A Method of Integrating Capillary Pressure and Relative Permeability Data Into a Full Field Numerical Simulation of Main Body "B" Reservoir, Elk Hills Field, California

2000 ◽  
Author(s):  
Thomas J. Hampton ◽  
S.P. Singh
Keyword(s):  
Numerical Simulation ◽  
Capillary Pressure ◽  
Relative Permeability ◽  
Main Body ◽  
Full Field ◽  
Permeability Data

A Machine Learning Methodology for Rock-Typing Using Relative Permeability Curves

2021 ◽  
Author(s):  
Carlos Esteban Alfonso ◽  
Frédérique Fournier ◽  
Victor Alcobia
Keyword(s):  
Machine Learning ◽  
Capillary Pressure ◽  
Relative Permeability ◽  
Fractional Flow ◽  
Flow Curves ◽  
Rock Types ◽  
Rock Typing ◽  
Relative Permeability Curves ◽  
Permeability Data

Abstract The determination of the petrophysical rock-types often lacks the inclusion of measured multiphase flow properties as the relative permeability curves. This is either the consequence of a limited number of SCAL relative permeability experiments, or due to the difficulty of linking the relative permeability characteristics to standard rock-types stemming from porosity, permeability and capillary pressure. However, as soon as the number of relative permeability curves is significant, they can be processed under the machine learning methodology stated by this paper. The process leads to an automatic definition of relative permeability based rock-types, from a precise and objective characterization of the curve shapes, which would not be achieved with a manual process. It improves the characterization of petrophysical rock-types, prior to their use in static and dynamic modeling. The machine learning approach analyzes the shapes of curves for their automatic classification. It develops a pattern recognition process combining the use of principal component analysis with a non-supervised clustering scheme. Before this, the set of relative permeability curves are pre-processed (normalization with the integration of irreducible water and residual oil saturations for the SCAL relative permeability samples from an imbibition experiment) and integrated under fractional flow curves. Fractional flow curves proved to be an effective way to unify the relative permeability of the two fluid phases, in a unique curve that characterizes the specific poral efficiency displacement of this rock sample. The methodology has been tested in a real data set from a carbonate reservoir having a significant number of relative permeability curves available for the study, in addition to capillary pressure, porosity and permeability data. The results evidenced the successful grouping of the relative permeability samples, according to their fractional flow curves, which allowed the classification of the rocks from poor to best displacement efficiency. This demonstrates the feasibility of the machine learning process for defining automatically rock-types from relative permeability data. The fractional flow rock-types were compared to rock-types obtained from capillary pressure analysis. The results indicated a lack of correspondence between the two series of rock-types, which testifies the additional information brought by the relative permeability data in a rock-typing study. Our results also expose the importance of having good quality SCAL experiments, with an accurate characterization of the saturation end-points, which are used for the normalization of the curves, and a consistent sampling for both capillary pressure and relative permeability measurements.

scholarly journals Uncertainty span for relative permeability and capillary pressure by varying wettability and spatial flow directions utilizing pore scale modelling

2020 ◽  
Vol 146 ◽  
pp. 01002
Author(s):  
Thomas Ramstad ◽  
Anders Kristoffersen ◽  
Einar Ebeltoft
Keyword(s):  
Continental Shelf ◽  
Pore Structure ◽  
Capillary Pressure ◽  
Relative Permeability ◽  
Phase Flow ◽  
Pore Scale ◽  
Full Field ◽  
Scale Modelling ◽  
Relative Permeability Curves ◽  
Norwegian Continental Shelf

Relative permeability and capillary pressure are key properties within special core analysis and provide crucial information for full field simulation models. These properties are traditionally obtained by multi-phase flow experiments, however pore scale modelling has during the last decade shown to add significant information as well as being less time-consuming to obtain. Pore scale modelling has been performed by using the lattice-Boltzmann method directly on the digital rock models obtained by high resolution micro-CT images on end-trims available when plugs are prepared for traditional SCAL-experiments. These digital rock models map the pore-structure and are used for direct simulations of two-phase flow to relative permeability curves. Various types of wettability conditions are introduced by a wettability map that opens for local variations of wettability on the pore space at the pore level. Focus have been to distribute realistic wettabilities representative for the Norwegian Continental Shelf which is experiencing weakly-wetting conditions and no strong preference neither to water nor oil. Spanning a realistic wettability-map and enabling flow in three directions, a large amount of relative permeability curves is obtained. The resulting relative permeabilities hence estimate the uncertainty of the obtained flow properties on a spatial but specific pore structure with varying, but realistic wettabilities. The obtained relative permeability curves are compared with results obtained by traditional SCAL-analysis on similar core material from the Norwegian Continental Shelf. The results are also compared with the SCAL-model provided for full field simulations for the same field. The results from the pore scale simulations are within the uncertainty span of the SCAL models, mimic the traditional SCAL-experiments and shows that pore scale modelling can provide a time- and cost-effective tool to provide SCAL-models with uncertainties.

Downscaled Capillary Pressure and Relative Permeability of Small Cores for Network Model Validation

2011 ◽  
Vol 4 ◽  
pp. 15-26 ◽  
Author(s):  
O.A. Olafuyi ◽  
Y. Cinar ◽  
M.A. Knackstedt ◽  
W.V. Pinczewski
Keyword(s):  
Experimental Data ◽  
Capillary Pressure ◽  
Relative Permeability ◽  
History Matching ◽  
Homogeneous Model ◽  
Porous Plate ◽  
Network Models ◽  
Micro Ct ◽  
Good Agreement ◽  
Permeability Data

This paper presents the results of drainage capillary pressure and relative permeability measurements made on cores having different bulk volumes ranging from 0.5 to 12 cm3. The aim of the experiments was to provide reliable experimental data which can be used to validate the predictive value of micro-CT based network models for capillary pressure and relative permeability. The micro-CT based network models use realistic networks constructed from the X-ray images of the rock samples having a typical bulk volume of 0.3 cm3. Experimental data for drainage capillary pressure were obtained using the centrifuge technique. The results of the largest cores were verified by the data obtained on the same sample using the porous plate technique. Relative permeability data were obtained by history matching the unsteady state displacement data. Homogeneous model sandstones (Berea and Bentheim) and carbonate (Mt. Gambier) were used in the experiments. Air-brine and oil-brine fluid-systems were used for drainage capillary pressure and relative permeability measurements, respectively. The relative permeability data were compared with those predicted from empirical and geometry based models using capillary pressure data. Good agreement was obtained for the drainage capillary pressure measured on all samples used. The residual saturations obtained from the cores used in the displacement experiments were also in good agreement. The models were found to predict relative permeability of oil and water with varying degrees of success. For water relative permeability, the Pirson model predicts the experimental data successfully while the Corey, Corey-Brooks/Burdine and van Genuchten/Burdine models predict the data of oil relative permeability better than the others. The results demonstrate for the first time that reliable drainage capillary pressure and relative permeability measurements can be made on small model sandstone and carbonate cores of representative scales used in micro-CT-imaging.

Sign in / Sign up

Export Citation Format

Share Document