On the Pore Geometry and Structure Rock Typing.

Accurate rock grouping and permeability prediction in complex carbonate reservoirs are critical for adequate reservoir characterization and management. These reservoirs are often challenging due to the intricate interplay of sedimentary and diagenetic processes that influence pore geometry and rock properties. This study introduces a new approach to connect carbonate reservoirs' sedimentary and diagenetic features using a pore geometry structure rock typing method. The objective is to enhance rock grouping and improve permeability prediction. The implementation of basic PGS rock typing in this study follows the rock type curve established by Wibowo and Permadi (2013), which is based on the similarity of the Kozeny constant (Kozeny, 1927). This constant is calculated as the product of the pore shape factor (Fs) and tortuosity (τ) as a parametric variable within specific rock groups. This method allows for a systematic exploration of the critical factors governing multiphase flow behavior within porous rocks. The study analyzed data from four cored wells, totaling nearly 1650 feet, which included 1185 routine core analysis (RCA) samples, 440 mercury injection capillary pressure (MICP) samples, and thin section data. Our methodology integrates detailed petrographic analysis, sedimentological studies, and advanced pore geometry characterization. Combining these geological insights with quantitative Petrophysical Group (PG) data from Mercury Injection Capillary Pressure (MICP), we develop a rock typing framework that links pore structure variations to sedimentary and diagenetic controls, including cementation and dissolution processes. This enables the identification of distinct rock types that reflect depositional environments and diagenetic alterations, which directly influence reservoir quality and fluid flow. This approach's application as a new insight to complement the Pore Geometry Structure (PGS) rock typing method demonstrates its effectiveness in grouping reservoir rocks with similar permeability and fluid flow characteristics. Our findings show a clear and robust correlation between the dissolution process and pore geometry structure, providing a solid foundation for the methodology. This is an additional equation for quantitatively specific surface area in the porosity- permeability relationship. This updated pore geometry- structure rock typing method provides a more accurate and geologically informed basis for permeability prediction, contributing to better reservoir modeling in complex carbonate systems. This study presents a novel framework that bridges the gap between sedimentary and diagenetic features and their impact on pore structures. It offers valuable insights that could significantly influence future reservoir development strategies in similar carbonate environments.

This paper presents new interrelationships of elastic properties of the porous rock to petrophysical parameters in order to enhance better understanding on how compressional and shear waves velocities, young modulus, bulk modulus, lame’s coefficients, and Poisson’s ratio correlate with permeability, porosity, petrophysical geometric details of the pore system, and microscopic geological features. This study employs 215 sandstone core-plugs from North West Java Basin. The approach used utilizes the Kozeny-Carman equation with Re-arrangement made on this equation leads to rock typing based on pore structure similarity, similar in pore shape factor and tortuosity. By plotting pore geometry against pore structure variable, it shows that P- and S-wave velocities, young modulus, bulk modulus, Poisson’s ratio, and lame’s coefficients data can be clearly grouped based on rock type and have strong correlations with permeability, pore geometry, and pore structure parameters. This grouping method enables to investigate the main influential factors that systematically control rock elastic properties. The interrelationships of each parameter of P-wave and S-wave velocities, young modulus, bulk modulus, Poisson’s ratio, and lame’s coefficients versus pore geometry and pore structure were constructed. The critical finding is that each relation among the rock groups of each elastic property is clearly separated. Each rock type has a similar pattern in that P-wave and S-wave velocities increase with pore geometry and pore structure variables. These velocities tend to be high with an increase in Kozeny constant. However, for a given porosity for all the groups, these velocities increase remarkably with a decrease in Kozeny constant. In other word, velocities increase with either an increase in the complexity of pore systems or, at the same pore complexity, a decrease in specific internal surface area. In addition, young modulus, bulk modulus, and lame’s coefficients also increase with pore geometry and pore structure in each rock type. As a novelty, this study helps to characterize the elastic properties based on porosity and permeability data in the form of pore geometry and pore structure. Furthermore, this work can help us to predict some elastic properties at in-situ condition as long as we have the porosity and permeability values interval.

