Well Logging

TESTING is a function of both source type and of formation velocities. Axial stress sources are less affected by the casing than either radial stress or volume-injection sources, and as formation velocity decreases, the effect of the casing becomes more significant. The new generalized stationaryphase solution also shows that as frequency approaches 1000 Hz, the results obtained by low-frequency approximations for stress sources can be inaccurate and that the energy radiated from the source becomes more highly directed in the horizontal directions.-from Author 945127 Hydrological aspects of geophysical borehole measurements in crystalline rocks of the Black Forest

The primary objective of this study is to identify and analyze the petrophysical properties of the newly investigated AEB_IIIG member reservoir in Meleiha West Deep (MWD) Field and to classify it into different rock types. Additionally, this research intends to develop mathematical equations that may be utilized to estimate permeability in uncored sections of the same well or in other wells where core samples are unavailable. The analysis focused on the pore hole records of ten wells that were drilled in MWD Field. The reservoir levels were identified, and their petrophysical parameters were evaluated using well logs and core data. We were able to recognize seven different types of rocks (petrophysical static rock type 1 (PSRT1) to PSRT7) using petrography data, the reservoir quality index (RQI), the flow zone index (FZI), R35, hydraulic flow units (HFUs), and stratigraphy modified Lorenz (SML) plots. The analysis of the petrophysical data shows that AEB_IIIG has unsteady net pay thicknesses over the area. It has a range of 8-25% shale volume, 12-17% effective porosity, and 72-92% hydrocarbon saturation. The RQI results show that psrt1, psrt2 and psrt3 have a good reservoir quality as indicated by high R35 and helium porosity, respectively. They contribute with more than 75% of the reservoir production. The equation derived for each rock type of AEB_IIIG reservoir can be employed to forecast the permeability value distribution inside the reservoir.

The development of unconventional resources requires accurate delineation of formation stiffness along extended horizontal borehole segments. This paper studies the feasibility of prediction of rock stiffness using drilling parameters recorded at the rig, downhole measurements while drilling, and near-bit vibrations. We used a machine learning-assisted workflow to model the wireline logs and assess the importance of various input data. The use of nearbit vibrations reduces the prediction error (of sonic data?) from ~5.3% achieved relying on to 1.8%, which is sufficient for drilling/completion applications. The machine learning algorithm also quantifies the quality of the wireline logs used for training: shear and density logs have ~20% of noisy data while the compressional velocity ~35%. Prediction of wireline shear and compressional sonic data using downhole vibrations measured while drilling has vast potential to reduce logging cost for borehole completion industrywide.

государственный университет нефти и газа (Национальный исследовательский университет) имени И.М. Губкина» (Москва, Россия). Задача увязки данных керна и геофизических исследований скважин является первым этапом построения адекватной геологической модели залежей углеводородов (УВ), поскольку наиболее надежную информацию о фильтрационно-емкостных свойствах коллекторов можно получить, только изучая образцы керна. Коллекция керна, используемая для формирования петрофизической модели, должна в полной мере описывать изучаемый разрез по площади (латерали) и по разрезу (вертикали). Петрофизическая настройка комплекса геофизических исследований (ГИС) выполняется сравнением их с данными анализа керна для отложений единого стратиграфического подразделения. Это необходимо для установления связей типа «керн -ГИС». При сопоставлении результатов непрерывной (поточечной) интерпретации ГИС привязка керновых данных осуществляется поточечно. В случае попластовой интерпретации геофизических данных в интервалах выделенных пропластков выполняется осреднение значений параметра по керну. Согласно Требованиям к составу и правилам оформления представляемых на государственную экспертизу материалов по подсчету запасов нефти и горючих газов (Приказ Министерства природных ресурсов и экологии РФ от 28 декабря 2015 г. № 564) в раздел «Физико-литологическая характеристика коллекторов продуктивных пластов и покрышек по результатам исследования керна» включаются методика и результаты привязки керна к разрезу. В настоящее время в специальной литературе собственно методика привязки керна к геофизическим исследованиям не описана в должной мере. В статье рассмотрены основные методические приемы привязки кернового материала к геофизическим исследованиям в «ручном» режиме. Различное программное обеспечение позволяет увязать данные керна и ГИС по глубине, однако за качество полученного результата и петрофизическую модель для целей определения подсчетных параметров отвечает специалист. Ключевые слова: керн, фильтрационно-емкостные свойства, пористость, проницаемость, геофизические методы исследования скважин.

Shear sonic log (DTS) availability is vital for litho-fluid discrimination within reservoirs, which is critical for field development and production. For certain reasons, most of the wells in the Lower Indus Basin (LIB) lack DTS logs, which are modeled using conventional techniques based on empirical relations and rock physics modeling. However, in their extensive computation, these approaches need assumptions and multiple prerequisites, which can compromise the true reservoir characteristics. Machine learning (ML) has recently emerged as a robust and optimized technique for predicting precise DTS with fewer input data sets. To predict the best DTS log that adheres to the geology, a comparison was made between three supervised machine learning (SML) algorithms: random forest (RF), decision tree regression (DTR), and support vector regression (SVR). Based on qualitative statistical measures, the RF stands out as the best algorithm, with maximum determination of correlation (R2) value...

