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Robustness of disaggregate oil and gas discovery forecasting models

Marine and Petroleum Geology

By:
and
DOI: 10.1016/0264-8172(89)90006-8

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Abstract

The trend in forecasting oil and gas discoveries has been to develop and use models that allow forecasts of the size distribution of future discoveries. From such forecasts, exploration and development costs can more readily be computed. Two classes of these forecasting models are the Arps-Roberts type models and the 'creaming method' models. This paper examines the robustness of the forecasts made by these models when the historical data on which the models are based have been subject to economic upheavals or when historical discovery data are aggregated from areas having widely differing economic structures. Model performance is examined in the context of forecasting discoveries for offshore Texas State and Federal areas. The analysis shows how the model forecasts are limited by information contained in the historical discovery data. Because the Arps-Roberts type models require more regularity in discovery sequence than the creaming models, prior information had to be introduced into the Arps-Roberts models to accommodate the influence of economic changes. The creaming methods captured the overall decline in discovery size but did not easily allow introduction of exogenous information to compensate for incomplete historical data. Moreover, the predictive log normal distribution associated with the creaming model methods appears to understate the importance of the potential contribution of small fields. ?? 1989.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Robustness of disaggregate oil and gas discovery forecasting models
Series title:
Marine and Petroleum Geology
DOI:
10.1016/0264-8172(89)90006-8
Volume
6
Issue:
3
Year Published:
1989
Language:
English
Publisher:
Elsevier
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Marine and Petroleum Geology
First page:
270
Last page:
276
Number of Pages:
7