Hydrocarbon saturation below present-day free water levels (FWL) is observed in many fields and can be attributed to either past geologic events or more recent production-related pressure changes and fluid movement. However, modeling residual oil saturation (Sorw) below a present-day FWL is a topic of limited understanding within reservoir characterization, particularly in evaluating the impact on water injection efficiency and reserves uncertainty in dynamic reservoir modeling. The presence of significant volumes of residual oil below the FWL can have profound implications for reserves estimations and development scenarios in field development plans. This study, inspired by a recent oil discovery in clastic sediments on the Norwegian Continental Shelf, explores this phenomenon through an integrated approach that spans from core and log scale analyses to field-scale assessment. This paper will present a case-study showing the recognition of a significant paleo-oil column based on petrophysical logs and core data, and both the definition of a present-day FWL and prediction of a paleo FWL. This paper will further describe a versatile technique for modeling residual oil saturation below the current FWL by integrating geological and engineering data from routine (RCA) and special core analyses (SCAL), well logs, and 3D reservoir models. The methodology begins with a rigorous quality check of core analysis data and other relevant information to ensure accuracy and suitability of the data used. We then applied a novel rock typing technique based on similarities in pore geometry and structure (PGS), incorporating RCA and SCAL data. These were integrated into a newly developed Corey SCAL modeling method to establish static and dynamic saturation functions for each rock type, which were then used in 3D reservoir modeling and simulation. Subsequently, we estimated the SCAL uncertainty range for each rock type and integrated it into the reference 3D static and dynamic models. After assimilating all input data into the 3D reservoir models, production forecasts were generated, including sensitivity and uncertainty workflows. Additionally, we developed new water saturation model workflows for static modeling by implementing saturation depth functions (SDF) with established Pc-imbibition curves. Furthermore, a fishbone completion model for water injection wells was constructed, and production was forecasted under the selected scenario. A key result of this work is effectively modelling residual oil saturation below a current FWL by implementing PGS rock typing and a saturation depth function based on Pc- imbibition in both static and dynamic models. The presence of oil saturation below the current FWL matched the observation from core and logs and increased Initial Oil in Place (IOIP) by approximately 25% compared to the original case without residual oil modeling. Meanwhile, this also reduced the recoverable oil volume by approximately 11% compared to the reference case primarily due to decreased injectivity in water injection following relative permeability corrections based on SCAL modeling techniques. To mitigate this negative impact, we evaluated methods for improving injectivity using a fishbone completion model in water injector wells during reservoir simulation, which resulted in an incremental oil recovery of up to 9% compared to the base case scenario of this study. As a novelty, this study proposes a new solution for estimating oil saturation below the current FWL based on saturation depth functions that are consistent with rock typing and wettability physics derived from imbibition capillary pressure curves. Additionally, the value of SCAL modeling, particularly in capturing the uncertainty in reserves evaluation through relative permeability and PGS rock types, proves suitable for full-field reservoir simulations, uncertainty analyses, and field performance assessments. This workflow also facilitates permeability prediction as a function of porosity and irreducible water saturation while generating systematic saturation functions based on capillary pressure data.

A quick, inexpensive way to maximize the use of routine core analysis data is desired to support both geological and engineering works. Better understanding about pore structure and geometry that relate to hydraulic characteristics of a pores system can lead to improved reservoir characterization. The objectives of this paper are to present techniques to improve permeability prediction and identify the implications of relationship between pore structural and geometrical attributes on hydraulic characteristic of rock samples. The present work is based on equations of capillary model. The equations in fact contain three important hydraulic parameters: mean and effective hydraulic diameters as the geometrical parameters and hydraulic conductivity as the structural parameter. These parameters and porosity are the main variables to be used in the crossplot analysis and interpretation. This work is facilitated with two core data sets of sandstones and carbonates. It is demonstrated that crossplot of the effective hydraulic diameter against porosity can be used to predict permeability. Comparisons between this technique and the previous one show that the present technique results in less scatter data points and overall gives better permeability prediction. The crossplot of either effective or mean hydraulic diameter versus hydraulic conductivity works perfectly in dividing all the data points into several distinct groups. The data points of each group are lining to form a straight line. Two and four distinct straight lines with different slopes are formed, respectively, for the sandstones and carbonates. These are in excellent agreement with the electrofacies and the result of Leverett’s J-Function analysis. Overall, this paper provides the related theoretical background and detailed discussion on the results, giving better understanding about pore structure and geometry and its relation with permeability and rock typing.

