scholarly journals Comparative Permeability Estimation Method and Identification of Rock Types using Cluster Analysis from Well Logs and Core Analysis Data in Tertiary Carbonate Reservoir-Khabaz Oil Field

2019 ◽  
Vol 25 (12) ◽  
pp. 49-61
Author(s):  
Adnan Ajam Abed ◽  
Sammer Mohammed Hamd-Allah
Keyword(s):  
Cluster Analysis ◽  
Carbonate Reservoir ◽  
Flow Unit ◽  
Well Logs ◽  
Analysis Approach ◽  
Flow Zone ◽  
Hydraulic Flow ◽  
Rock Types ◽  
Flow Units ◽  
Reservoir Zonation

Characterization of the heterogonous reservoir is complex representation and evaluation of petrophysical properties and application of the relationships between porosity-permeability within the framework of hydraulic flow units is used to estimate permeability in un-cored wells. Techniques of flow unit or hydraulic flow unit (HFU) divided the reservoir into zones laterally and vertically which can be managed and control fluid flow within flow unit and considerably is entirely different with other flow units through reservoir. Each flow unit can be distinguished by applying the relationships of flow zone indicator (FZI) method. Supporting the relationship between porosity and permeability by using flow zone indictor is carried out for evaluating the reservoir quality and identification of flow unit used in reservoir zonation.  In this study, flow zone indicator has been used to identify five layers belonging to Tertiary reservoirs. Consequently, the porosity-permeability cross plot has been done depending on FZI values as groups and for each group denoted to reservoir rock types. On the other hand, extending rock type identification in un-cored wells should apply a cluster analysis approach by using well logs data. Reservoir zonation has been achieved by cluster analysis approach and for each group known as cluster which variation and different with others. Five clusters generated in this study and permeability estimated depend on these groups in un-cored wells by using well log data that gives good results compared with different empirical methods.

scholarly journals Rock typing based on hydraulic and electric flow units for reservoir characterization of Nubia Sandstone, southwest Sinai, Egypt

2021 ◽  
Author(s):  
Abdel Moktader A. El-Sayed ◽  
Nahla A. El Sayed ◽  
Hadeer A. Ali ◽  
Mohamed A. Kassab ◽  
Salah M. Abdel-Wahab ◽  
...  
Keyword(s):  
Iron Oxides ◽  
Reservoir Characterization ◽  
Flow Unit ◽  
Reservoir Quality ◽  
Thin Sections ◽  
Hydraulic Flow ◽  
Rock Types ◽  
Flow Units ◽  
Reservoir Quality Index ◽  
Hydraulic Flow Units

AbstractThe present work describes and evaluates the reservoir quality of the sandstone of the Nubia Formation at the Gebel Abu Hasswa outcrop in southwest Sinai, Egypt. Hydraulic flow unit (HFU) and electrical flow unit (EFU) concepts are implied to achieve this purpose. The Paleozoic section made up of four formations has been studied. The oldest is Araba Formation followed by Naqus formations (Nubia C and D) overlay by Abu Durba, Ahemir and Qiseib formations (Nubia B), where the Lower Cretaceous (Nubia A) is represented by the Malha Formation. The studied samples have been collected from Araba, Abu Durba, Ahemir and the Malha formations. The hydraulic flow unit (HFU) discrimination was carried out based on permeability and porosity relationship, whereas the electrical flow unit (EFU) differentiation was carried out based on the relationship between formation resistivity factor and porosity. Petrographic investigation of the studied thin sections illustrates that the studied samples are mainly quartz arenite. Important roles to enhance or reduce the pore size and/or pore throats controlling the reservoir petrophysical behavior are due to the diagenetic processes. The present study used the reservoir quality index (RQI) and Winland R35 as additional parameters applied to discriminate the HFUs. The study samples have five hydraulic flow units of different rock types, where the detected electrical flow units are only three. The differences between them are may be due to the cementation process with iron oxides that might act as pore filling, lining and pore bridging, sometimes bridges helping to decrease permeability without serious reduction in porosity. The reduction between the number of EFUs and HFUs comes from the effect of diagenesis processes which is responsible for a precipitation of different cement types such as different clay minerals and iron oxides.

scholarly journals Predicting the flow zone indicator of carbonate reservoirs using NMR echo transforms, and routine open-hole log measurements: Insights from a field case study spanning extreme micro-structure properties

