Interpretation Of Logging Data Research Articles

Evaluation of Hydrocarbon Reservoir in the “SIMA” Field of Niger Delta Nigeria from Interpretation of 3D Seismic and Petrophysical Log Data

3D seismic and petrophysical log data interpretation of reservoir sands in “SIMA” Field, onshore Niger Delta has been undertaken in this study to ascertain the reservoir characteristics in terms of favourable structural and petrophysical parameters suitable for hydrocarbon accumulation and entrapment in the field. Horizon and fault interpretation were carried out for subsurface structural delineation. In all, seven faults (five normal and two listric faults) were mapped in the seismic section. These faults were major structure building faults corresponding to the growth and antithetic faults in the area within the well control. The antithetic fault trending northwest-southeast and the normal fault trending northeast-southwest on the structural high in the section act as good trapping mechanisms for hydrocarbon accumulations in the reservoir. From the manual and auto-tracking methods applied, several horizons were identified and mapped. The section is characterized by high amplitude with moderate-to-good continuity reflections appearing parallel to sub-parallel, mostly disturbed by some truncations which are more fault related than lithologic heterogeneity. The southwestern part is, however, characterized by low-to-high or variable amplitude reflections with poor-to-low continuity. Normal faults linked to roll-over anticlines were identified. Some fault truncations were observed due to lithologic heterogeneity. The combination of these faults acts as good traps for hydrocarbon accumulations in the reservoir. Reservoir favourable petrophysical qualities, having average NTG, porosity, permeability and water saturation of 5 m, 0.20423, 1128.219 kD and 0.458 respectively.

Accounting for tilted electrical anisotropy in numerical simulation and interpretation of resistivity logging data (analytical review based on national and foreign literature)

Features and main conclusions of publications devoted to the study of medium transverse-isotropic geoelectric models which are characterized by inclination of the electrical anisotropy axis relative to a logging tool are reviewed in this article. Such models can be defined either by horizontal and vertical conductivities (or their reciprocals, called resistivities) with a non-zero dip of a logging tool or by the conductivity tensor with the tilt of the principal axes.

The Mishrif Reservoir Characteristics Utilizing Well Log Data Interpretation in the Fauqi Oilfield in Maysan, Southern Iraq

The Mishrif Formation was deemed the main oil reservoir in the Fauqi oilfield, southern Iraq. This paper aims to predict characteristic properties of the Mishrif Formation depending on the interpretation of well logs data. The data were collected from five wells of log images which had been digitized with Didger software version 5. 12. 1762 to be analyzed and interpreted using interactive petrophysics 3.5.1.2 software. The main lithology of the Mishrif Formation in this region was determined using standard (M-N xplot) based on the integration of density-neutron logs. The results confirmed that the Mishrif Formation is mainly composed of limestone units. A Gamma-ray log was used to estimate the shale volume in the Mishrif Formation depending on old rock function. As a result, shale volume relative to the bulk volume was about 19%, and an increasing volume was noticed in the upper reservoir, reaching the highest in the MA and MB11 units. The Mishrif Formation porosity was calculated using the interpretation of neutron, density, and sonic logs. The results showed that the Mishrif Formation is distinctive with low to medium porosity values (4.8 to 17%). The calculation of cores manifested the dominance of secondary porosity in the MB21 unit of the formation in comparison to the other stratigraphic units in the studied area. These results led to a the fact that the MB21 unit was more exposed to dissolution diagenetic processes in the south dome, which provided a good permeability integrated with the medium effective porosity, puttinh it as the main reservoir unit.

