Rock Typing Methods Research Articles

Decameter-Scale Flow-Unit Classification in Brazilian Presalt Carbonates

Summary Rock typing into flow units (FUs) plays a pivotal role in constructing static and dynamic models of petroleum reservoirs. Decisions made by asset teams mostly depend on predictions of how fluids will percolate through the subsurface during the reservoir life cycle. In carbonate settings, dealing with rock typing is complex and can generate a large quantity of units because of diagenetic processes such as dissolution, cementation, and silicification. Most rock-typing methods in carbonates successfully classify small-scale flow heterogeneity in well resolution but fail when interpolating those facies further away from the 1D domain, because of the lack of correlation between FUs and spatial data. Seismic data can be used to detect large-scale FUs and assist the interpolation of small-scale FUs in 3D reservoir volume, thus producing more-realistic static and dynamic models. We propose a modification of the classical rock-typing methods that use permeability (k) vs. porosity (ϕ) plots and electrical properties, with a data set from the Mero Field, part of the giant Libra Field of presalt carbonate reservoirs in offshore Brazil. From the permeability cumulative S-curve analysis, we established major large-scale FUs that maintain part of the carbonate flow heterogeneity and correlate them with the elastic attributes: P-impedance (PI) and S-impedance (SI). In addition, we established a priori PI and SI correlations with the formation-factor (FF) (F) parameter to categorize large-scale FUs using the F vs. k methodology. With the large-scale FUs mapped in seismic data sets, core-plug-scale FUs can be populated into the 3D static and dynamic models using geostatistics tools, thus creating more-realistic reservoir models and assisting asset teams in the decision-making process.

Rock typing from cored intervals to all wells with method of decision tree

Rock typing is a fundamental work in geology study of oil and gas field. Generally, it is difficult to define a quantitative relationship to expand the classification from cored intervals to all wells with the traditional method based on geologic origin analysis, when rock of complex pore structure is confronted. On the basis of conventional core analysis and well logs, the authors propose a workflow to extend rock typing from cores to all wells with the method of decision tree. In the study case of F oilfield from Middle East, the method and workflow not only predict the rock type on wells, but also get satisfying precision of permeability impetration. Therefore, when data used to quantify pore structure is scare and traditional rock typing method is impossible, the method and workflow founded on decision tree could be a universal alternative.

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

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.

K-Mean Cluster Analysis for Better Determining the Sweet Spot Intervals of the Unconventional Organic-Rich Shale: A Case Study

Abstract The petrophysical analysis is the crucial task for evaluating the quality of unconventional organic-rich shale and tight gas reservoirs. The presence of organic matter and the ultra-tight with over complex pore system have remained a lack of understanding of how to evaluate the extensive parameters of porosity considering organic content, gas saturation, organic richness, brittleness index, and sweet spot interval by only using conventional log. Therefore, this study offers effectively applied techniques and better analysis for interpreting these parameters by maximizing and integrating geological, geochemical, rock mechanical and engineering data. In general, the field data used in this study are from the first dedicated well for source rock exploration in the North Sumatra Basin, Indonesia. The developed method was derived by using conventional log. All interpretation results were validated by laboratory data measurements of routine and special core analysis, petrography, total organic carbon (TOC) and organic maturation, and brittleness index (BI) calculation. Moreover, the high quality of NMR log data was used as well to ensure our developed techniques present good estimations. Briefly about the methods, we started to determine the total and effective porosity based on the density log by including the presence of organic matter and multi-mineral analysis in these estimations. Then, we used the revised water saturation-TOC of water saturation while the TOC was predicted in advance by averaging three results from the correlation of TOC-Density, modified CARBOLOG and Passey’s ΔlogR methods. Equally important, in order to obtain the reliable gas saturation prediction, we used saturation exponent (n), cementation factor (m), and the tortuosity factor (a) parameters which obtained from laboratory measurement of formation resistivity factor and resistivity index (FFRI). In addition, the brittleness index was predicted based on sonic log data. Finally, all parameters needed for determining gas shale sweet spot have been made. Then, we developed a way to evaluate the sweet spot interval by using K-mean clustering. In conclusion, this clustering result properly follows the shale quality index parameters which consist of organic richness and maturation, brittleness index, the storage capacity of porosity and gas saturation. This study shows that these petrophysical applied techniques leads us to interpret the best position of shale interval to be developed with a simple, fast, and accurate prediction way. Furthermore, as a novelty, this method can be used as rock typing method and obviously can reduce uncertainty and risks in organic-rich shale exploration.