2021 ◽  
Author(s):  
Mabkhout Al-Dousari ◽  
◽  
Salah Almudhhi ◽  
Ali A. Garrouch ◽  
◽  
...  
Keyword(s):  
Relative Error ◽  
Carbonate Reservoir ◽  
Micro Structure ◽  
Flow Zone ◽  
Hydraulic Flow ◽  
Absolute Relative Error ◽  
Flow Units ◽  
Average Absolute Relative Error ◽  
Open Hole ◽  
Hydraulic Flow Units

Predicting the flow zone indicator is essential for identifying the hydraulic flow units of hydrocarbon reservoirs. Delineation of hydraulic flow units is crucial for mapping petrophysical and rock mechanical properties. Precise prediction of the flow zone indicator (FZI) of carbonate rocks using well log measurements in un-cored intervals is still a daunting challenge for petrophysicists. This study presents a data mining methodology for predicting the rock FZI using NMR echo transforms, and conventional open-hole log measurements. The methodology is applied on a carbonate reservoir with extreme microstructure properties, from an oil “M” field characterized by a relatively high-permeability with a median of approximately 167 mD, and a maximum of 3480 mD. The reservoir from the M field features detritic, or vuggy structure, covering a wide range of rock fabrics varying from microcrystalline mudstones to coarse-grained grainstones. Porosity has a median of approximately 22%. Dimensional analysis and regression analysis are applied for the derivation of four transforms that appear to capture approximately 80% of the FZI variance. These four transforms are formulated using the geometric mean of the transverse NMR relaxation time (T2lm), the ratio of the free fluid index (FFI) to the bulk volume irreducible (BVI), the bulk density, the sonic compressional travel time, the true resistivity, the photo-electric absorption, and the effective porosity. Non-linear regression models have been developed for predicting the FZI using the derived transforms, for the carbonate reservoir from the M field. The average relative error for the estimated FZI values is approximately 52%. The same transforms are used as input for training a developed general regression neural network (GRNN), built for the purpose of predicting rock FZI. The constructed GRNN predicts FZI with a notable precision. The average absolute relative error on FZI for the training set is approximately 3.1%. The average absolute relative error on FZI for the blind testing set is approximately 22.0 %. The data mining approach presented in this study appears to suggest that (i) the relationship between the flow zone indicator and open-hole log attributes is highly non-linear, (ii) the FZI is highly affected by parameters that reflect rock texture, rock micro-structure geometry, and diagenetic alterations, and (iii) the derived transforms provide a means for further enhancement of the flow zone indicator prediction in carbonate reservoirs.

Application of hydraulic flow unit for prediction of flow zone in carbonate reservoir

2021 ◽  
Vol 14 (8) ◽  
Author(s):  
Nirlipta Priyadarshini Nayak ◽  
Harinandan Kumar ◽  
Shivani Bhist
Keyword(s):  
Carbonate Reservoir ◽  
Flow Unit ◽  
Flow Zone ◽  
Hydraulic Flow

scholarly journals PETROPHYSICAL CHARACTERIZATION OF ALBIAN CARBONATE RESERVOIR IN CAMPOS BASIN USING A MULTIVARIATE APPROACH WITH WELL LOGS AND LABORATORY MEASUREMENTS

2018 ◽  
Vol 36 (2) ◽  
pp. 123
Author(s):  
Antonio Abel Carrasquilla ◽  
Raphael Ribeiro Silva
Keyword(s):  
Cluster Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Water Saturation ◽  
Laboratory Data ◽  
Carbonate Reservoir ◽  
Well Logs ◽  
Flow Units ◽  
Rock Typing ◽  
Campos Basin