A quick, inexpensive way to maximize the use of routine core analysis data is desired to support both geological and engineering works. Better understanding about pore structure and geometry that relate to hydraulic characteristics of a pores system can lead to improved reservoir characterization. The objectives of this paper are to present techniques to improve permeability prediction and identify the implications of relationship between pore structural and geometrical attributes on hydraulic characteristic of rock samples. The present work is based on equations of capillary model. The equations in fact contain three important hydraulic parameters: mean and effective hydraulic diameters as the geometrical parameters and hydraulic conductivity as the structural parameter. These parameters and porosity are the main variables to be used in the crossplot analysis and interpretation. This work is facilitated with two core data sets of sandstones and carbonates. It is demonstrated that crossplot of the effective hydraulic diameter against porosity can be used to predict permeability. Comparisons between this technique and the previous one show that the present technique results in less scatter data points and overall gives better permeability prediction. The crossplot of either effective or mean hydraulic diameter versus hydraulic conductivity works perfectly in dividing all the data points into several distinct groups. The data points of each group are lining to form a straight line. Two and four distinct straight lines with different slopes are formed, respectively, for the sandstones and carbonates. These are in excellent agreement with the electrofacies and the result of Leverett's J-Function analysis. Overall, this paper provides the related theoretical background and detailed discussion on the results, giving better understanding about pore structure and geometry and its relation with permeability and rock typing.

Extensive and detailed studies of the pore systems of the Ghawar Arab D limestone have been captured in very large mercury injection capillary pressure data sets1–3 in which all data have been analyzed using Thomeer functions4–6. These data give new insight into the pore geometry dependence of the reservoir dynamical properties: permeability and imbibition oil relative permeability7 and yield ultimate recovery rock types with algorithms for rock type based reservoir simulation studies of ultimate recovery. New carbonate petrophysical concepts are established. The dominant subgroup of the examined carbonate limestone pore systems comprise the major Arab D reservoir section are denoted as an M_1 bimodal pore system3. The M_1 bimodal pore system consists of a macropore system (M), with a well defined and wide distribution of pore throat diameters and geometries, in conjunction with Type 1 microporosity with equally well defined and narrow distribution of pore throat diameters and geometries. This bimodal M_1 pore system results in a mixed wet reservoir condition in the bulk of the reservoir. The role played by the macro and micro pores of the M_1 pore system has been related to the reservoir dynamical properties: permeability and relative permeability7. This work demonstrates fundamentally new pore geometry based formulations for calculating permeability and imbibition oil relative permeability and therefore delineates the pore geometry based variation in microscopic displacement efficiency for variations within these systems. For these reservoir rocks, the appropriate pore geometrical parameters to perform ultimate recovery rock typing have been identified. This paper presents data and formulations for improved pore system based models of permeability and imbibition oil relative permeability in the M_1 bimodal pore system that reproduce measured laboratory data over a range of oil relative permeability from 1 to 0.0001 for seven waterflood composites. The relative permeability formulation uses two attributes of the pore system: permeability (already shown to be a function of pore geometrical parameters) and the volume of Type 1 microporosity alone. Both of these can be extracted from appropriate processing of appropriate well log data. These results show that shifts of the oil relative permeability curve to increasing water saturation (the right) commonly ascribed to wettability changes, result in this case from increasing the amount of Type 1 microporosity in the M_1 bimodal system which add an "ineffective" water saturation to the relative permeability water saturation axis.

Permeability and rock type are the most important rock properties which can be used as input parameters to build 3D petrophysical models of hydrocarbon reservoirs. These parameters are derived from core samples which may not be available for all boreholes, whereas, almost all boreholes have well log data. In this study, the importance of the fuzzy logic approach for prediction of rock type from well log responses was shown by using an example of the Vp to Vs ratio for lithology determination from crisp and fuzzy logic approaches. A fuzzy c-means clustering technique was used for rock type classification using porosity and permeability data. Then, based on the fuzzy possibility concept, an algorithm was prepared to estimate clustering derived rock types from well log data. Permeability was modelled and predicted using a Takagi-Sugeno fuzzy inference system. Then a back propagation neural network was applied to verify fuzzy results for permeability modelling. For this purpose, three wells of the Iran offshore gas field were chosen for the construction of intelligent models of the reservoir, and a forth well was used as a test well to evaluate the reliability of the models. The results of this study show that fuzzy logic approach was successful for the prediction of permeability and rock types in the Iran offshore gas field.