The Asmari Formation Petrophysical Parameters in the Abu Ghirab Oil Field of the Zagros Fold Belt Basin, Southeastern Iraq, Using Well Log Data Interpretation

The current study represents the evaluation of petrophysical characteristics, lithological analysis, and identification of the Asmari Formation for the main and sub-reservoir units in the Abu Ghirab oil field, Maysan, southeast of Iraq. This petrophysical assessment was accomplished using the interpretations of well log data to know the properties of the Asmari Formation reservoir. The available logs such as resistivity, gamma ray, neutron and density logs were converted to digital data using the Diger Sotware. The lithic properties of the reservoir like porosity, total shale saturation, oil and water saturation were interpreted and calculated using the interactive petrophysics software. The lithic and mineral study was completed and the type of mineral filling was known through the cross-plot of the porosity logs for different wells. The petrophysical properties were calculated and represented on the CPI profile. Depending on the petrophysical characteristics, the Asmari Formation was divided into main and sub units, which are: Jeribe-Euphrates and its sub-units A1, A2, and A3; Upper Kirkuk unit and B1, B2, B3, B4 sub-units; and Middle-Lower Kirkuk unit and C subunit. The results showed that the reservoir has economic oil productivity. The subunits B2, B3 in Upper Kirkuk were characterized by high effective porosity values and high hydrocarbon content, and they are the highest produced units in Upper Kirkuk in studied wells. The vary on lithology represents as dolomites in the Jeribe, Euphrates, limestones in the Kirkuk group, and the mineral components were calcite and dolomite.

A practical approach to develop a proper anisotropic rock physics model for media comprising of multiple fracture sets in the absence of sophisticated laboratory/wireline data

For economical production from a fractured reservoir, a characteristic analysis of the fracture parameters like its density and orientation within the reservoir is essential to improve the fluid flow during extraction. This study deals with the development of a proper anisotropic rock physics model for a media with multiple fracture sets to study the spatial distribution of important fracture parameters i.e., fracture density and orientation in the absence of sophisticated laboratory/wireline and pre-stack seismic data. The crest of hydrocarbon producing fault-bounded Balkassar Anticline in Northern Potwar, Upper Indus Basin, Pakistan is selected as a case study representing a potential zone for development of fractures at reservoir level (Sakesar Limestone). The methodology consists of the interpretation of 3D post-stack seismic and conventional wireline log data to demarcate the reservoir containing fractures. The Ant-tracking discrete fracture network (DFN) attribute is applied on 3D post-stack seismic data to obtain an initial estimate about the presence of fracture corridors and their orientations. Based on this initial estimate, a proper rock physics model has been developed utilizing inverse Gassmann relations, T-matrix approximation, and Brown and Korringa relations. The output from the developed rock physics model has been displayed in the form of 13 effective independent elastic stiffness constants (monoclinic symmetry–representing media comprising of multiple fracture sets) as a function of fracture densities and azimuthal fracture orientations. A clear decreasing trend in effective elastic stiffness constants with increasing fracture densities can be observed. Similarly, a periodic trend of effective elastic stiffness constants with fracture orientations can be observed. These trends are more or less expected, but they would have been difficult to quantify without a proper rock physics model. The use of independent effective elastic constants for the generation of synthetic seismic amplitude versus angle and azimuth (AVAZ) data and its correlation with observed seismic AVAZ data in a geostatistical sense has been discussed.

Geoelectrical Models of the Achimov Formation Reservoirs at the Tevlinsko-Russkinskoye Field

The article discusses the results of applying the methodology for assessing the oil saturation of the Achimov formation reservoirs based on the quantitative interpretation of electric logging data in vertical wells of the Tevlinsko-Russkinskoye field. Interpretation of electric logging data using traditional methods leads to errors in oil saturation estimation due to complex diagram shapes, which make it difficult to take readings in thin layers under the influence of resistivity-contrasting zones of penetration and enclosing layers. To calculate reservoir properties, approved petrophysical dependencies were applied, and the resistivity value of thin reservoirs was determined as a result of numerical joint inversion of data from a complex of galvanic and induction probes in the class of 2D geoelectric models, taking into account the design features of probes, well structure, radial and vertical distribution of electrophysical properties of rocks in the section. In 24 wells, geoelectric models were built and the oil content of the BS reservoirs was estimated.

