In today's climate of oil sand development many operators are interested in assessing the development potential of their leases with a view to some form of commercial development.
Often there is a relative lack of geological data compared to the leases currently under commercial development. Furthermore, the expenditure and time required to increase the amount of data, and to build 3D geological models, is not warranted without some strong indication of development potential. There is also a strong desire to gain some assessment of the risk associated with any performance forecast.
The authors have developed an approach to lease evaluation and performance forecasting which maximizes the use of existing geological data and incorporates a stochastic methodology that allows the assessment of risk associated with lease development through the provision of Probability Density Functions for performance related parameters such as CSOR and recovery factor.
The approach has been used successfully with several operators over the past year and incorporated in submissions to the AEUB for development projects.
The intent is to provide a number of papers, of which this is the first, that describe the approach in detail.
The purpose of the current paper is to provide an overview of the approach as applied to actual field situations. Whereas the current paper addresses the use of the methodology for oil sand leases with a view to using the SAGD process, the approach can be applied without restriction to any form of lease or process
Many operators of oil sands leases are faced with the need to evaluate the development potential of their leases, and possibly file an application for development with the AEUB, without detailed geological information – even in the immediate area chosen for the first development if such is even known.
Constructing a good/effective 3D geological model requires good data frequency in space – logs, cores – and time. If the raw data are not available then considerable additional time and expense must be expended to develop the necessary detail before the geological modeling can begin.
In this case, what is desired is a method of using what geological data do exist in the most effective manner to provide an assessment of the performance of the chosen recovery process (es) in different locations, and also to provide risk sensitivity to performance in the location eventually chosen for first development.
This performance assessment should be good enough to warrant confidence in filing a development application to regulatory authorities and also supportive of the expenditures required to develop additional localized geological information to support the development.
The method described here has been used in several cases to evaluate small areas (1 – 2 sections at a time) of oil sands leases using on average one well per section of detailed geological information.
The technique is based on the use of a single vertical well description for each evaluation model. The evaluation model is a reservoir flow simulation data set for a thermal reservoir simulator.
