and k. optimizing said objective function based on said second set of scenarios to determine the optimum gain at two or more risk aversion levels.

5. The method of claim 4 , further comprising: l. comparing the gain from (g) to the gain from (k) at two or more common preferred risk aversion levels to determine the value of said additional information.

6. The method of claim 1 , further comprising: i. formulating a second objective function wherein one of said set of scenarios is assumed to be deterministic; j. deterministically optimizing said second objective function to determine the gain attributable to the deterministic treatment of said scenario; k. determining the difference between the gain of (i) and the gain of (g) at a preferred risk level; and l. repeating (i), (j), and (k) for each scenario.

7. The method of claim 6 , further comprising: m. determining the average of the differences in gains obtained in (l) to determine the value of perfect information.

8. The method of claim 1 , further comprising developing a decision table or efficient frontier based on the gain in value of the goal attributable to each of said one or more decision strategies.

9. The method of claim 1 , wherein the objective function accounts for the cost associated with each of said one or more exploitation strategies.

10. The method of claim 1 , further comprising a pricing model.

11. The method of claim 10 , wherein said pricing model is stochastic.

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