Geostatistics has been used to improve the reservoir characterization process for the last fifteen years. This article briefly discusses the accomplishments so far, and discusses the future challenges.
Reservoir characterization is a process of integrating various qualities and quantities of data in a consistent manner to describe reservoir properties of interest at inter well locations. Appropriate weight should be given to the quality and the scale of the data, and data should be integrated such that we can predict the future performance of the reservoir. Our goal in reservoir characterization is not to seek the truth about reservoir; instead, to build a reasonable reservoir model which is adequate to predict the future performance. The model will not only be dependent on the type of data available, but it should also be dependent on the type of flow process we are trying to simulate. More complex the flow process (e.g., CO2 process), more detailed will be the reservoir description; more simple the flow process (e.g., dry gas reservoir), simpler will be the reservoir description.
Reservoir description process is not new; since the first oil discovery, oil companies have used all the available data techniques to describe the reservoir so that the next well to be drilled will be based on more information than a prior well. However, several changes have taken place in the last fifteen years. Some of these changes are listed below:
We have better and faster computers so that we can handle more complex algorithms, and can generate detailed reservoir descriptions in a reasonable amount of time. PC revolution has brought the computer power to small players, making it feasible for even small operators to harness the power of detailed reservoir description processes.
Several new algorithms have been developed in the last fifteen years which allow integration of various types of data in an easier fashion.
As the reservoirs get more mature, there is more need to describe the reservoir in more details so as to locate the remaining hydrocarbons.
There is an increasing recognition that representation of heterogeneities is as important as representing correct physics in the flow simulators.
Geostatistics is based on a simple principle that geological data are spatially correlated. This spatial correlation is quantified and is utlilized to determine the weights assigned to the nearby samples to estimate the value at the unsampled location. Geostatistics has been used in mining industry for several years. Its use in petroleum industry is of relatively recent origin. To address the unique problems encountered in petroleum engineering, several new geostastical techniques have been established in the past several years. Some of these techniques are discussed below.
Several papers have been published in the literature to demonstrate the application of geostatistics. It will be impossible to list all the successes of various geostatistical techniques. Instead, an effort is made to highlight the accomplishments which are widely used and embraced by oil companies.