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.

Digital Rock Typing DRT Algorithm Formulation with Optimal Supervised Semantic Segmentation

2022 ◽  
Author(s):  
Omar Alfarisi ◽  
Djamel Ouzzane ◽  
Mohamed Sassi ◽  
TieJun Zhang
Keyword(s):  
Carbonate Rock ◽  
Chemical Properties ◽  
Rock Physics ◽  
Semantic Segmentation ◽  
Rock Properties ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Rock Types ◽  
Fluid Saturation ◽  
Rock Typing

<p><a></a>Each grid block in a 3D geological model requires a rock type that represents all physical and chemical properties of that block. The properties that classify rock types are lithology, permeability, and capillary pressure. Scientists and engineers determined these properties using conventional laboratory measurements, which embedded destructive methods to the sample or altered some of its properties (i.e., wettability, permeability, and porosity) because the measurements process includes sample crushing, fluid flow, or fluid saturation. Lately, Digital Rock Physics (DRT) has emerged to quantify these properties from micro-Computerized Tomography (uCT) and Magnetic Resonance Imaging (MRI) images. However, the literature did not attempt rock typing in a wholly digital context. We propose performing Digital Rock Typing (DRT) by: (1) integrating the latest DRP advances in a novel process that honors digital rock properties determination, while; (2) digitalizing the latest rock typing approaches in carbonate, and (3) introducing a novel carbonate rock typing process that utilizes computer vision capabilities to provide more insight about the heterogeneous carbonate rock texture.<br></p>

Utilizing Capillary Pressure Measurements and Water Saturation Logs to Determine Reservoir Quality in a Giant Middle Eastern Carbonate Field

2021 ◽  
Author(s):  
Bashar Alramahi ◽  
Qaed Jaafar ◽  
Hisham Al-Qassab
Keyword(s):  
Water Level ◽  
Capillary Pressure ◽  
Water Saturation ◽  
Middle Eastern ◽  
Free Water ◽  
Production Data ◽  
Reservoir Quality ◽  
Pressure Measurements ◽  
High Quality ◽  
Reservoir Facies

Abstract Classifying rock facies and estimating permeability is particularly challenging in Microporous dominated carbonate rocks. Reservoir rock types with a very small porosity range could have up to two orders of magnitude permeability difference resulting in high uncertainty in facies and permeability assignment in static and dynamic models. While seismic and conventional porosity logs can guide the mapping of large scale features to define resource density, estimating permeability requires the integration of advanced logs, core measurements, production data and a general understanding of the geologic depositional setting. Core based primary drainage capillary pressure measurements, including porous plate and mercury injection, offer a valuable insight into the relation between rock quality (i.e., permeability, pore throat size) and water saturation at various capillary pressure levels. Capillary pressure data was incorporated into a petrophysical workflow that compares current (Archie) water saturation at a particular height above free water level (i.e., capillary pressure) to the expected water saturation from core based capillary pressure measurements of various rock facies. This was then used to assign rock facies, and ultimately, estimate permeability along the entire wellbore, differentiating low quality microporous rocks from high quality grainstones with similar porosity values. The workflow first requires normalizing log based water saturations relative to structural position and proximity to the free water level to ensure that the only variable impacting current day water saturation is reservoir quality. This paper presents a case study where this workflow was used to detect the presence of grainstone facies in a giant Middle Eastern Carbonate Field. Log based algorithms were used to compare Archie water saturation with primary drainage core based saturation height functions of different rock facies to detect the presence of grainstones and estimate their permeability. Grainstones were then mapped spatially over the field and overlaid with field wide oil production and water injection data to confirm a positive correlation between predicted reservoir quality and productivity/injectivity of the reservoir facies. Core based permeability measurements were also used to confirm predicted permeability trends along wellbores where core was acquired. This workflow presents a novel approach in integrating core, log and dynamic production data to map high quality reservoir facies guiding future field development strategy, workover decisions, and selection of future well locations.

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]

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.

scholarly journals PREDIKSI PERMEABILITAS MENGGUNAKAN METODE LOG DAN PORE GEOMETRY STRUCTURE (PGS) PADA DAERAH CEKUNGAN JAWA BARAT UTARA

2020 ◽  
Vol 6 (1) ◽  
pp. 3-17
Author(s):  
Ayu Yuliani ◽  
Ordas Dewanto ◽  
Karyanto Karyanto ◽  
Ade Yogi
Keyword(s):  
Water Saturation ◽  
Effective Porosity ◽  
Reservoir Rock ◽  
Rock Properties ◽  
Pore Geometry ◽  
Rock Permeability ◽  
Zone Formation ◽  
Geometry Structure ◽  
Rock Typing

