The importance of optimal geological zonation and choice of rock parameters in dynamic reservoir simulation: a case study for the Laminaria field

2018 ◽  
Vol 58 (2) ◽  
pp. 683 ◽  
Author(s):  
Peter Behrenbruch ◽  
Tuan G. Hoang ◽  
Khang D. Bui ◽  
Minh Triet Do Huu ◽  
Tony Kennaird
Keyword(s):  
Capillary Pressure ◽  
Relative Permeability ◽  
Reservoir Simulation ◽  
History Matching ◽  
Laboratory Data ◽  
Analysis Data ◽  
Scale Model ◽  
Core Analysis ◽  
Relative Permeability Curves ◽  
Rock Parameters

The Laminaria field, located offshore in the Timor Sea, is one of Australia’s premier oil developments operated for many years by Woodside Energy Ltd. First production was achieved in 1999 using a state-of-the-art floating production storage and offloading vessel, the largest deployed in Australian waters. As is typical, dynamic reservoir simulation was used to predict reservoir performance and forecast production and ultimate recovery. Initial models, using special core analysis (SCAL) laboratory data and pseudos, covered a range of approaches, field and conceptual models. Initial coarser models also used straight-line relative permeability curves. These models were later refined during history matching. The success of simulation studies depends critically on optimal gridding, particularly vertical definition. An objective of the study presented is to demonstrate the importance of optimal and detailed vertical zonation using Routine Core Analysis data and a range of Hydraulic Flow Zone Unit models. In this regard, the performance of a fine-scale model is compared with three alternative, more traditional and coarse models. Secondly the choice of SCAL rock parameters may also have a significant impact, particularly relative permeability. This paper discusses the use of the more recently developed Carman-Kozeny based SCAL models, the Modified Carman-Kozeny Purcell (MCKP) model for capillary pressure and the 2-phase Modified Carman-Kozeny (2p-MCK) model for relative permeability. These models compare favourably with industry standard approaches, the use of Leverett J-functions for capillary pressure and the Modified Brooks-Corey model for relative permeability. The benefit of the MCK-based models is that they have better functionality and far better adherence to actual laboratory data.

scholarly journals Insights, Trends and Challenges Associated with Measuring Coal Relative Permeability

2019 ◽  
Vol 89 ◽  
pp. 01004
Author(s):  
Dylan Shaw ◽  
Peyman Mostaghimi ◽  
Furqan Hussain ◽  
Ryan T. Armstrong
Keyword(s):  
Relative Permeability ◽  
Effective Stress ◽  
History Matching ◽  
Water Saturation ◽  
Laboratory Data ◽  
Stress Regime ◽  
Cross Point ◽  
Irreducible Water Saturation ◽  
Relative Permeability Curves ◽  
The Right

Due to the poroelasticity of coal, both porosity and permeability change over the life of the field as pore pressure decreases and effective stress increases. The relative permeability also changes as the effective stress regime shifts from one state to another. This paper examines coal relative permeability trends for changes in effective stress. The unsteady-state technique was used to determine experimental relativepermeability curves, which were then corrected for capillary-end effect through history matching. A modified Brooks-Corey correlation was sufficient for generating relative permeability curves and was successfully used to history match the laboratory data. Analysis of the corrected curves indicate that as effective stress increases, gas relative permeability increases, irreducible water saturation increases and the relative permeability cross-point shifts to the right.

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.

