Abstract
Multivariate probabilistic pattern recognition methods such as discriminant analysis are powerful for interpreting seismic data in terms of reservoir properties. They consist of calibrating a mathematical relationship between local seismic information (seismic voxels or pieces of traces extracted at a reservoir level), characterised by a set of measurements, named seismic attributes, and a pre-defined set of classes, named seismic facies. In the context of seismic reservoir characterisation, this methodology provides a map or a volume of most probable facies, which describes the main reservoir heterogeneities. During the last decade, another application of this technique to the interpretation of 4D seismic data has also emerged: in this case, each seismic vintage is interpreted in terms of seismic facies, and differences in the interpretation of one vintage from another are correlated a posteriori to production effects such as fluid substitutions or pressure variations. As a probabilistic method, discriminant analysis allows the evaluation, at least partly, of uncertainty associated with seismic facies interpretation, and assignment probabilities computed by the methodology are a measure of the confidence of the interpretation. However, this uncertainty evaluation is only partial. In this paper, we will describe three other aspects of uncertainties, which are not correctly handled by classical discriminant analysis. The first aspect is linked with measurement errors. To propagate this type of error in seismic facies analysis, we have had to develop a methodology based on a combination of discriminant analysis and interval analysis. The other two aspects of uncertainty are linked with the interpretation of seismic facies. Due to the difference in resolution between seismic data in real reservoir heterogeneities, one seismic facies may correspond to several different fine-scale geological or dynamic scenarios. We will show in this paper how pseudo-well methodology, as well as seismic modelling (in the context of 4D interpretation) can help address this issue.
Highlights
Among the different techniques that have been developed for seismic reservoir characterisation and monitoring, seismic facies analysis plays a particular role
A interesting aspect of seismic facies is that this methodology allows one to answer jointly two types of questions, through the use of supervised and unsupervised methodologies: – Supervised methodology aims at evaluating how similar seismic objects are to pre-defined groups, or training classes, which are formed of collections of already interpreted objects
These objects may be extracted close to cored well locations, where we have a direct access to local reservoir heterogeneity. – Unsupervised methodology aims at detecting groups of objects with similar characteristics among all the seismic objects
Summary
Among the different techniques that have been developed for seismic reservoir characterisation and monitoring, seismic facies analysis plays a particular role This methodology is based on pattern recognition techniques dedicated to interpreting seismic objects extracted from seismic data (multi-attribute voxels, or pieces of traces at a reservoir level) and described by a number of characteristics, or seismic attributes in a set of classes (Dumay and Fournier, 1988). A interesting aspect of seismic facies is that this methodology allows one to answer jointly two types of questions, through the use of supervised and unsupervised methodologies: – Supervised methodology aims at evaluating how similar seismic objects are to pre-defined groups, or training classes, which are formed of collections of already interpreted objects These objects may be extracted close to cored well locations, where we have a direct access to local reservoir heterogeneity. The last part of the paper, about fine-scale heterogeneity evaluation, is developed on the synthetic case study
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