ABSTRACT. This study characterizes an Albian carbonate reservoir of Field B in the Campos Basin, based on geophysical well logs and laboratory petrophysical data. This permitted us to estimate the porosity, permeability and water saturation of this reservoir more reliably. In order to achieve this goal, the Cluster Analysis for Rock Typing module of the Interactive Petrophysics software was used to divide the well into electrofacies. For each of them, an equation was determined to find the porosity and the permeability, using the multiple linear regression technique, using as input the log data and as target the laboratory data. The obtained results were compared with different models proposed by other authors, with the best results being found with multiple linear regression. Water saturation, on the other hand, was estimated by Archie equation after identifying the cementation coefficient with the Pickett crossplot. Finally, the porosity and permeability data were again used to now identify three main flow units in the reservoir through the Winland graph. To verify the effectiveness of the adopted methodology, it was successfully applied in a blind test, defining poros-ity, permeability, water saturation and flow units in a well without laboratory data. Keywords: well logging, Field B, petrophysics, carbonate reservoir, Albian.RESUMO. Este estudo caracteriza um reservatório carbonático Albiano do Campo B na Bacia de Campos, a partir de dados de perfis de poço e de petrofísica de laboratório. Uma estimativa da porosidade, da permeabilidade e da saturação de água de forma mais confiável. Com ese objetivo, foi usado o módulo Cluster Analysis for Rock Typing do software Interactive Petrophysics para dividir o poço em eletrofácies. Para cada uma delas, foi determinada uma equação para a porosidade e a perme-abilidade, através da técnica de regressão linear múltipla, usando como entrada os dados de perfis de poço e como alvo os dados de laboratório. Esses resultados foram comparados com modelos propostos por outros autores, sendo os melhores aqueles obtidos com regressão linear múltipla. A saturação de água foi estimada com a Equação de Archie após identificar o coeficiente de cimenta-ção com o crossplot de Pickett. Finalmente, os dados de porosidade e permeabilidade foram usados para identificar três unidades de fluxo através do gráfico de Winland. Para verificar a eficácia da metodologia adotada, a mesma foi aplicada com sucesso num teste cego, definindo a porosidade, a permeabilidade, a saturação de água e as unidades de fluxo num poço sem dados de laboratório. Palavras-chave: perfis de poços, Campo B, petrofísica, reservatório carbonático, Albiano.   

Improved Prediction of Reservoir Behavior Through Integration of Quantitative Geological and Petrophysical Data

1999 ◽  
Vol 2 (02) ◽  
pp. 149-160 ◽  
Author(s):  
D.K. Davies ◽  
R.K. Vessell ◽  
J.B. Auman
Keyword(s):  
Body Size ◽  
Reservoir Characterization ◽  
Rock Type ◽  
Carbonate Reservoir ◽  
High Porosity ◽  
Geometrical Characteristics ◽  
Rock Types ◽  
Flow Units ◽  
Reservoir Description ◽  
Pore Body

Summary This paper presents a cost effective, quantitative methodology for reservoir characterization that results in improved prediction of permeability, production and injection behavior during primary and enhanced recovery operations. The method is based fundamentally on the identification of rock types (intervals of rock with unique pore geometry). This approach uses image analysis of core material to quantitatively identify various pore geometries. When combined with more traditional petrophysical measurements, such as porosity, permeability and capillary pressure, intervals of rock with various pore geometries (rock types) can be recognized from conventional wireline logs in noncored wells or intervals. This allows for calculation of rock type and improved estimation of permeability and saturation. Based on geological input, the reservoirs can then be divided into flow units (hydrodynamically continuous layers) and grid blocks for simulation. Results are presented of detailed studies in two, distinctly different, complex reservoirs: a low porosity carbonate reservoir and a high porosity sandstone reservoir. When combined with production data, the improved characterization and predictability of performance obtained using this unique technique have provided a means of targeting the highest quality development drilling locations, improving pattern design, rapidly recognizing conformance and formation damage problems, identifying bypassed pay intervals, and improving assessments of present and future value. Introduction This paper presents a technique for improved prediction of permeability and flow unit distribution that can be used in reservoirs of widely differing lithologies and differing porosity characteristics. The technique focuses on the use and integration of pore geometrical data and wireline log data to predict permeability and define hydraulic flow units in complex reservoirs. The two studies presented here include a low porosity, complex carbonate reservoir and a high porosity, heterogeneous sandstone reservoir. These reservoir classes represent end-members in the spectrum of hydrocarbon reservoirs. Additionally, these reservoirs are often difficult to characterize (due to their geological complexity) and frequently contain significant volumes of remaining reserves.1 The two reservoir studies are funded by the U.S. Department of Energy as part of the Class II and Class III Oil Programs for shallow shelf carbonate (SSC) reservoirs and slope/basin clastic (SBC) reservoirs. The technique described in this paper has also been used to characterize a wide range of other carbonate and sandstone reservoirs including tight gas sands (Wilcox, Vicksburg, and Cotton Valley Formations, Texas), moderate porosity sandstones (Middle Magdalena Valley, Colombia and San Jorge Basin, Argentina), and high porosity reservoirs (Offshore Gulf Coast and Middle East). The techniques used for reservoir description in this paper meet three basic requirements that are important in mature, heterogeneous fields.The reservoir descriptions are log-based. Flow units are identified using wireline logs because few wells have cores. Integration of data from analysis of cores is an essential component of the log models.Accurate values of permeability are derived from logs. In complex reservoirs, values of porosity and saturation derived from routine log analysis often do not accurately identify productivity. It is therefore necessary to develop a log model that will allow the prediction of another producibility parameter. In these studies we have derived foot-by-foot values of permeability for cored and non-cored intervals in all wells with suitable wireline logs.Use only the existing databases. No new wells will be drilled to aid reservoir description. Methodology Techniques of reservoir description used in these studies are based on the identification of rock types (intervals of rock with unique petrophysical properties). Rock types are identified on the basis of measured pore geometrical characteristics, principally pore body size (average diameter), pore body shape, aspect ratio (size of pore body: size of pore throat) and coordination number (number of throats per pore). This involves the detailed analysis of small rock samples taken from existing cores (conventional cores and sidewall cores). The rock type information is used to develop the vertical layering profile in cored intervals. Integration of rock type data with wireline log data allows field-wide extrapolation of the reservoir model from cored to non-cored wells. Emphasis is placed on measurement of pore geometrical characteristics using a scanning electron microscope specially equipped for automated image analysis procedures.2–4 A knowledge of pore geometrical characteristics is of fundamental importance to reservoir characterization because the displacement of hydrocarbons is controlled at the pore level; the petrophysical properties of rocks are controlled by the pore geometry.5–8 The specific procedure includes the following steps.Routine measurement of porosity and permeability.Detailed macroscopic core description to identify vertical changes in texture and lithology for all cores.Detailed thin section and scanning electron microscope analyses (secondary electron imaging mode) of 100 to 150 small rock samples taken from the same locations as the plugs used in routine core analysis. In the SBC reservoir, x-ray diffraction analysis is also used. The combination of thin section and x-ray analyses provides direct measurement of the shale volume, clay volume, grain size, sorting and mineral composition for the core samples analyzed.Rock types are identified for each rock sample using measured data on pore body size, pore throat size and pore interconnectivity (coordination number and pore arrangement).

