Rock Typing as an Effective Tool for Permeability and Water-Saturation Modeling: A Case Study in a Clastic Reservoir in the Oriente Basin

2007 ◽  
Vol 10 (06) ◽  
pp. 730-739 ◽  
Author(s):  
Genliang Guo ◽  
Marlon A. Diaz ◽  
Francisco Jose Paz ◽  
Joe Smalley ◽  
Eric A. Waninger
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Water Saturation ◽  
Rock Type ◽  
Permeability Model ◽  
Initial Water ◽  
Rock Types ◽  
Rock Typing ◽  
Relative Permeability Curves ◽  
Clastic Reservoirs

Summary In clastic reservoirs in the Oriente basin, South America, the rock-quality index (RQI) and flow-zone indicator (FZI) have proved to be effective techniques for rock-type classifications. It has long been recognized that excellent permeability/porosity relationships can be obtained once the conventional core data are grouped according to their rock types. Furthermore, it was also observed from this study that the capillary pressure curves, as well as the relative permeability curves, show close relationships with the defined rock types in the basin. These results lead us to believe that if the rock type is defined properly, then a realistic permeability model, a unique set of relative permeability curves, and a consistent J function can be developed for a given rock type. The primary purpose of this paper is to demonstrate the procedure for implementing this technique in our reservoir modeling. First, conventional core data were used to define the rock types for the cored intervals. The wireline log measurements at the cored depths were extracted, normalized, and subsequently analyzed together with the calculated rock types. A mathematical model was then built to predict the rock type in uncored intervals and in uncored wells. This allows the generation of a synthetic rock-type log for all wells with modern log suites. Geostatistical techniques can then be used to populate the rock type throughout a reservoir. After rock type and porosity are populated properly, the permeability can be estimated by use of the unique permeability/porosity relationship for a given rock type. The initial water saturation for a reservoir can be estimated subsequently by use of the corresponding rock-type, porosity, and permeability models as well as the rock-type-based J functions. We observed that a global permeability multiplier became unnecessary in our reservoir-simulation models when the permeability model is constructed with this technique. Consistent initial-water-saturation models (i.e., calculated and log-measured water saturations are in excellent agreement) can be obtained when the proper J function is used for a given rock type. As a result, the uncertainty associated with volumetric calculations is greatly reduced as a more accurate initial-water-saturation model is used. The true dynamic characteristics (i.e., the flow capacity) of the reservoir are captured in the reservoir-simulation model when a more reliable permeability model is used. Introduction Rock typing is a process of classifying reservoir rocks into distinct units, each of which was deposited under similar geological conditions and has undergone similar diagenetic alterations (Gunter et al. 1997). When properly classified, a given rock type is imprinted by a unique permeability/porosity relationship, capillary pressure profile (or J function), and set of relative permeability curves (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993). As a result, when properly applied, rock typing can lead to the accurate estimation of formation permeability in uncored intervals and in uncored wells; reliable generation of initial-water-saturation profile; and subsequently, the consistent and realistic simulation of reservoir dynamic behavior and production performance. Of the various quantitative rock-typing techniques (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993; Porras and Campos 2001; Jennings and Lucia 2001; Rincones et al. 2000; Soto et al. 2001) presented in the literature, two techniques (RQI/FZI and Winland's R35) appear to be used more widely than the others for clastic reservoirs (Gunter et al. 1997, Amaefule et al. 1993). In the RQI/FZI approach (Amaefule et al. 1993), rock types are classified with the following three equations: [equations]

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.

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.

scholarly journals Integrated rock typing and pore facies analyses in a heterogeneous carbonate for saturation height modelling, a case study from Fahliyan Formation, the Persian Gulf

2021 ◽  
Vol 11 (4) ◽  
pp. 1577-1595
Author(s):  
Rasoul Ranjbar-Karami ◽  
Parisa Tavoosi Iraj ◽  
Hamzeh Mehrabi
Keyword(s):  
Capillary Pressure ◽  
Water Saturation ◽  
High Energy ◽  
Carbonate Reservoir ◽  
Reservoir Rock ◽  
Initial Water ◽  
Rock Types ◽  
Rock Typing ◽  
Pore Types ◽  
Fitting Parameters