Determination of reservoir rock properties is very important to be able to understand the reservoir better. One of these rock properties is permeability. Permeability is the ability of a rock to pass fluid. In this study, the calculation of permeability was carried out using log and PGS (Pore Geometry Structure) methods based on core data, logs, and CT scans. In the log method, the calculation of permeability is done by petrophysical analysis which aims to evaluate the target zone formation in the form of calculation of the distribution of shale content (effective volume), effective porosity, water saturation, and permeability. Next, the determination of porosity values from CT Scan. Performed on 2 data cores of 20 tubes, each tube was plotted as many as 15 points. The output of this stage is the CT Porosity value that will be used for the distribution of predictions of PGS permeability values. In the PGS method, rock typing is based on geological descriptions, then calculation of permeability predictions. Using these two methods, permeability can be calculated in the study area. The results of log and PGS permeability calculations that show good correlation are the results of calculation of PGS permeability. It can be seen from the data from the calculation of PGS permeability approaching a gradient of one value with R2 of 0.906, it will increasingly approach the core rock permeability value. Whereas the log permeability calculation for core rock permeability is 0.845.

Digital Rock Typing DRT Algorithm Formulation with Optimal Supervised Semantic Segmentation

2022 ◽  
Author(s):  
Omar Alfarisi ◽  
Djamel Ouzzane ◽  
Mohamed Sassi ◽  
TieJun Zhang
Keyword(s):  
Carbonate Rock ◽  
Chemical Properties ◽  
Rock Physics ◽  
Semantic Segmentation ◽  
Rock Properties ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Rock Types ◽  
Fluid Saturation ◽  
Rock Typing

<p><a></a>Each grid block in a 3D geological model requires a rock type that represents all physical and chemical properties of that block. The properties that classify rock types are lithology, permeability, and capillary pressure. Scientists and engineers determined these properties using conventional laboratory measurements, which embedded destructive methods to the sample or altered some of its properties (i.e., wettability, permeability, and porosity) because the measurements process includes sample crushing, fluid flow, or fluid saturation. Lately, Digital Rock Physics (DRT) has emerged to quantify these properties from micro-Computerized Tomography (uCT) and Magnetic Resonance Imaging (MRI) images. However, the literature did not attempt rock typing in a wholly digital context. We propose performing Digital Rock Typing (DRT) by: (1) integrating the latest DRP advances in a novel process that honors digital rock properties determination, while; (2) digitalizing the latest rock typing approaches in carbonate, and (3) introducing a novel carbonate rock typing process that utilizes computer vision capabilities to provide more insight about the heterogeneous carbonate rock texture.<br></p>

Quantification of micron-scale structural and hydraulic properties of long-term pig manure and lime amended red soil aggregates using the lattice Boltzmann method and pore network modelling

2020 ◽  
Author(s):  
Rong Qu ◽  
Hu Zhou ◽  
Paul Hallet
Keyword(s):  
Capillary Pressure ◽  
Lattice Boltzmann ◽  
Water Retention ◽  
Water Saturation ◽  
Pore Network ◽  
The Other ◽  
Pig Manure ◽  
Manure Treatment ◽  
Boltzmann Method ◽  
Control Samples

&lt;p&gt;Lime and animal manure can have major impacts on soil physical properties, particularly in degraded and highly weathered soils that are naturally acidic. Here we evaluate how treatment of a regular till Acrisol in southeast China with different amounts of lime and/or pig manure, and planted with maize, affects pore scale properties down to micron size using synchrotron microtomography (SR&amp;#8211;mCT). Soil macroaggregates (2 - 5 mm) from 4 treatments were measured: 1) Control, no manure amendment; 2) low manure (150 kg N ha&lt;sup&gt;-1&lt;/sup&gt; y&lt;sup&gt;-1&lt;/sup&gt;); 3) high manure (600 kg N ha&lt;sup&gt;-1&lt;/sup&gt; y&lt;sup&gt;-1&lt;/sup&gt;); and 4) high manure (600 kg N ha&lt;sup&gt;-1&lt;/sup&gt; y&lt;sup&gt;-1&lt;/sup&gt;)+ lime (3000 kg Ca(OH)&lt;sub&gt;2&lt;/sub&gt; ha&lt;sup&gt;-1 &lt;/sup&gt;every 3 years). Pore structure at a resolution of 3.7 &amp;#181;m was reconstructed in 3D and the Multi- Relaxation- Time (MRT) Scheme for Multi- Phase Lattice Boltzmann Method (LBM) was used to simulate water flow and retention. Topological analysis was performed based on the extracted pore network by using the maximal ball-based pore network extraction. A quasi-static pore network solver was applied to compute the capillary pressure based on the extracted pore networks. The application of a high amount of pig manure increased the fraction of macropores (&gt;100 &amp;#181;m) to 38.61% compared to the controlled level (18.15%). A high amount of pig manure also decreased total porosity to 8.08% compared to 11.35% for the control, suggesting less micropores caused by high pig manure treatment. The application of high amount of pig manure and lime also caused more uniform water flow. Control samples had a velocity frequency at around e&lt;sup&gt;11 &lt;/sup&gt;of the normalized velocity (respect to the mean), while the samples from the other treatments had more evenly distributed peaks. Water flows most quickly due to least impediment by pores in the samples with high manure amendment. The slope between permeability and porosity increased from 8.10 Darcy (&lt;!-- Units? --&gt;controlled) to 174.47 Darcy (high amount of manure treatment). The amendment of 600 kg N ha&lt;sup&gt;-1&lt;/sup&gt; y&lt;sup&gt;-1 &lt;/sup&gt;pig manure increased water retention ability calculated by the simulations. For the capillary pressure &gt; -50 kPa, control samples had the greatest water saturation level compared with the samples from the other treatments, while there were no significant differences of water saturation of samples from all the treatments for the capillary pressure &lt; -1000 kPa . The simulated water retention results had the same trend with the measured results.&lt;/p&gt;