In Sandstone, the pore complexity in certain rock types is not only related to the mineral constituents, but also to other tectonic properties, including texture and porosity. In sandstones, texture is a primary factor contributing to pore geometry and structure. This condition causes a distributed relationship between P-wave velocity and porosity, although a clear trend exists. The purpose of this research, therefore, was to study the effects of pore complexity with the variation of P-wave velocity on saturated rocks and its impact in estimating critical porosity. In addition, the concept of rock type and convergent point was applied to establish the correlation between saturated P-wave velocity with pore geometry, and pore structure. Subsequently, the data was grouped into several rock types, with each having its own empirical bond and also tends to intersect with others at a converging point. In conclusion, a very good relationship between saturated P-wave velocity and porosity was obtained by categorizing the rocks based on pore geometry and pore structure. However, the individual rock group is known to demonstrate similar pore geometry and specific critical porosity values.

Integrated reservoir rock typing in carbonate reservoirs is a very significant step in reservoir modeling. The key purpose of this study is the determination of integrated rock types in Sarvak Formation of an Iranian oilfield. In this study, electrofacies (EFAC) analysis of Sarvak reservoir was done in detail to determine the reservoir quality and determine rock types of the Sarvak Formation in the studied field. The core data and conventional petrophysical logs were used for rock typing. Some petrophysical logs such as porosity, sonic, neutron, density, and PEF (Photo electric factor) were used as input data for electrofacies analysis. Multi-Resolution Graph-Based Clustering (MRGC) was used among six different approaches resulting four electrofacies after merging the similar clusters. EFAC-1 has the lowest and EFAC-4 has the highest porosity. In addition, based on Winland and Amaefule approaches, three rock types were determined using core data (porosity and permeability). As a result, three rock types were determined which rock type-1 has the smallest pore-throat size and FZI (flow zone indicator) while the rock type-3 has the highest ones. The correlation coefficient between porosity and permeability in each rock type is more than 80%. Rock type 1 mostly composed of EFAC-1 and EFAC-2, while the rock types 2 and 3 share mostly the EFACs 1, 3 and 4.

Hydraulic flow units and rock types in the Middle and Lower Bahariya Formation encountered in different drilled wells in NEAG-1 field were investigated. These are governed by lithologic variations and flaser laminations characterizing the Bahariya deposits, while they have a direct impact on sedimentation and digenetic process. The measured pore throat radius (r35) using mercury injection capillary pressure (MICP) technique were used to develop self-reliant trend lines with reliable formula derived from laboratory petrophysical measurements. Petrographic investigations were used for outlining mineralogy, porosity types and mode of occurrence of formation fines. X-ray diffraction technique (XRD) of bulk samples was used for detecting rock forming minerals, mineralogy of cementing materials and their quantitative dominance in the pore spaces of the studied Bahariya sandstone samples. The Primary and secondary porosity either interparticle or intraparticle are controlling by pore space architecture while, four reservoir rock types (T-1, T-2, T-3 and T-4) are detected. Each rock type reflects different sedimentary environmental agent, degree of digenesis and variation in mineralogy. The calculated equations predict that up to 85 % of measured permeability data demonstrate 10 hydraulic flow units which reveal the value of r35 standing between 0.2μm and 3. 11μm. The relationship between helium porosity and nitrogen permeability for the studied samples are supported by high coefficients of correlation (R2 = range 0.75 to 0.85) allowing reservoir characterization and permeability prediction from measured average porosity of each reservoir rock type. Different empirical relationships were constructed in order to facilitate hydrocarbon exploration and development in the Neag-1 oil field in the Egyptian Western Desert.