AbstractKnowledge of initial fluids saturation has great importance in hydrocarbon reservoir analysis and modelling. Distribution of initial water saturation (Swi) in 3D models dictates the original oil in place (STOIIP), which consequently influences reserve estimation and dynamic modelling. Calculation of initial water saturation in heterogeneous carbonate reservoirs always is a challenging task, because these reservoirs have complex depositional and diagenetic history with a complex pore network. This paper aims to model the initial water saturation in a pore facies framework, in a heterogeneous carbonate reservoir. Petrographic studies were accomplished to define depositional facies, diagenetic features and pore types. Accordingly, isolated pores are dominant in the upper parts, while the lower intervals contain more interconnected interparticle pore types. Generally, in the upper and middle parts of the reservoir, diagenetic alterations such as cementation and compaction decreased the primary reservoir potential. However, in the lower interval, which mainly includes high-energy shoal facies, high reservoir quality was formed by primary interparticle pores and secondary dissolution moulds and vugs. Using huge number of primary drainage mercury injection capillary pressure tests, we evaluate the ability of FZI, r35Winland, r35Pittman, FZI* and Lucia’s petrophysical classes in definition of rock types. Results show that recently introduced rock typing method is an efficient way to classify samples into petrophysical rock types with same pore characteristics. Moreover, as in this study MICP data were available from every one meter of reservoir interval, results show that using FZI* method much more representative sample can be selected for SCAL laboratory tests, in case of limitation in number of SCAL tests samples. Integration of petrographic analyses with routine (RCAL) and special (SCAL) core data resulted in recognition of four pore facies in the studied reservoir. Finally, in order to model initial water saturation, capillary pressure data were averaged in each pore facies which was defined by FZI* method and using a nonlinear curve fitting approach, fitting parameters (M and C) were extracted. Finally, relationship between fitting parameters and porosity in core samples was used to model initial water saturation in wells and between wells. As permeability prediction and reservoir rock typing are challenging tasks, findings of this study help to model initial water saturation using log-derived porosity.

Enhanced and Rock Typing-Based Reservoir Characterization of the Palaeocene Harash Carbonate Reservoir-Zelten Field-Sirte Basin-Libya

2021 ◽  
Author(s):  
Mohamed Masoud ◽  
W. Scott Meddaugh ◽  
Masoud Eljaroshi ◽  
Khaled Elghanduri
Keyword(s):  
Rock Type ◽  
Carbonate Reservoir ◽  
Classification Model ◽  
Reservoir Rocks ◽  
The Core ◽  
Core Samples ◽  
Rock Types ◽  
Rock Typing ◽  
Open Hole ◽  
Type Classification

Abstract The Harash Formation was previously known as the Ruaga A and is considered to be one of the most productive reservoirs in the Zelten field in terms of reservoir quality, areal extent, and hydrocarbon quantity. To date, nearly 70 wells were drilled targeting the Harash reservoir. A few wells initially naturally produced but most had to be stimulated which reflected the field drilling and development plan. The Harash reservoir rock typing identification was essential in understanding the reservoir geology implementation of reservoir development drilling program, the construction of representative reservoir models, hydrocarbons volumetric calculations, and historical pressure-production matching in the flow modelling processes. The objectives of this study are to predict the permeability at un-cored wells and unsampled locations, to classify the reservoir rocks into main rock typing, and to build robust reservoir properties models in which static petrophysical properties and fluid properties are assigned for identified rock type and assessed the existed vertical and lateral heterogeneity within the Palaeocene Harash carbonate reservoir. Initially, an objective-based workflow was developed by generating a training dataset from open hole logs and core samples which were conventionally and specially analyzed of six wells. The developed dataset was used to predict permeability at cored wells through a K-mod model that applies Neural Network Analysis (NNA) and Declustring (DC) algorithms to generate representative permeability and electro-facies. Equal statistical weights were given to log responses without analytical supervision taking into account the significant log response variations. The core data was grouped on petrophysical basis to compute pore throat size aiming at deriving and enlarging the interpretation process from the core to log domain using Indexation and Probabilities of Self-Organized Maps (IPSOM) classification model to develop a reliable representation of rock type classification at the well scale. Permeability and rock typing derived from the open-hole logs and core samples analysis are the main K-mod and IPSOM classification model outputs. The results were propagated to more than 70 un-cored wells. Rock typing techniques were also conducted to classify the Harash reservoir rocks in a consistent manner. Depositional rock typing using a stratigraphic modified Lorenz plot and electro-facies suggest three different rock types that are probably linked to three flow zones. The defined rock types are dominated by specifc reservoir parameters. Electro-facies enables subdivision of the formation into petrophysical groups in which properties were assigned to and were characterized by dynamic behavior and the rock-fluid interaction. Capillary pressure and relative permeability data proved the complexity in rock capillarity. Subsequently, Swc is really rock typing dependent. The use of a consistent representative petrophysical rock type classification led to a significant improvement of geological and flow models.