Study comparative rock typing methods to classify rock type carbonate reservoir Field “S” East Java

Challenges in the characterization of the carbonate reservoir are related to rock type and porosity. The permeability cannot be determined only by porosity. So the method that can be used to classify rock type and estimates the permeability is rock typing method. This study uses several rock typing methods that are Flow Zone Indicator (FZI), Winland R35, Pore Geometry Structure (PGS), and Lucia method. Core data from three wells have been applied in this study as reference wells. The objective is comparing those four methods and choose the best method for this study. There are two assessments in comparing. First, comparing the core permeability with predicted permeability on each method of rock typing. The result is the Winland R35 method has a better correlation between predicted permeability and core permeability, which have the value of the gradient is 0,9772, R2 is 0,9369 and RMS error is 62,14 mD. Second is by spreading the seismic parameters data to see the separation of each class in each method of rock typing. From this assessment, Lucia has a better distribution of seismic parameters. This assessment is more important than the first assessment. Therefore, Lucia is the best rock typing method in this study.

The effect of carbonate reservoir heterogeneity on Archie's exponents (a and m), an example from Kangan and Dalan gas formations in the central Persian Gulf

Calculating hydrocarbon in place is one of the most important aspects to be considered in reservoir evaluation. Carbonate rocks with high heterogeneity, exhibit significant changes in petrophysical and lithological properties. Archie's exponents (m and a) are basic parameters for saturation calculations. Uncertainties in obtaining these exponents lead to considerable errors in the saturation assessment. In this study, various pore and rock typing methods were carried out on a Permian–Triassic carbonate reservoir in the central Persian Gulf, Iran. The used methods include pore typing, pore facies classification, velocity deviation log, reservoir quality index, Winland R35, Pittman R35 and ranges of core permeability. Archie's exponents were obtained for different classes based on extracted data from petrographical studies, conventional core analysis and wire line log data. Results showed that determination of rock types based on pore typing has the greatest effect on the precise determination of Archie's exponents. On the other hand, the most unreliable results were related to the velocity deviation log. Pore types directly control the connectivity of the fluid pathways and so have the most important effect. Combining pore types in various groups such as velocity deviation or pore facies classification, reduce the measurement accuracy of Archie's exponents and resulted water saturation. Finally, it can be concluded that, in addition to the high impact of pore type on the accuracy of the obtained exponents, the permeability and pore throat radius are less effective in determining the Archie's exponents.

New Approach for Unconventional Reservoirs Rock Typing Characterization: Egyptian Unconventional Gas Reservoirs

The main objective of this research is to enhance unconventional reservoir characterization by developing and/or establishing new correlations through using a real case study of unconventional shale gas reservoir called Upper Safa formation that located in the western desert of Egypt. In addition to describing its geochemical and petro physical reservoir rock and fluid properties more consistently through a full integration among unconventional rock parameters as permeability, porosity, tortuosity, surface roughness, adsorption, type of kerosene, level of maturity, total organic carbon content, and etc. The results showed that Upper Safa formation is a shale gas unconventional resource play that consists mainly of Kaolinite clay and other mixed clay types. Geochemical pyrolysis analysis is used to confirm the presents of Kerogen type III as a shale gas potential reservoir. Interpretation analysis has been used also to confirm the presence of hydrocarbon potential in shale reservoirs depend on the readings that indicating most of shale play. Hence, after applying the surface roughness factor to Total gas in place equation through multiplying the (1-0.4) factor to volume of adsorbed gas in place to get new more accurate value for total gas in place TGIP’ equals 9.12 BCF. Moreover, brittleness ratio average value equals to 50% brittleness. However, TOC results which are obtained within the ranges of very good petroleum potential according to Rock Eval pyrolysis from 2% to 4% TOC. Hence, the results obtained from using of Dykstra Parson permeability variation, Upper Safa formation is highly heterogeneous formation which is very close to 100% heterogeneous formation, as any unconventional shale reservoirs due to the huge variation in the permeability ranges from milli-Darcy ranges to nano-Darcy ranges. Thus, several conventional and unconventional rock typing methods have been applied to overcome this zonation problem, besides establishing a new approach for unconventional reservoirs rock typing.