FROM PLUG MEASUREMENTS TO DYNAMIC SIMULATIONS: UPSCALING EFFECTS ON MODELED HYDROCARBON VOLUMES

2021 ◽  
Author(s):  
Iulian N. Hulea ◽  
Keyword(s):  
History Matching ◽  
Water Saturation ◽  
Free Water ◽  
Rock Properties ◽  
Free Fluid ◽  
Detailed Knowledge ◽  
Well Performance ◽  
Permeability Model ◽  
Rock Quality ◽  
Change Of Scale

Building reliable subsurface models requires detailed knowledge of both the rock and fluids involved. One critical petrophysical property determining the viability of a development is the hydrocarbon saturation. In 3D geological models, the saturation is populated via Saturation height models and free fluid levels. In populating a 3D model with meaningful properties, measurements at various scales are integrated. Core measurements acquired at resolution far superior to that used in the 3D models require a change of scale- upscaling step. The process of accurately predicting water saturation in the upscaled model is not trivial. Here we follow this process by employing a saturation height model (SHM) at different scales in relationship to various permeability realizations. Multiple choices available as inputs into the SHM in various ranges of sensitivity with respect to the free water level position as well as different rock quality are looked at. Various degrees of heterogeneity are studied by using synthetic data, the saturation prediction accuracy based on upscaled input rock properties (like arithmetic/geometric and harmonic upscaled permeability) is investigated. For homogeneous rocks a workflow is detailed with the purpose of detecting the upscaling limits highlighting the possible errors that might appear in the upscaling process. A counterintuitive result is that in the transition zone (the focus of this work) permeable rocks are more prone to errors than the less permeable ones. We also conclude that no alteration of the SHM is necessary in the upscaling process. Given the fact that rock quality enters the SHM and that permeability upscaling follows a route that ultimately attempts to honor well performance, a natural question is what the relevance of such a permeability model as input for the SHM is. Our results highlight the best choices for an upscaled SHM input (upscaled) permeability- not necessarily the upscaled permeability used in history matching. Smallest errors are shown to be resulting from using geometrical or 1/3 power law upscaled permeability.

scholarly journals Water saturation modeling using modified J-function constrained by rock typing method in bioclastic limestone

2020 ◽  
Vol 75 ◽  
pp. 66
Author(s):  
Ya Deng ◽  
Rui Guo ◽  
Zhongyuan Tian ◽  
Limin Zhao ◽  
Dandan Hu ◽  
...  
Keyword(s):  
Water Saturation ◽  
Free Water ◽  
Petrophysical Properties ◽  
Saturation Model ◽  
Typing Method ◽  
Thin Sections ◽  
Rock Types ◽  
Rock Typing ◽  
Wireline Logs ◽  
Mercury Injection Capillary Pressure

Combining both geological and petrophysical properties, a reliable rock typing scheme can be achieved. Two steps are included in rock typing. Step 1: rocks are classified into lithofacies based on core observations and thin sections; Step 2: lithofacies are further subdivided into rock types according to petrophysical properties such as MICP (Mercury Injection Capillary Pressure) and K-Phi relationships. By correlating rock types to electrofacies (clusters of log data), we can group the target formation into 12 rock types. Then it is possible to predict the distributions of rock types laterally and vertically using wireline logs. To avoid the defect of the classical J-function saturation model that includes permeability which is quite uncertain especially in carbonate rocks, a modified J-function was created and used in the paper. In this function, water saturation is simply expressed as a function of height above free water level for a specific rock type. Different water saturation models are established for different rock types. Finally, the water saturation model has been successfully constructed and verified to be appropriate.

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