ACCESS NUMBER: 30951-17806 

STUDY TITLE: Long-Term Oil and Gas Structure Installation and Removal Forecasting 

in the Gulf of Mexico: A Decision- and Resource-Based Approach

REPORT TITLE: Long-Term Oil and Gas Structure Installation and Removal 

Forecasting in the Gulf of Mexico: A Decision- and Resource-Based Approach

CONTRACT NUMBER: 1435-01-99-CA-30951-17806

SPONSORING OCS REGION: Gulf of Mexico

APPLICABLE PLANNING AREA: Western, Central, Eastern

FISCAL YEAR(S) OF PROJECT FUNDING: 2001, 2002

COMPLETION DATE OF REPORT: May 2004

COST(S): FY 2001: $23,353.43; FY 2002: $36,949.55; CUMMULATIVE PROJECT 

COST: $60,302.98

PROJECT MANAGER: M.J. Kaiser

AFFILIATION: Louisiana State University, Center for Energy Studies

ADDRESS: Energy, Coast & Environment Bldg., Nicholson Extension, Baton Rouge, 

Louisiana 70803 

PRINCIPAL INVESTIGATOR: M.J. Kaiser

KEY WORDS: Gulf of Mexico; offshore; infrastructure; forecasting; outer continental 

shelf

BACKGROUND: The Resource and Economic Analysis (REA) Unit of the U.S. 

Minerals Management Service (MMS) performs infrastructure forecasting in support of 

economic and environmental impact studies in the Gulf of Mexico (GOM). he MMS 

performs a number of forecasts related to GOM infrastructure, including but not 

necessarily limited to, number of exploratory wells, number of delineation wells, number 

of development wells, number of production wells, number of workovers, number of 

structures installed, number of structures removed, number of subsea completions, and 

miles of pipeline. 

Infrastructure forecast is an important input element to decision making at the MMS, 

and because of the scale of activities involved, drilling activity and structure installations 

are closely watched and used as a general guide on resource levels and development 

expectations.
ACCESS NUMBER: 30951-17806 

There is only a limited amount of documentation supporting the REA/MMS forecast 

models, however, and so the first task of this report is to formalize the REA/MMS 

procedure in a quantitative framework. The REA’s platform forecasting procedure is 

analyzed in an effort to add operational insight into the methodology and to provide 

support for refinements to the approach. 

OBJECTIVES: The primary purpose of this paper is three-fold: (1) to document and 

specify the procedures currently employed by the REA in the construction of a platform 

forecast in the Gulf of Mexico, (2) to analyze the assumption set employed in the REA 

forecast and to critique the procedure, and (3) to develop an alternative methodology for 

platform forecasting. 

DESCRIPTION: In this report we developed a methodological framework to forecast 

structure installation and removal rates in the GOM over a 40-year time horizon. The 

framework is based on a model structure developed by the REA of the MMS, but 

departs from the REA approach in terms of the level and type of disaggregation 

employed and the methodology used to construct the forecast.

The number of structures required to develop a field is affected by a number of factors, 

including but not necessarily limited to, the expected size of the field, the number of 

productive wells drilled from each platform, the amount of oil/gas each productive well 

produces, environmental factors such as water depth, soil conditions, and storm 

intensity, capital cost, availability of platforms, and strategic opportunity. The emphasis 

of this paper is to present a decision- and resource-based framework to an 

infrastructure forecast in a manner subject to an explicit set of assumptions.

SIGNIFICANT CONCLUSIONS: Forecasting is a traditional blend of art and science, 

and under conditions of unknown uncertainty, it is desirable to maintain a consistent, 

simplistic, and structured methodology that explicitly enumerates the assumption set 

and does not mix scenario assumptions or introduce additional uncertainty external to 

the modeling framework. Infrastructure forecast deserve careful attention to detail and 

deliberate methodological development, and should be performed on a regular basis to 

develop a better understanding of the system drivers and limitations of the analysis. 

The REA/MMS has done a good job in developing and promulgating the GOM platform 

forecast, and as discussed in this paper, the main criticism is aimed at refining the 

methodology, explicitly enumerating the assumption set, and ensuring that the solution 

methodology is consistent within the model framework. A set of recommendations was 

described addressing these concerns. 

The methodology suggested in this paper is an adaptation of the REA approach that 

formalizes the framework in a consistent manner, modifies some key elements of the 

methodology, and incorporates decision parameters within the procedure. A formal 

development of the proposed methodology was presented and compared with the REA 

approach. Comparison of the two approaches illustrates that the REA and CES 

procedures represent a trade-off between the preferences of the user and the 
ACCESS NUMBER: 30951-17806 

assumptions of the methodology. It is suggested that the two procedures evolve into an 

automated “best practice” model. 

STUDY RESULTS: The task of this paper was to develop a unified approach to 

infrastructure forecasting in the Gulf of Mexico and to forecast the number of structures 

expected to be installed and removed per water depth and planning area category over 

a long-term horizon. The consistency of the methodology, the application of a discrete 

assumption set, and the inclusion of a decision-oriented framework within the model 

represent the central tenants of the procedure. The model results should be interpreted 

as a first-order approximation to a very complex reality, and as such, should serve as a 

guide to infrastructure forecast requirements. 

The need to properly select and specify aggregation categories is a critical ingredient in 

any forecast strategy, and the decomposition of the data into appropriate categories is 

an important aspect of pre-processing to ensure that the methodology is consistent and 

the procedure is sufficiently structured. No matter how fine the infrastructure data is 

decomposed and disaggregated within various categories, however, forecasting 

procedures rely upon other forecast and judgmental adjustments which can differ 

enormously in scope and magnitude. The uncertainty in these adjustments should be 

understood and clearly communicated to the user group. One of the principal tasks of 

this paper was to identify this uncertainty and to employ decision-oriented parameters 

as a means to explore the sensitivity of the model results. 

The infrastructure forecast developed is a decision- and resource-based model similar 

to the methodology employed by the MMS but more broadly defined and executed 

within an analytic and computational framework. The output of the model is derived 

from the forecast of a supply curve and an infrastructure requirement ratio. A decisionoriented framework is employed to construct the supply curve which incorporates the 

beliefs of the user and variables such as technology change. The results of the forecast 

were presented under various assumptions on recovery rate and development timing. 

STUDY PRODUCTS: Kaiser, M.J., D.V. Mesyanzhinov, and A.G. Pulsipher. 2004. 

Long-term oil and gas structure installation and removal forecasting in the Gulf of 

Mexico: A decision- and resource-based approach. U.S. Department of the Interior, 

Minerals Management Service, Gulf of Mexico OCS Region, New Orleans, La. OCS 

Study MMS 2004-009. 62 pp.