Integrating XRD and Well Logging Data to Establish Electro-Facies and Permeability Models for an Unconventional Heterogeneous Tight Gas Reservoir, Obaiyed Giant Gas Field

2021 ◽  
Author(s):  
Ibrahim Mabrouk
Keyword(s):  
Development Strategy ◽  
Flow Unit ◽  
Petrographic Analysis ◽  
Production Forecast ◽  
Gas Field ◽  
Hydraulic Flow ◽  
Heterogeneous Reservoirs ◽  
Flow Units ◽  
Tight Gas Reservoir ◽  
Hydraulic Flow Units

Abstract Formation evaluation in heterogeneous reservoirs can be very challenging especially in fields that extend over several kilometers in area where the permeability varies from 0.1 mD up to 1000 D within the same porosity. The porosity, hydrocarbon saturation and net sand thickness in most of Obaiyed field wells are consistent; hence, the productivity of these wells is enormously dependent on the reservoir permeability. Since the permeability is highly heterogeneous, initial production rate of the wells varies between few MMSCFD to almost one hundred MMSCFD. The huge permeability variation led to a tremendous uncertainty in the dynamic modeling, which resulted in an inaccurate production forecast affecting the field economics estimation. Understanding permeability distribution and heterogeneity in Obaiyed field is the key factor for establishing a realistic permeability model, which will lead to a successful field development strategy. Extensive work was performed to understand key factors that govern the permeability in Obaiyed using the data of 1-kilometer length of cores acquired in more than 50 wells covering different reservoir properties in the field. Core data were used to separate the reservoir into different Hydraulic Flow Units (HFU) according to Amaefule's work performed on the Kozeny-Carmen model. Afterwards, a correlation between the HFU and well logs was established using IPSOM Electro-Facies module in order to define the flow units in un-cored wells. The result of this correlation was used to calibrate a Porosity-Permeability relationship for each flow unit. The next step was examining the clay-type distribution and diagenesis in each flow unit using the petrographic analysis (XRD) results from the core xdata. All factors controlling the permeability can now be represented in hydraulic flow units which are considered as a method of measurement of the reservoir quality. Consequently, property maps were constructed showing the location and continuity of each of the flow units, leading to a more deterministic approach in the well placement process. Based on this new work methodology, a production cut-off criteria relating the reservoir productivity to both clay minerals presence and percentages was established for multiple wells scenarios. As a result, the development strategy of the field changed from only vertical wells to include horizontal wells as well which proved to be the only economic approach to produce the Illite dominated zones. This paper presents a workflow to provide a representative estimation of permeability in extremely heterogeneous reservoirs especially the ones dominated by complex clay distribution.

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