Integration of Multiple Oil and Gas Data Sources for Use in Forecasting Future Rates of Discovery of Oil and Gas
DREW, LAWRENCE J., U.S. Geological Survey, Reston, VA, and JOHN H. SCHUENEMEYER, University of Delaware, Newark, DE
Discovery process models are commonly used to forecast both the amount of crude oil and natural gas remaining to be found and the rate at which they are going to be discovered in the future. These models require accurate estimates of the sizes of past discoveries and their interarrival times in the historical time series of wildcat wells drilled.
The major source of well data is a commercial data base, the Petroleum Information Well History Control file, which consists of approximately two million records. Wells should be designated as successful or unsuccessful and as either discovery or development. Discovery wells far too often are not uniquely designated. In these situations, the discovery well has to be determined from other data. Several labor-intensive steps are required in order to convert the raw well and field information into data useful for forecasting.
An additional problem is to determine the size of each field that has been discovered. Estimates of the ultimate productivity of fields are often contradictory, inaccurate, or in the case of many of the smaller fields, nonexistent. The correction of all these problems involves the examination of dictionaries such as the International Oil and Gas Scouts yearbooks. In the reconciliation process, field codes, cumulative productions, formation names, depths, and numbers of well completions are used.
The sizes of the final, conditioned data sets vary from one thousand to one hundred thousand wells and from one hundred to several thousand fields. At present, the method we have devised, which involves much statistical graphical analysis and hand labor, may be the only practical method for creating input data of acceptable quality for use in discovery process modeling.
AAPG Search and Discovery Article #91004 © 1991 AAPG Annual Convention Dallas, Texas, April 7-10, 1991 (2009)