Two-dimensional numerical simulation of spontaneous potential logging data with account to clay content of a reservoir by finite element method

Spontaneous polarization potential (SP) logging remains one of the most widely used geophysical methods of borehole investigation. However, for a long time its interpretation was based on empirical dependences and analytical solutions in simplified formulations. At present the development of the method is associated with the development of new approaches to numerical modeling and quantitative interpretation of SP logging data. Application of numerical algorithms makes it possible to considerably increase information content and resolution of SP method. Nevertheless, most of the currently proposed approaches rely on a simplified description of SP signal formation, which may lead to errors in data interpretation for complex reservoir intervals. In this work, we propose an algorithm for numerical simulation of SP logging data as applied to the study of clayed fluid-saturated reservoirs. The physical and mathematical model of SP signal formation in terms of coupled fluxes for the case of electrochemical SP source is considered. The software realization of the algorithm includes a two-dimensional numerical simulation of SP signals based on the application of the finite element method in the axially symmetric model of the geological medium. The character of SP signals for reservoirs of different thickness at four values of the reservoir water saturation coefficient is studied, as well as the dependence of the shape and amplitude of the SP anomaly in a water- and oil-saturated clayed reservoir on the content and type of clay mineral. The obtained results, aimed at the development of the SP method, improve the quality of SP diagrams interpretation for the study of clayed reservoirs.

Data-Driven Methodology for the Prediction of Fluid Flow in Ultrasonic Production Logging Data Processing

A new method for the determination of oil and water flow rates in vertical upward oil-water two-phase pipe flows has been proposed. This method consists of an application of machine learning techniques on the probability density function (PDF) and the power spectral density (PSD) of the power spectrum output of an ultrasonic Doppler sensor in the pipe. The power spectrum characteristic parameters of the two-phase flow are first determined by the probability density function (PDF) method. Then, the transducer signal is preprocessed by distance correlation analysis (DCA), and independent features are extracted by principal component analysis (PCA). The extracted features are used as input to a least-squares fit, which gave the oil flow rates as output. In the same way, the transducer signal is also preprocessed by partial correlation analysis (PCA), and independent features were extracted using independent component analysis (ICA). The extracted features were used as inputs to multilayer back-propagation neural networks, which water cuts as output. The present method was used to calibrate an ultrasonic Doppler sensor to estimate the flow rates of both phases in oil–water flow in a vertical pipe of diameter 159 mm. Predictions of the present method were in good agreement with direct flow rate measurements. Compared to previously used methods of feature extraction from the ultrasonic Doppler power spectrum signals, the present method provides a theoretical basis for the interpretation of ultrasonic multiphase flow logging data. Ultrasonic multiphase flow logging has potential application value in the production profile logging and interpretation evaluation of production wells with low fluid production and high water cut.

Lithology prediction from well log data using machine learning techniques: A case study from Talcher coalfield, Eastern India

Coal exploration in the Indian scenario is challenging due to plenty of carbon contents and dirt bands within a coal seam. Manual interpretation of geophysical logging data in such conditions is time-consuming and tedious due to the non-linear behaviors of well log signals. This paper intends to apply supervised machine learning techniques such as Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Multi-Layer Perceptron (MLP), and Extreme Gradient Boosting technique (XGBoost) for meticulously interpreting such banded coal seams from geophysical logs. To investigate the efficacy of the above-mentioned five ML techniques in the Indian scenario, we have considered Gamma-ray, Density, and Resistivity logs from four boreholes drilled in Talcher coalfield, Eastern India. ML model training results indicate that all the prediction models have scored more than 88% accuracy scores in classifying carbonaceous and non-coal lithofacies. Receiver Operating Characteristics (ROC) curves of different ML models suggest that the obtained area under the curve (AUC) is positive and above the main diagonal for all lithotypes. Finalized ML models with appropriate hyper-parameters are also applied on the nearby drilled wells, and the outputs are validated against geological core data. It is found that all ML models have acquired an overall accuracy score greater than 80% in all three test wells, conveying that ML techniques are a potential solution for dealing with banded coal seam problems in the Indian scenario.

