Upload
truongtruc
View
222
Download
6
Embed Size (px)
Citation preview
Indicator Facies Modelling
Reservoir management of mature giant fi elds requires the use of modelling tools which can handle a large number of wells and which can rapidly build and update the reservoir model. For giant fi elds, RMSIndicators lets you rapidly build and continuously maintain 3D facies models conditioned to thousands of wells and 3D seismic data. It provides a fast and reliable foundation for reservoir management and decision making.
Fast, Simple Facies Modelling
RMSIndicators is a simple and quick tool for generating facies models. It can run with a minimum of user data, or it can use additional geological information. It can accommodate unlimited amounts of well data. It is straightforward to set up and can use seismic or trends to refi ne the model.
Indicator modelling is a ‘data driven’ technique, i.e. the parameter values are derived from input data. The standard input to the indicator modelling includes the well data, volume fractions and indicator variograms. Variograms give an indication of the variability of the facies in a given direction. Changing the length of the variogram axis controls facies continuity in that direction as seen on the right of the 2 by 2 fi gure.
Simulations run so fast that you can easily fi ne-tune the parameters by hand, either trend selection or variogram values, to get optimal results.
A variety of trends can be used as additional geological input to the modelling. Facies information is taken from the blocked wells and each facies type can follow its own trend. Total facies volume is constrained to equal 1 whilst matching the individual volume fractions.
Seismic data can also be used to constrain the facies distributions. The seismic can either be used as a directly correlated seismic to facies value or as a more subtle probabilistic relationship between seismic attribute and facies type.
IN SUMMARY
• Fast and accurate pixel-based modelling.
• Handles very large numbers of wells quickly and effi ciently.
• More complex models can be produced very easily by integrating a variety of 1D, 2D and 3D geological trends.
• The modelling process is straight forward, with an intuitive interface.
• Seamless links to volumetric calculations, connectivity analysis, full well planning functionality and reservoir simulation carry you smoothly through your workfl ow.
• Conditions to seismic data using a unique indicator co-simulation algorithm.
• Incorporates large numbers of wells quickly and effi ciently.
• Uses the tried and tested Sequential Indicator Simulator algorithm.
ROXAR AS, GAMLE FORUSVEI 17, PO BOX 112, 4065 STAVANGER, NORWAY TELEPHONE +47 51 81 8800 FAX +47 51 81 8801 WWW.ROXAR.COM
Ro
xar
2014
Indicator Facies Modelling
Integrating Geological Trends
RMSIndicators can model any number of facies and can use 1D, 2D and 3D geological trends to constrain the facies distribution.
For example, vertical geological trends are defi ned using vertical proportion curves, such as illustrated left showing proportion curves for two coal-capped upwards-coarsening cycles.
These proportion curves have been used as input for the facies model shown in the cross-section below. Note the continuity of the two coal-rich horizons
Other typical geological trends include maps that are used to constrain the lateral facies distribution, for example, a trend of increasing water depth can control increasing shale fraction or constrain patch reef development.
Seismic Constraints
RMSIndicators provides two methods for using seismic data for modelling facies distribution.
• Conditional probabilities• Indicator co-simulation
The conditional probabilities method provides similar results to using a 3D trend.
The indicator co-simulation method is unique to this module. It is analogous to conventional co-kriging methods, but is applied to facies indicators. This method provides an objective correlation co-effi cient between the seismic and faces data.
Modelling Giant Fields
RMSIndicators is the true “millions of cells, thousands of wells” technology for facies modelling. The fi gure opposite shows an indicator model generated for a mature giant oil fi eld with 25 million cells and 1000 wells.
To learn more please visit www.roxarsoftware.com or emailus on [email protected].
Simulation takes minutes not hours on a standard PC