|Publisher||Society of Petroleum Engineers||Language||English|
|Content Type||Conference Paper|
|Title||Enhancing Drilling Risk & Performance Management Through the Use of Probabilistic Time & Cost Estimating|
|Authors||W.M. Akins, Nexen Inc.; M.P. Abell, The Peak Group; E.M. Diggins, Nexen Inc.|
SPE/IADC Drilling Conference, 23-25 February 2005, Amsterdam, Netherlands
|Copyright||2005. SPE/IADC Drilling Conference|
|1 Drilling and Completions
Not only is risk management critical to the well construction process, but in several jurisdictions around the world, a demonstrated risk management plan is a pre-requisite to doing business. One of the key elements of well risk management is a comprehensive understanding of the inherent risks at each stage of the process, their inter-relationships and the impact on project cycle time and capital cost. This paper describes a probabilistic approach to developing a drilling / completion time and cost model that can be used throughout the well construction life cycle, from project conception through operations and as a tool for project review.
The process starts with the development of a well specific sequence of operational steps. A step by step risk and hazard analysis is undertaken including examination of time and cost variances from relevant offsets, probability of occurrence of events representing both productive and non productive / problem time, and identification of possible contingency steps. The result of this analysis is a time and cost distribution for each step in the operational sequence. These distributions are input to a Monte Carlo simulator and the subsequent output includes a comprehensive time and cost probability distribution, including detailed risk information. Multi-well / campaign models can be developed by connecting a series of individual wells but with the added feature of applying appropriate learning curves and optimization measures.
This process allows for a non-biased, statistically based approach to project scoping, AFE preparation and management of capital spend through the operating phase allowing more informed decision making to occur at critical points in the project. It provides a tool which can be used to enhance senior management / asset team understanding of possible project time and cost outcomes; recognizing the inherent risks and the sensitivity of time and cost to these risks.
Probabilistic cost and time estimating is quickly becoming a common business practice in the well construction industry. It integrates well with probabilistic estimating that is being used in the geological, reserve estimating and price forecasting disciplines of the industry.
Probabilistic estimating provides a non-biased method of forecasting the time and cost of a drilling and completions project. The process also enables the engineer and fellow team members to acknowledge the uncertainties that are a part of well construction and to analyze offset data. It also provides a medium to communicate risked time and cost forecasts of a drilling project.
With a basic knowledge of probability concepts and a comprehensive understanding of well construction, probabilistic estimating is straightforward to implement. Input includes time and cost information, probability of events or problems occurring, and associated consequences for each phase or step in the well construction sequence. With use of a Monte Carlo simulation the output includes a series of cost and time probability distribution curves. The project model can have as much or little definition on drilling/construction phases as the engineer has information. The estimating technique can therefore be used for anything from scoping estimates to very detailed AFE determination, and for updated forecasts during large projects.
This paper will describe the probabilistic estimating process, including the advantages of the process and the limitations that the engineer must be aware of to use the probabilistic techniques properly. The paper will also describe three case studies where probabilistic estimating has been applied.
|File Size||253 KB||9|