Deep Classified Autoencoder for Lithofacies Identification

Lithofacies classification is an indispensable procedure in well logging and seismic data interpretation. We propose a novel deep classified autoencoder learning approach to identify lithofacies for high-dimensional data and complex problems. Deep autoencoder (DAE) is an unsupervised learning method via layerwise pretraining multiple autoencoders. It can learn deep data features automatically and reconstruct the original data with a small error. Introducing sparse constraint (i.e., sparse autoencoder) potentiates the learning ability of autoencoder. On this foundation, additional regularization terms constructed by labeled samples are considered in the new DAE approach in order to boost the performance. The new method can adaptively preserve the most significant input features and remove insensitive properties to decrease computational complexity. At the same time, we embed the class information into the loss function of autoencoder to measure intraclass similarity and improve the classification accuracy. Several experiments on well data and seismic data show that the proposed method achieves promising results. Compared with the traditional deep autoencoder (DAE), the proposed method is more competitive in terms of classification accuracy and robustness.

Characterization of reservoirs and depositional study of J-P Field, shallow offshore of Niger Delta Basin, Nigeria

Well log data interpretation was carried out over J-P Field in the Niger Delta, Nigeria. This was done with a view to characterizing the reservoirs based on the estimation of petrophysical parameters and to assessing the environment of deposition in J-P Field. Seven reservoirs were mapped and correlated across the four drilled wells in J-P Field. Petrophysical parameters such as porosity, volume of shale, water saturation and hydrocarbon saturation were estimated. In addition, depositional environments of each reservoir in J-P Field were determined based on the gamma ray responses. This study reveals that the range of petrophysical parameters across the delineated reservoirs; for porosity varies from 19 to 21%, thickness varies from 24 to 122 m, volume of shale varies from 15 to 29%, water saturation varies from 22 to 60% and hydrocarbon saturation varies from 40 to 78%. The depositional environment was interpreted as comprised of prograding deltas, transgressive marine sands, fluvial channels and deltaic settings. It is concluded that J-P Field has a porosity range varying from good to very good in quality and high hydrocarbon saturation of oil. Furthermore, the study revealed that J-P Field falls within the marginal marine depositional environment.

Estimation of fracture density and orientation from azimuthal elastic impedance difference through singular value decomposition

Accurate estimation of fracture density and orientation is of great significance for seismic characterization of fractured reservoirs. Here, we propose a novel methodology to estimate fracture density and orientation from azimuthal elastic impedance (AEI) difference using singular value decomposition (SVD). Based on Hudson's model, we first derive the AEI equation containing fracture density in HTI media, and then obtain basis functions and singular values from the normalized AEI difference utilizing SVD. Analysis shows that the basis function changing with azimuth is related to fracture orientation, fracture density is the linearly weighted sum of singular values, and the first singular value contributes the most to fracture density. Thus, we develop an SVD-based fracture density and orientation inversion approach constrained by smooth prior elastic parameters. Synthetic example shows that fracture density and orientation can be stably estimated, and the correlation coefficient between the true value and the estimated fracture density is above 0.85 even when an S/N ratio of 2. Field data example shows that the estimated fracture orientation is consistent with the interpretation of image log data, and the estimated fracture density reliably indicates fractured gas-bearing reservoir, which could help to guide the exploration and development of fractured reservoirs.

Interpretation of electrical logging data from the Hettangian-Aalenian terrigenous reservoirs in the Southeast of Western Siberia

In the southeast of Western Siberia, the most studied are the Upper Jurassic deposits, most of the oil and gas fields being confined to them. However, the probability of discovering new hydrocarbon deposits in the Upper Jurassic horizons is extremely small. Therefore, of great importance is finding new hydrocarbon deposits in less studied deep-lying complexes. The article considers the development of a criterion for determining the saturation type of the terrigenous reservoirs in the Hettangian-Aalenian deposits in the southeast of the West Siberian sedimentary basin. We use the example of the Ust-Tym megadepression, a large depression located in the central part of the Tomsk region. The Lower and Middle Jurassic sections are represented by the Urman and Togur formations, Salat formation (Peshkov formation is its isochronous analogue) and Tyumen formation, and characterized by the alternation of predominantly sandy (potential reservoirs) and argillaceous-carbonaceous (seals) sequences. In the studied interval, tests were carried out in just a few wells, for which reason the identification of deposits and promising objects is complicated. Determining the type of reservoir saturation will significantly improve the assessment of oil and gas potential. As a result of interpreting lateral logging sounding data, the geoelectric parameters of the invasion zone and undisturbed formation were reconstructed for the Lower Jurassic and Aalenian deposits. Based on the well logging data interpretation by means of numerical inversion, we obtained the criterion for the saturation type of the reservoirs (Ju11-17) in the Hettangian-Aalenian complex. The boundary resistivity values for the oil-saturated reservoirs vary from 8 to 20 ohm∙m, while for the water-saturated ones they do not exceed 5 ohm∙m.

