Abstract
Abstract
In the current climate of large numbers of projects, ever shortening cycle times and increasing field complexity, there is a need for rigourous and agreed Quality Control (QC) guidelines for reviewing static reservoir models.
Within Woodside, the assurance process includes a combination of checklists, guidelines, and milestone reviews at predefined steps in the workflow, the latter being a combination of project framing, 10%, 75%, and fully integrated study reviews.
Although each field is different, and each study has its own objectives, common checkpoints are easily identified and can be grouped in general categories such as: study objectives; geological setting and correlation; input data; structural model; layering and log averaging; and facies and rock property modelling (Fig. 1). There are supplemented by the export to dynamic simulators, and comparisons between upscaled and finely gridded properties, including volumetrics. Most software packages provide some sort of audit trails whilst manipulating the data that makes up the static reservoir model.
A set of pointers with respect to general model QC are given, which are as handy as hints and tips for the beginner, and as reminders (" did you think about...") for the experienced static reservoir modeller.
Introduction
Faced with a 3D static reservoir model, a large number of realisations and scenarios, a set of powerpoints and a deadline, seeing the forest through the trees can be tricky when it comes to checking static reservoir models. Where does one start? What makes one model better than another? It would be good if we could determine this prior to the drillbit entering the ground.
Providing some clear guidelines on reservoir modelling workflows, as well as key milestones at which the status of the modelling study is reviewed, provides a focus for both the geologist and the review panel.
Keep in mind that above all, we are dealing with a model, an "analogy used to help visualise something that cannot be directly observed"1. The static model is an interpretation and simplification of the real world and multiple sensitivities should be run reflecting the uncertainties in the input data. The resulting ranges should be realistic and reflect the maturity of the project. A field with 20 years of production is likely to have a tighter range of in-place volume estimates than a green field. When using a static or dynamic model for well planning, the final check should come from the seismic data, as fault and surface data in the 3 static model is a simplified reflection of the actual interpretation.
And, if it feels wrong, it probably is wrong!
Provide Clear Model Objectives
Prior to commencing any study, there should be a clear understanding of the model objectives. Model geometries and details are dependent on which deliverables are expected. For instance, a static model constructed in a complex structural setting for input into dynamic simulation would have a focus on maintaining cell orthogonality and limiting model size to facilitate dynamic fluid flow (maintenance of geologic detail and model run times after upscaling?). However, in the same setting, a model constructed for detailed well planning should have as good as possible a match to the actual fault locations, independent of cell orthogonality or model size.
Setting up a "Terms of Reference" document when commencing the study can be of great help. This is generally a one page document constructed by the subsurface team, which clearly states the agreed model objectives and deliverables, timing, available data and key uncertainties/issues. A "model framing workshop", whereby the study gets discussed with input from all disciplines, is usually the best forum.