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.

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.

The Characteristics and Impacts Factors of Relative Permeability Curves in High Temperature and Low-Permeability Limestone Reservoirs

2014 ◽  
Vol 1010-1012 ◽  
pp. 1676-1683 ◽  
Author(s):  
Bin Li ◽  
Wan Fen Pu ◽  
Ke Xing Li ◽  
Hu Jia ◽  
Ke Yu Wang ◽  
...  
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
Water Saturation ◽  
Phase Region ◽  
Two Phase ◽  
Experimental Conditions ◽  
Irreducible Water Saturation ◽  
Productive Water ◽  
Relative Permeability Curves ◽  
Water Cut

To improve the understanding of the influence of effective permeability, reservoir temperature and oil-water viscosity on relative permeability and oil recovery factor, core displacement experiments had been performed under several experimental conditions. Core samples used in every test were natural cores that came from Halfaya oilfield while formation fluids were simulated oil and water prepared based on analyze data of actual oil and productive water. Results from the experiments indicated that the shape of relative permeability curves, irreducible water saturation, residual oil saturation, width of two-phase region and position of isotonic point were all affected by these factors. Besides, oil recovery and water cut were also related closely to permeability, temperature and viscosity ratio.

Carbonate Rock Type Matrix RocMat, The Ultimate Rock Properties Catalogue

2013 ◽  
Author(s):  
Omar Al-Farisi ◽  
Hadi Belhaj ◽  
Fatmah Yammahi ◽  
Abdulla Al-Shemsi ◽  
Hocine Khemissa
Keyword(s):  
Capillary Pressure ◽  
Carbonate Rock ◽  
Water Saturation ◽  
Rock Type ◽  
Free Water ◽  
Pore Network ◽  
Rock Properties ◽  
Main Task ◽  
Rock Typing ◽  
Heterogeneous Rocks

Rock typing is one of the most important steps in reservoir modeling, and it’s the main task in reservoir characterization. In carbonate, the rock typing work that’s been performed during the last two decades had a little progress in term of providing reliable estimation of reservoir behavior. However, the development of Conjunction Rock Properties Convergence, CROPC, a carbonate rock typing concept that provided an important and easy solution to the carbonate rock typing gaps, has a major breakthrough, even though, CROPC methodology was developed to capture the single pore network through the conjunction of Lithology, permeability, capillary pressure and water saturation. Therefore, the need to identify more complex carbonate pore network had led to the initiation of developing the Carbonate Rock Type Matrix RocMat, which will be detailed in this paper, as part of a Master of Science research project. In this novel concept the carbonate rocks were classified into homogeneous, single pore network, and heterogeneous rocks, dual and triple pore network with the utilization of the effective petrophysical properties of permeability, capillary pressure, saturation, porosity and height above free water level, all were classified in a conjunction matrix that honors these properties and at the same time enables generating sub groups as down scaling and estimation for unseen groups with infinite rock complexity capturing, at the same time it enables the ease to lump the groups and generates upscale-groups that make it easier for utilization by the geologist and reservoir engineers to achieve the objective of better reservoir performance prediction, the work was performed and then tested in two carbonate offshore fields data. This RocMat was structured to be the ultimate catalog for carbonate rock types.

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