Specific features of the probability petrophysical estimation of rock formations using the approaches of the concept of porous space connectedness

Background. The technology of probability petrophysical estimation of parameters using layer-bylayer interpretation of well logging data is present in this paper. Specific features of the technology is to using both the vertical and horizontal processing.
 Aim. The aim of the technology is the possibility of its adaptation when interpreting well logging data using the approaches of the concept of pore space connectedness, which reduce the variability of estimates of productive thicknesses of reservoirs in comparison with traditional approaches to calculating geological reserves using fixed cutoff porosity coefficient.
 Materials and methods. The paper discusses the main features of modeling the uncertainties of the input parameters and ways of representing them in the form of various distributions with a description of a generalized algorithm for the probabilistic assessment of geological reserves. The distributions of the reservoir area, oil density and conversion factor, the basic version of the results of the reservoir logging data interpretation in the form of a table continuous in depth with readings from the logging methods curves in intervals homogeneous in lithology are use as input parameters when executing the algorithm. In addition, distributions reflecting variations in the uncertainties of geophysical parameters, constants of petrophysical models, boundary cutoff s for identifying reservoirs and assessing their saturation nature are used to the input of the algorithm.
 Results. An algorithm for probabilistic petrophysical assessment has been developed taking into account the use of petrophysical modeling within the framework of the concept of pore space connectivity and the layer-by-layer mode of interpretation of well logging data. It is shown that additional petrotyping, which makes it possible to clarify the parameter of pore space connectivity, reduces the error of the resulting estimates, which can reduce the risk of making ineffective decisions.
 Conclusions. It is show that additional petrotyping, which makes it possible to clarify the parameter of pore space connectedness, reduces the error of the resulting estimates, which can reduce the risk of making ineffective decisions.

Peculiarities of change in the main formation parameters of the KS and PK suite deposits at the Pirallakhi adasy field

In order to analyze the changes in the parameters of the main reservoir parameters by area and depth at the Pirallahi adasy field, the results of the interpretation of core and logging data were used. For this, the data from well logging and the results of core analysis over the area were collected and analyzed. The results of interpretation of the data of complex well logging studies of wells carried out at the field and the results of analysis of core materials are systematized, statistical analysis is carried out. In the section of each well, reservoirs were identified, characterized by reservoir properties for the KS and PK formations, their porosity, clay content, oil and gas saturation, and permeability were determined. The weighted average values of these parameters for individual wells were calculated and distribution graphs were drawn up. Dependences are established between the parameters of the filtration-capacitive characteristics and correlations are built. The graphs of dependence are built between the parameters characterizing the reservoir characteristics, porosity and clay content, permeability and porosity in the KS and PK formations. As a result of the studies carried out, it can be noted that the Pirallahi adasi field, despite the fact that it has been in operation for a long time, the obtained results of the well logging data interpretation for the KS and PK formations, the identified reservoirs have high properties that the hydrocarbon reserves of the field have not been exhausted. Taking into account the above, it is more expedient to continue drilling and development of new wells in the best possible way, choosing the optimal well network at the Pirallahi adasy field. Keywords: well logging; reservoir characteristics; permeability and porosity; interpretation of core and logging data.

CORRELATION RESULTS OF THE PROTEROZOIC-PHANEROZOIC SECTIONS OF THE ALDAN-MAYA OIL AND GAS BEARING REGION ON DEEP DRILLING DATA

The article discusses the controversial issues of well log correlation of the Riphean, Vendian, Cambrian and Mesozoic sequences, which is prospects for oil and gas within the Aldan-Maya petroleum region. The author's version of the stratigraphic correlation is based on the interpretation of logging data, seismic surveys, core description, archival and published materials. The results obtained can be used for stratigraphic picks correction and structural maps plotting.

