Abstract This paper describes the final part of a joint integrated seismic characterization project on a major carbonate reservoir of an onshore field, in the Middle East. The reservoir geomodel building captures well information, the 3D structural and seismic information obtained through seismic interpretation and impedance inversion.
The aim of this seismic characterization project was to improve the reservoir management by optimizing well placement, geosteering and geomodeling. These goals imply to derive the lateral and vertical heterogeneities in the reservoir and to characterize the reservoir porosity variations including the location and volume of some non-reservoir ‘dense’ bodies embedded in it.
Stochastic inversion was carried out with in house software Geolnv™. The stochastic approach enables us to compute a family of equiprobable impedance inversion volumes that are both constrained by seismic and well data. For this inversion, a family of 100 realizations was computed using 22 input wells and a mean wavelet that extracted on 6 high quality wells. Each inversion contained 785 000 traces.
The mean and the standard deviation (Sigma) are computed from the 100 realizations and analyzed. Next, the probability of a cell to be higher than a described threshold is computed from the inversion family. From these probabilities, the locations of the high impedance or low density zones in the reservoir can be delineated and their volume calculated.
Results are entered into the geomodel built in time at a 1 ms sampling. The 38 Million cells impedance cubes are read in the same Stratigraphy time grid, in proportional layers of the reservoir formation and then read into depth into the geomodel.
The depth model is then converted into porosity estimated stochastically using 100 wells present in the geomodel. The models corresponding to mean impedance cubes, mean plus and minus a proportion of Sigma were prepared for an uncertainty approach. The porosity models were produced with different methods; either deterministic or stochastic, constrained at the wells and then pore volumes computed for these different options.
Introduction The overall aim of this part of the study is to assist reservoir management, by attaining the objectives listed below:To create an operation workflow to seamlessly integrate GeoInv™ (a geostatistical inversion tool that has been developed by TOTAL'S Geoscience Research Centre) results in time into a 3D geomodel in depth (IRAP)
In the 3D geomodel, determine the porosity from the Acoustic Impedance and well logs.
This integration study is limited to the Southern area of the field (Fig. 1).
Generally speaking, the goal was to take the 3 impedance cubes from GeoInv™ : the mean, mean + a S and - a S where S sigma is the standard deviation, import them into IRAP and then compute the porosity from well log data using the acoustic impedance as a trend for the different models.
These objectives were successfully achieved, after some trial and error mainly due to file formats and software limitations. However, the workflow is not a simple "push-button" method and requires data QC at each step.