Modeling and simulation of transition zones in tight carbonate reservoirs by incorporation of improved rock typing and hysteresis models

Transition zones in tight heterogeneous carbonate reservoirs contain a considerable amount of original oil in place. Identifying and characterizing the petrophysical flow units of the transition zone is crucial for reserve estimation and performance prediction. This paper presents a petrophysical rock typing method based on decoding pore-size distributions from mercury injection capillary pressure (MICP) data by using Thomeer hyperboles, with proven application in a tight carbonate reservoir in the Middle East region. In this study, 150 MICP data sets were used which were type curve matched using Thomeer Hyperbolas with closure correction. Multivariate clustering method has been employed to divide the samples into a number of groups for the purpose of both representing the reservoir heterogeneity and simplifying rock typing for dynamic modeling. From the MICP curves, it has been found that mainly monomodal pore systems prevail in the targeted transition zone and five different rock types are identified. It has been observed that most of the pore throat types are meso and micro types with the negligible existence of nano-pore type. The intrinsic advantage of this rock typing method is to describe the pore system quantitatively, which is different from other rock typing methods based on the apparent poro-perm relationship. The comparison of the grouped data with the petrophysical properties showed that different pore-size distributions yield similar porosity and permeability values, reinforcing the importance of grouping rocks based on pore systems instead of their resulting properties. Additionally, a study has also been conducted to improve understanding on the relative permeability in transition zone by implementing an up-to-date model for the mix-wet condition. The work in this paper provides a guide for the further understanding of rock typing and modeling of transition zones in carbonate reservoirs.

Application of integrated rock typing and flow units identification methods for an Iranian carbonate reservoir

During the exploration phase of any oil and gas field, recognition of borehole type, its completion approach, and understanding of the future reservoir performance are directly interrelated to identification of the reservoir's rock types and flow units. Identifying different geological events, lithofacies characteristics, diagenetic processes, and level of heterogeneity can be the first step for knowing rock types and consequently flow units in its reservoir layers. These result in an acceptable dynamic model of a field development and relatively reliable production forecasts.Focus of this paper is on rock typing and flow unit classification for a carbonate reservoir of a green field. Four petrophysical methods including Rock Fabric Number (RFN), Winland porosity-permeability plot (R35), Reservoir Quality Index/Flow Zone Indicator (RQI/FZI), and Bulk Volume Water (BVW) were implemented on four exploration wells. At the next step graphical tools (Stratigraphic Modified Lorenz Plot (SMLP), Modified Lorenz Plot (MLP) and Stratigraphic Flow Profile (SFP) were used to locate established flow units and rock types within the reservoir column. Lastly, variation and frequency of defined flow units have been used to achieve a satisfactory understanding of the level of heterogeneity and the possible effect on well production.Integration of defined flow units by different methods inferred a high level of heterogeneity in the studied reservoir and the BVW was chosen as the best method of rock typing for feeding to the static model. The BVW method assists in considering main variation of reservoir properties meanwhile avoid complexity of models. During modelling, choosing an optimum number of rock types for fine-grid model with small dimensions cells (50 m*50 m*1 m) can help to separate different layers vertically without necessity of dividing them to many distinct subzones. Usually, groping numerous subzones during up scaling is confusing and complicate; likewise, in a coarse grid may omit or mix some frequency of thin seal and productive subintervals in reservoir zones. Comparing achieved flow unit classification with outcomes of production test showed in this reservoir with high level of heterogeneity an adequate type of well is vertical and highly deviated ones, moreover, dual completion can be the best type of production which separate high and low productive zones.