Study current oil-gas saturation according to the geophysical logging data in Pirallahi adasy field

The paper studies the current distribution of oil-gas saturation in the reservoirs of Kirmaki and Lower Kirmaki suits in Pirallahi adasy field according to the integral analysis using the results of field, geological, geophysical well logging, as well as those of laboratory investigations. For studying the heterogeneity of sections, the changes of reservoir parameters according to the logging data interpretation have been analyzed. Based on comparative analysis of data interpretation for old and new wells (PNNL and other logging measurements), the areas maintained productivity in research region have been revealed and the sites for new well drilling and residual oil extraction recommended as well.

Well logging data interpretation for appraising the performance of Alam El-Bueib reservoir in Safir Oil Field, Shushan Basin, Egypt

This paper presents different well log data interpretation techniques for evaluating the reservoir quality for the sandstone reservoir of the Alam El-Bueib-3A Member in Safir-03 well, Shushan Basin, Egypt. The evaluation of the available well log data for the Alam El-Bueib-3A Member in this well indicated high quality as oil-producing reservoir between depths 8108–8133 ft (25 ft thick). The calculated reservoir parameters possess shale volume less than or equal to 9% indicating the clean nature of this sandstone interval, water saturation values range from 10 to 23%, and effective porosity varies between 19 and 23%. Bulk volume of water is less than 0.04, non-producing water (SWirr) saturation varies between 10 and 12%, and permeability ranges from 393 to 1339 MD reflecting excellent reservoir quality. The calculated BVW values are less than the minimum (BVWmin = 0.05) reflecting clean (no water) oil production, which was confirmed through the drill stem test (DST). The relative permeabilities to both water and oil are located between 0.01–0 and 1.0–0.5, respectively. The water cut is fairly low where it ranges between 0 and 20%. Additionally, the water saturation values are less than the critical water saturation (Scw = 29.5%) which reflects that the whole net pay will flow hydrocarbon, whereas the water phase will remain immobile. This was confirmed with reservoir engineering through the DST.

Estimation of Uncertainty of a Volumetric Reservoir Model and Optimization of Numerical Inversion in Well Log Data Interpretation

This study considers an approach to joint inversion of logging data in oil and gas wells for finding the volume fractions of reservoir components. The inversion is reduced to a linear least squares problem with additional iterations to account for physical constraints. To analyse the quality of inversion, uncertainty evaluation tools are developed for both the model responses and inversion results – volume fractions of the reservoir components. The tools include algorithms for construction of depth-related “confidence corridors” for individual properties and standard deviation ellipses to analyse cross-correlations. An optimization problem of improving the quality of inversion by tuning specific readings of logging methods for individual reservoir layers (or facies/lithotypes) is also posed and solved by minimizing a mismatch criterion between the actual and simulated log curves. Thus, the developed toolkit provides a means for optimized joint inversion of logging data with visual control of uncertainty and cross-correlation in the inversion results.

Numerical solution of the integral equations of the electromagnetic field in geosteering problems

Extra-deep azimuthal resistivity measurements improve the depth of investigation up to 30 m from the wellbore. Interpretation of electromagnetic logging data in the neighbourhood of a well becomes an important technical problem. We present an efficient parallel method for computation of induction tool responses with multiple transmitter–receiver configurations in 2D pixel-based anisotropic model crossed by an arbitrary well trajectory. The cornerstone of the approach is volume integral equation method. We consider the conductivity distribution as a sum of background and anomalous conductivities. Background conductivity is 1D-layered. Anomalous conductivity has arbitrary 2D distribution. Electromagnetic fields are the superposition of background and anomalous fields. Background fields are calculated exactly using rigorous analytical solution for 1D-layered background model. With this approach, the 2D pixel-based model is treated as an extension of the 1D-layered model. The anomalous fields are required only in pixels with conductivity different from the conductivity of the 1D-layered model. Anomalous fields are calculated using convergent series of integral operators [1]. The approach takes into account conductivity anisotropy and allows obtaining both the exact solution and the fast approximate one. The convergence of approximate solution is investigated on some synthetic examples.