The permeability (k) and electrical resistivity of carbonate rocks with similar porosity (ϕ) may exhibit multiple orders of magnitude differences due to the diversity of pore types and the multiscale characteristics of pore size. As a result, traditional permeability-porosity and resistivity-porosity models usually have strong limitations when applied to carbonate reservoirs, let alone evaluate permeability from electrical resistivity. In this study, a new rock typing parameter named relative transport quality index (RTQI) is proposed to categorize rock samples using permeability and formation resistivity factor (F). Samples with similar RTQI values tend to have similar relative capacities of hydraulic and electrical transport. Subsequently, the classification performance and microscopic differences between RTQI and other rock typing indices including flow zone indicator (FZI), current zone indicator (CZI), and electrical quality index (EQI) were compared and discussed based on the reported petrophysical data of 316 carbonate rock samples. The results indicate that the RTQI method significantly reduces the scattering of k and F by dividing the samples into distinct groups, and each RTQI group corresponds to a special k–F correlation with a high determination coefficient. However, the number of rock types identified by different rock typing indices is different, meaning that samples belonging to the same rock type in the k–F plot of the RTQI method may be classified into different rock types in the k–ϕ plot of the FZI method and the F–ϕ plots of the CZI and EQI methods, which may be caused by the microscopic differences of rock typing parameters. Different from the strong dependence of FZI on hydraulic tortuosity and CZI/EQI on electrical tortuosity, RTQI is mainly dominated by the ratio of electrical tortuosity to hydraulic tortuosity. Additionally, in view of the good correlation between petrophysical data after rock typing, two workflows are proposed to estimate the hydraulic and electrical parameters of carbonate rocks from log data.

The Jonah field is one of the biggest tight gas sand fields in the Green River basin. Production profiles from its deeper sections show high liquid hydrocarbons close to the Pinedale anticline, especially in Mesaverde and Lance formations. To assess the potential of condensate production, new approaches for rock classification are needed to differentiate between discontinuous sandstone layers and the interbedded siltstones. A gamma ray cut off of 75 API has been defined to distinguish between sandstone and siltstone in logs and core samples in Lance and Mesaverde Formations. Significant variation of porosity and permeability occurs within the sandstone zones. This variation warrants new rock typing approaches. We present rock typing for tight sandstones and siltstones with an understanding of petrophysical properties such as pore structure, porosity, permeability, and cementation. We studied 94 samples from the Mesaverde and Lance Formations with lithologies varying from clean sandstone to shale. X-ray diffraction (XRD) mineralogy, mercury injection capillary pressure (MICP), helium porosity and permeability were measured for all samples. NMR transverse relaxation times (T2) at 2 MHz were also measured for 10 water saturated samples. Nitrogen adsorption was performed on 11 samples from Mesaverde formation to determine pore volume and pore size distribution. MICP data are used to subdivide rocks into three groups based on pore throat size distribution: reservoir sandstones, non-reservoir sandstone and siltstone/mudstone. Dominant pore throat size for reservoir and non-reservoir sandstones are 400 and 100 nm, respectively. In order to apply pore throat size rock typing to downhole measurements, NMR pore size classification is used to identify formations. Pore size from NMR demonstrated equivalent behavior to pore throat size from MICP. The logarithmic mean values of T2 transverse relaxation times for reservoir, non-reservoir sandstone and siltstone/mudstone are 22.2 ms, 3.4 ms and 0.29 ms, respectively. Clear separation of reservoir sandstone, non-reservoir sandstone and siltstone is seen based on pressure dependency of ultrasonic compressional and shear velocities during initial pressure loading. Reservoir sandstone demonstrates the highest compressibility. In addition, siltstone and mudstone were separated based on log differential pore volume distribution from N2 adsorption data. Based on pore size distribution data, four main rock types are identified in Lance and Mesaverde formations in Jonah field. Rock typing based on gamma ray and porosity logs can be considered as rock classification of end members. To capture transitional behavior in between end members, pore size distribution is needed in logging application. Since NMR T2 distribution show similar spectra to MICP throat size distribution, the rock typing technique can be applied using NMR log data. Separation of mudstone from siltstone can be used for identification of shale end points in log data.

