Oil companies need to assess new fields or prospects where very little hard data exists. Based on seismic data, analysts can estimate the probability distribution of the reserve size. With little actual data available, companies still must quantify and optimize the Net Present Value (NPV) of this asset. The number of wells to drill, the size of the processing facility, and the plateau rate of the field must all be optimized. The following example is a custom application written by Palisade Custom Development using @RISK’s XDK in Excel.
This analysis can be simplified by representing the production profile by three phases:
- Build up: The period when wells are drilled to gain enough production to fill the facilities.
- Plateau: After reaching the desired production rate (plateau), the period when production is continued at that rate as long as the reservoir pressure is constant and until a certain fraction of the reserves is produced. In the early stages of development, this fraction can only be estimated, and production above a certain rate influences plateau duration.
- Decline: The period when production rates, P, decline by the same proportion in each time step, leading to an exponential function: P(t) = P(0) exp(-c*t), where t is the time since the plateau phase began and c is some constant.
With only estimates for the total Stock Tank Oil Initially In Place (STOIIP = reserve size) and percent recovery amounts, the objective is to select a production rate, a facility size, and well numbers to maximize some financial measure. In this example, the measure used is the P10 of the NPV distribution. In other words, the oil company wants to optimize an NPV value which they are 90% confident of achieving or exceeding.
As described, the problem is neither trivial nor overly complex. A high plateau rate doesn’t lose any reserves, but it does increase costs with extra wells and larger facilities. However, facility costs per unit decrease with a larger throughput, so choosing the largest allowed rate and selecting a facility and number of wells to match might be appropriate.
This is just one example of how Palisade can provide personalized risk solutions for your business needs. We offer custom software development services as well as software developer kits to create your own applications integrating @RISK, RISKOptimizer, and other Palisade technology. We can also help automate Palisade software using VBA in Microsoft Excel or Project.
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Free Webcast this Thursday: "Exploring Oil & Gas Applications of @RISK and the DecisionTools Suite" – See more at: https://blog.palisade.com/blog/risk-and-decision-analysis-news/free-webcast-this-thursday-exploring-oil-and-gas-applications-of-risk-and-the-decisiontools-suite#sthash.sev3ym2s.dpuf