An integrated workflow to characterize and evaluate low resistivity pay and its phenomenon in a sandstone reservoir

The identification, characterization and evaluation of low resistivity pay is very challenging and important for the development of oil and gas fields. Proper identification and characterization of these reservoirs is essential for recovering their reserves. There are many reasons for low resistivity pay zones. It is crucial to identify the origin of this phenomenon. This paper deals with the identification, characterization and evaluation of low resistivity hydrocarbon-bearing sand reservoirs in order to understand the low resistivity phenomenon in a sandstone reservoir, the characterization of the rock types and how to conduct petrophysical analysis to accurately obtain petrophysical properties. An integrated workflow based on petrographical, rock typing and petrophysical methods is conducted and applied. From the integrated analysis that was performed, the presence of illite and a mixed layer of illite–smectite clay minerals in sandstone formation and pyrite–siderite conductive minerals was identified as one of the main reasons for low resistivity occurence in sandstone reservoirs. These clay minerals are distributed as a laminated–dispersed shale distribution model in sandstone reservoirs. The dual water method is recommended to calculate water saturation in low resistivity hydrocarbon-bearing sand reservoirs as this method is more accurate and does not result in an over estimation in water saturation calculation.

Inspecting the Reservoir Characteristics of the Burgan Formation of Soroosh Oil Field Applying Rock Typing Methods in the Context of Geological Studies

The Albian age Burgan Formation is one of the most important siliciclastic reservoirs in the Arabian Plate. Northwest of Persian Gulf is the main area in Iran invaded by these siliciclastic sediments. This study uses a new and comprehensive procedure to identify the reservoir characteristics of the Burgan Formation in Soroush oil field (NW Persian Gulf). Results from core and petrographic studies led identification of 7 microfacies (MF1 to MF7) that are grouped into 3 main facies association (FA1, to FA3). Results from reservoir characterization indicate a dramatic decrease in reservoir quality from bottom to top (FA1 toward FA3). Using the Flow Zone Indicator (FZI) method, 5 Hydraluic flow units (HFUs) were recognized in the formation. The HFUs are in a notable accordance with facies associations. The HFUs 1 and 2 correlate with theFA1, the HFUs 3 and 4 with the FA2 and the HFU5 cover intervals defined by FA3. Cluster analysis of wireline logs resulted in determination of 5 electrofacies (EF1 to EF5) which are in agreement with the ascertained HFUs. Inspecting the vertical distribution of FAs, HFUs and EFs, three distinct zones are determined. The lower zone is characterized by good reservoir quality, abundance of FA1, HFUs1 and 2 and also EFs 1 and 2 is observed there. The middle zone with a moderate reservoir quality and upper zone presents the poorest quality. In the middle zone FA2, HFUs3 and 4 and also EFs 3 and 4 are more abundant while in the upper one interval are clearly correlated with FA3, HFU5 and also EF5.

Petrophysics Analysis for Reservoir Characterization of Upper Plover Formation in the Field “A”, Bonaparte Basin, Offshore Timor, Maluku, Indonesia

Hydrocarbon potential within Upper Plover Formation in the Field “A” has not been produced due to unclear in understanding of reservoir problem. This formation consists of heterogeneous reservoir rock with their own physical characteristics. Reservoir characterization has been done by applying rock typing (RT) method utilizing wireline logs data to obtain reservoir properties including clay volume, porosity, water saturation, and permeability. Rock types are classified on the basis of porosity and permeability distribution from routines core analysis (RCAL) data. Meanwhile, conventional core data is utilized to depositional environment interpretations. This study also applied neural network methods to rock types analyze for intervals reservoir without core data. The Upper Plover Formation in the study area indicates potential reservoir distributes into 7 parasequences. Their were deposited during transgressive systems in coastal environments (foreshore - offshore) with coarsening upward pattern during Middle to Late Jurassic. The porosity of reservoir ranges from 1–19 % and permeability varies from 0.01 mD to 1300 mD. Based on the facies association and its physical properties from rock typing analysis, the reservoir within Upper Plover Formation can be grouped into 4 reservoir class: Class A (Excellent), Class B (Good), Class C (Poor), and Class D (Very Poor). For further analysis, only class A-C are considered as potential reservoir, and the remain is neglected.