Rock typing is an essential part of building geologic model for an asset. Millions of dollars are invested in logs, core measurements, SCAL studies, and geological interpretation that result in definition of different rock types. Rock types overlap and do not have crisp boundaries.;Upon definition of rock types for a series of geological formations geoscientists use approximation of multiple and overlapping rock types to identify a dominant rock type for any grid block in a reservoir simulation model. This defeats the original purpose of performing detail geological, petrophysical studies as far as reservoir flow models are concerned.;The objective of this study is to develop a new and novel methodology based on performing "fuzzy rock typing". Fuzzy rock typing refers to application of fuzzy set theory to the part of reservoir characterization that is concerned with rock type determination. Fuzzy set theory is applied in order to take into account the inherent uncertainties and vagueness associated with rock typing in hydrocarbon bearing reservoirs.;In this work, a numerical simulator has been used as the control environment in order to set up multiple studies that would demonstrate the differences between using conventional (current practices) approach of implementation of geologic models in the reservoir flow simulation studies and the new approach that is the subject of this study. By using the numerical reservoir simulator as the control environment it is intended to study the complexities that exist in upscaling the high resolution geological model using two different approaches.;The high resolution geological model used in its entirety and the flow simulation is performed. The results (production profiles) are compared to first, the upscaled model using conventional (current) practices and then the upscaled model using the proposed technique. The results are analyzed in order to demonstrate the difference between the two techniques and the advantages and disadvantages of each have been identified.

It has been known that the uncertainty of original oil in place (OOIP) is one of main challenges in proper reservoir development. The field has complex reservoir subunits, variable fluid contacts and structural and stratigraphic sand discontinuities. Therefore, reliable reservoir characterization and estimation of fluids in place requires an integrated approach of all available data of petrophysical evaluation, special core analysis (SCAL), geology, geophysics, reservoir rock typing (RRT), saturation height model (SHM) and fluid analysis. An innovative and integrated petrophysical evaluation have been studied and used in reservoir characterization. An advanced permeability log has been developed from porosity, clay bound, pore size, core and mobility data. It has used the modification of SHM that based on SCAL data including MICP, Centrifuge, Porous Plate and Relative Permeability data for every RRT and variable fluid contacts for subunits. An initial water saturation, and residual oil saturation from SCAL data have been used in evaluation. The pulse neutron capture and PLT have been used to verify fluid contacts and water saturation changes in complex sandstone reservoirs during production. The advanced integrated evaluation approach of subsurface and well test data has been used to provide reliable and good of reservoir properties and results on porosity, permeability, fluid contacts, reservoir rock typing and initial water saturation initial oil in place. For every reservoir subunits, the free water level (FWL) derived from formation pressure has been used to identify an initial oil water contact, and thus it has provided good comparison of Log-Sw and SHF derived Sw for reservoir modeling. The study has provided reliable reservoir characterization, reservoir modeling and for the development for multi-layer and complex sandstone reservoirs. Therefore the innovative integrated reservoir evaluation approach has provided reliable assurance and important benefits for reservoir characterization, optimization and reservoir management. The integrated approach presented in this paper presents an advanced step in the characterization of very flower shaped faulted complex reservoir. It has been utilized for the derivation of advanced permeability log as function of porosity, clay bound, pore size and mobility data per different rock types. Integration of available petrophysical, pressure, and SCAL data to derive the variable reservoir fluid contacts, and develop SHFs for fluids in place estimation and reservoir modeling purposes.

In this paper, the low-permeability reservoir was subdivided into several units based on three models; in the first model, porosity, permeability, pore sizes, and shale volume were used as an input in the heterogeneous rock analysis clustering workflow to define rock units; in the second model, rock types were defined using flow zone index. The third flow unit discriminator was proposed by the author; the model is based on relation between porosity, permeability, irreducible water saturation, and pore size distribution. Also, Wyllie–Rose equation for permeability in tight reservoir was core-calibrated, and coefficients e, d, and Kw were established. The reservoir is built of thin layers of sandstones with variable porosity, permeability, pore sizes, and irreducible water. The research was performed in two wells where as input well log data, the laboratory results of mercury injection porosimetry, permeability measurements, and nuclear magnetic resonance data were used. Furthermore, it was investigated whether the presence of fractures identified on XRMI images were strictly related to one flow unit.