Use of Transient Data To Calculate Absolute Permeability and Average Fluid Saturations

2010 ◽  
Vol 13 (02) ◽  
pp. 306-312 ◽  
Author(s):  
Medhat M. Kamal ◽  
Yan Pan
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Surface Flow ◽  
Absolute Permeability ◽  
Phase Flow ◽  
Simulation Studies ◽  
Flow Rates ◽  
Reservoir Performance ◽  
Transient Data ◽  
Relative Permeability Curves

Summary A new well-testing-analysis method is presented. The method allows for calculating the absolute permeability of the formation in the area influenced by the test and the average saturations in this area. Traditional pressure-transient-analysis methods have been developed and are completely adequate for single-phase flow in the reservoir. The proposed method is not intended for these conditions. The method applies to two-phase flow in the reservoir (oil and water or oil and gas). Future expansion to three-phase flow is possible. Current analysis methods yield only the effective permeability for the dominant flowing phase and the "total mobility" of all phases. The new method uses the surface-flow rates and fluid properties of the flowing phases and the same relative permeability relations used in characterizing the reservoir and predicting its future performance. The method has been verified by comparing the results from analyzing several synthetic tests that were produced by a numerical simulator with the input values. Use of the method with field data is also described. The new method could be applied wherever values of absolute permeability or fluid saturations are used in predicting well and reservoir performance. Probably, the major impact would be in reservoir simulation studies in which the need to transform welltesting permeability to simulator input values is eliminated and additional parameters (fluids saturations) become available to help history match the reservoir performance. This work will also help in predicting well flow rates and in situations in which absolute permeability changes with time (e.g., from compaction). Results showed that the values of absolute permeability in water/oil cases could be reproduced within 3% of the correct values and within 5% of the correct values in gas/oil cases. Errors in calculating the fluid saturations were even lower. One of the main advantages of this method is that the relative permeability curves used in calculating the absolute permeability and average saturations, and later on in numerical reservoir simulation studies, are the same, ensuring a consistent process. The proposed method does not address the question of which set of relative permeability curves should be used. This question should be answered by the engineer performing the reservoir engineering/simulation study. The proposed method mainly is meant to provide consistent results for predicting the reservoir performance using whatever relative permeability relations that are being used in the reservoir simulation model. The method does not induce any additional errors in determining the average saturation or absolute permeability over what may result from using these specific relative permeability curves in the reservoir simulation study. The impact of this study will be to expand the use of information already contained in transient data and surface flow rates of all phases. The results will provide engineers with additional parameters to improve and speed up history matching and the prediction of well and reservoir performances in just about all studies.

Lowering the phase-trap damage in tight-gas reservoirs by using interfacial tension (IFT) reducers

2013 ◽  
Vol 53 (1) ◽  
pp. 363
Author(s):  
Yangfan Lu ◽  
Hassan Bahrami ◽  
Mofazzal Hossain ◽  
Ahmad Jamili ◽  
Arshad Ahmed ◽  
...  
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Water Saturation ◽  
Tight Gas ◽  
Gas Reservoirs ◽  
Tight Gas Reservoirs ◽  
Water Based ◽  
Tight Formations ◽  
Tight Reservoirs ◽  
Relative Permeability Curves

Tight-gas reservoirs have low permeability and significant damage. When drilling the tight formations, wellbore liquid invades the formation and increases water saturation of the near wellbore area and significantly deceases permeability of this area. Because of the invasion, the permeability of the invasion zone near the wellbore in tight-gas formations significantly decreases. This damage is mainly controlled by wettability and capillary pressure (Pc). One of the methods to improve productivity of tight-gas reservoirs is to reduce IFT between formation gas and invaded water to remove phase trapping. The invasion of wellbore liquid into tight formations can damage permeability controlled by Pc and relative permeability curves. In the case of drilling by using a water-based mud, tight formations are sensitive to the invasion damage due to the high-critical water saturation and capillary pressures. Reducing the Pc is an effective way to increase the well productivity. Using the IFT reducers, Pc effect is reduced and trapped phase can be recovered; therefore, productivity of the TGS reservoirs can be increased significantly. This study focuses on reducing phase-trapping damage in tight reservoirs by using reservoir simulation to examine the methods, such use of IFT reducers in water-based-drilled tight formations that can reduce Pc effect. The Pc and relative permeability curves are corrected based on the reduced IFT; they are then input to the reservoir simulation model to quantitatively understand how IFT reducers can help improve productivity of tight reservoirs.

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