Bayesian rock classification and petrophysical uncertainty characterization with fast well-log forward modeling in thin-bed reservoirs

Rock typing is critical in deepwater reservoir characterization to construct stratigraphic models populated with static and dynamic petrophysical properties. Rock typing based on multiple well logs is subject to large uncertainty in thinly bedded reservoirs because true physical properties cannot be resolved by low-resolution logging tools due to shoulder-bed effects. We have introduced a new Bayesian approach that inherently adopts the scientific method of iterative hypothesis testing to perform rock typing by simultaneously honoring different logging-tool physics in a multilayered earth model. In addition to estimating the vertical distribution of rock types with maximum likelihood, the Bayesian method quantifies the uncertainty of rock types and the associated petrophysical properties layer by layer. Bayesian rock classification is performed with a fast sampling technique based on the Markov-chain Monte Carlo method, thereby enabling an efficient search of rock types to obtain the final results. We have used a fast linear iterative refinement method to simulate nuclear logs and a 2D forward modeling code to simulate array-induction resistivity logs. A rock-type distribution hypothesis is considered acceptable only when all the observed well logs are reproduced with forward modeling. In a field case of offshore deltaic gas reservoir, the Bayesian method differentiates rock types that exhibit subtle petrophysical variations due to grain size change. The new method provides more than 77% agreement between log- and core-derived rock types, whereas conventional deterministic methods achieve only 60% agreement due to the presence of thin beds and laminations. Even though large uncertainty is observed in thinly bedded and laminated zones, the Bayesian rock-typing method still yields rock types and petrophysical properties that agree well with core-plug measurements acquired in these layers. As a result, the overall correlation between log-derived permeability and core-measured permeability is improved by approximately 16% when compared with conventional deterministic methods.

Application of Conventional Well Logs To Characterize Spatial Heterogeneity in Carbonate Formations Required for Prediction of Acid-Fracture Conductivity

SummaryAcid etching, as the consequence of heterogeneous distribution of petrophysical and compositional properties, results in the conductivity of acid fractures in carbonate reservoirs. Reliable characterization of small-scale formation spatial heterogeneity by use of geostatistical analysis (i.e., variogram analysis) can improve prediction of acid-fracture conductivity significantly. Previous publications suggest that permeability correlation length can be used to assimilate spatial heterogeneity in prediction of acid-fracture conductivity. Well logs are good candidates to provide information about petrophysical and compositional properties of the formation with the required resolution for prediction of acid-fracture conductivity. However, the assessment of permeability and mineralogy from conventional well logs is challenging because of high spatial heterogeneity and complex pore structure. Rock typing has been suggested in the literature to improve permeability assessment in carbonates. Most of the previously introduced rock-typing methods are dependent on core measurements. However, core data are generally sparse and not available with the sampling rate required for prediction of acid-fracture conductivity.The main objective of this paper is to quantify formation spatial heterogeneity with variogram analysis of well logs and well-log-based estimates of petrophysical and compositional properties in carbonate reservoirs. We introduce an iterative permeability-assessment technique that is based on well logs, which takes into account characteristics of different rock classes in the reservoir. Furthermore, we propose three rock-classification techniques that are based on conventional well logs and that take into account static and dynamic petrophysical properties of the formation as well as mineral composition.We applied the proposed techniques successfully in two carbonate formations—Happy Spraberry oil field and Hugoton gas field. The petrophysical rock classification is in good agreement with identified core-derived rock classes. The results show approximately 54% improvement in permeability assessment compared with conventional permeability-assessment techniques, which can improve prediction of acid-stimulation jobs significantly. Finally, we investigated the direct application of well logs and well-log-based estimates of petrophysical and compositional properties for variogram analysis required to characterize formation spatial heterogeneity. We conducted variogram analysis in both field examples. The results show that the direct application of well logs and well-log-based estimates of petrophysical/compositional properties is reliable to characterize formation spatial heterogeneity. We also showed that application of well logs can enhance assessment of spatial heterogeneity compared with core measurements.

Integration of rock typing methods for carbonate reservoir characterization

Reservoir rock typing is the most important part of all reservoir modelling. For integrated reservoir rock typing, static and dynamic properties need to be combined, but sometimes these two are incompatible. The failure is due to the misunderstanding of the crucial parameters that control the dynamic behaviour of the reservoir rock and thus selecting inappropriate methods for defining static rock types. In this study, rock types were defined by combining the SCAL data with the rock properties, particularly rock fabric and pore types. First, air-displacing-water capillary pressure curues were classified because they are representative of fluid saturation and behaviour under capillary forces. Next the most important rock properties which control the fluid flow and saturation behaviour (rock fabric and pore types) were combined with defined classes. Corresponding petrophysical properties were also attributed to reservoir rock types and eventually, defined rock types were compared with relative permeability curves. This study focused on representing the importance of the pore system, specifically pore types in fluid saturation and entrapment in the reservoir rock. The most common tests in static rock typing, such as electrofacies analysis and porosity–permeability correlation, were carried out and the results indicate that these are not appropriate approaches for reservoir rock typing in carbonate reservoirs with a complicated pore system.

Pore System Characterization and Petrophysical Rock Classification Using a Bimodal Gaussian Density Function

This paper introduces a bimodal Gaussian density function to characterize pore-size distributions in terms of incremental pore volume versus logarithmic pore-throat radius. An inverse problem is formulated and solved to reconstruct mercury injection capillary pressure curves by enforcing a bimodal Gaussian pore-size distribution. The bimodal Gaussian model generates six petrophysically interpretable attributes which provide a quantitative basis for petrophysical modeling and rock typing. Correlations between these attributes and their associated petrophysical properties are investigated to verify interpretations. In the field case, the correlation coefficient (R2) between absolute permeability, end-point gas relative permeability and the mean value of large pore-throat size mode are 0.93 and 0.715, respectively. Correlation (R2=0.613) is also observed between critical water saturation and pore volume connected by small pore-throat sizes. Petrophysical modeling based on the bimodal Gaussian pore-size distribution with sufficient core data calibration predicts static and dynamic petrophysical properties that are in agreement with laboratory core measurements. The quantitative pore-system description underlies a new petrophysical rock typing method that combines all relevant pore-system attributes. Verification of the method was performed with field data from two key wells in the Hugoton carbonate gas field, Kansas.

FLOW UNIT DISTRIBUTION AND RESERVOIR MODELLING IN CRETACEOUS CARBONATES OF THE SARVAK FORMATION, ABTEYMOUR OILFIELD, DEZFUL EMBAYMENT, SW IRAN

Carbonate sediments within the Mid‐Cretaceous Sarvak Formation form an important reservoir at the Abteymour oilfield in the western Dezful Embayment, SW Iran. The poroperm characteristics of this reservoir were controlled by factors including deposition under tropical climatic conditions and early diagenesis, repeated phases of subaerial exposure due to local, regional and global‐scale tectonism, and diagenetic modification during burial. From microfacies analysis, the Sarvak Formation carbonates in the Abteymour field were interpreted in a previous study as having been deposited on a homoclinal ramp‐type platform. Three third‐order sequences were recognized in the middle Cenomanian to middle Turonian part of the formation. The reservoir quality of the carbonates was enhanced both by dissolution (comprising separate phases of eogenetic and telogenetic meteoric dissolution) and dolomitization (especially stylolite‐related dolomitization).In this paper, a rock/pore type approach was used in order to integrate petrophysical data with facies and diagenetic models within a sequence stratigraphic framework. Two different rock‐typing methods for the determination of flow units were considered. Hydraulic flow units (HFUs) were identified firstly using flow zone indicators and secondly using a stratigraphic modified Lorenz plot. The flow units resulting from these two methods are compared, and their close correspondence within the sequence stratigraphic framework is discussed. In addition, the previously‐used large‐scale reservoir zonation scheme for the Abteymour field is correlated with the defined flow units, and four new Integrated Reservoir Zones are introduced. By integrating geological information with petrophysical parameters (including porosity, permeability and saturation) within a sequence stratigraphic framework, field‐scale variations and controls on reservoir quality are described.