The impact of wood loads on bulk density and preconsolidation pressure and of harvester and forwarder traffic on rut depth, bulk density and preconsolidation pressure of two Ultisols were examined in this study. Our objective was to quantify the threshold beyond which significant soil compaction and rutting would occur. This study was carried out in the county of Eunápolis, state of Bahia, Brazil, (16 º 23 ' 17…

Corporate reputation is an intangible asset of organisations that could help to sustain a competitive advantage for a long period; however, ineffective development of corporate reputation by organisations could reduce the competitive advantage in the global market. To address this issue, this study aims to examine the effect of corporate reputation on customer satisfaction, customer loyalty and behavioural intention in the restaurant industry of Indonesia. Using a cross-sectional research design, 600 questionnaires were distributed among managers in the restaurant industry of Indonesia. A convenient sampling technique was used, which yielded a 58.33% response rate. The Structural Equation Modelling technique was used to analyse the data. The findings have shown a positive and significant association between corporate reputation, customer satisfaction, customer loyalty, and behavioural intention. This study contributed to the extant literature and also provided valuable insights upon which organisations may capitalize to improve corporate reputation and sustain a competitive advantage.

The Delaware basin of Western Texas and Southeastern New Mexico consists of multi-stacked reservoirs with most common drilling activity targeting the Bone Spring formation. For the purpose of optimized completions and production, sweet spot interval is defined based on rock quality and fracability. Available suite of logging while drilling (LWD) with azimuthal measurements aided in accurately placing horizontal wells within defined target stratigraphic zone. With LWD borehole image dip data and azimuthal deep resistivity measurements, integrated near wellbore reservoir-scale structural modeling was done using advanced 3D modeling technique. Workflows which includes dip interpretation, dip sequence analysis, extraction of local structural components, true stratigraphic computation, isopaching, structural axis delineation and definition of structural units and elements were applied. Resultant high resolution structural model is useful for taking decisions on sidetracking, well planning and well placement in reservoirs with sub-seismic structural elements and complex 3D structures.

The West Salym is a Salym Petroleum Development oil field in the Khanty-Mansi region, 120 km southwest of Surgut, Russia. The West Salym oil field was discovered in 1987 and was brought on stream in 2004. The reservoirs vary from fluvial/deltaic to shallow marine deposits. Primary development of the central area of West Salym Field is complete, but the field edges remain undeveloped and potentially attractive. The edges of the field are presented by a mouth bar and characterized by significant structural formation changes, including unknown formation dips and local carbonate concretions and stripes. The sand thickness of the target layer is 15 m, with a minimum oil height of 1 m, which is caused by structural dips and nearby oil/water contact (OWC). These conditions make it difficult to drain the area with geometrically placed wells within the hydrocarbon-saturated layer using well correlation and 3D seismic-interpretation results. Another challenge is the low resistivity contrast between the shale, oil-bearing, and water-bearing layers. This poor contrast complicates the evaluation of reservoir properties and the ability to distinguish different fluid saturations. Two horizontal wells (500 m each) were drilled for the first time in West Salym Field to evaluate capabilities of modern reservoir-navigation technology using deep-azimuthal resistivity technology and advanced data-interpretation software. Drilling of both horizontal wells was improved with a standard wireline logging suite (gamma ray, spontaneous potential, resistivity, density, and neutron) and pressure-testing results available from pilot holes. Logging-while-drilling (LWD) deep-azimuthal resistivity technology has been used in field development, contributing to proactive reservoir navigation. This technology provides input for interpreting an extensive set of multicomponent, multispacing, and multifrequency measurements. These data are usually sufficient to resolve the formation properties in the vicinity of several meters from the wellbore and to adjust the direction of the well trajectory. However, because of time restrictions, very simple resistivity models and only a subset of the data are often used for real-time interpretation. Moreover, the structure of the data subset is often predefined to provide the maximum depth of investigation, neglecting the resolution quality of the formation parameters. In some fields, it can lead to increased uncertainties during reservoir navigation. The data-interpretation software mentioned in this paper has excellent performance and enables real-time processing of the full set of downhole measurements derived from multilayered formation models. This case highlights the first use of this software application in the Russian Federation. The software is dependent on the method of the most-probable parameter combination, and it maintains an optimal balance between the information recovered from the measured data and all available a priori knowledge about the formation structure. The ability to accurately involve a priori information enhances the capability to resolve layers with low resistivity contrasts. Moreover, the inversion software is user-guided, enabling precise monitoring of lateral and vertical changes in the geology. The data-inversion software ensured successful reservoir navigation in the challenging conditions of the West Salym Field. All steering decisions were made according to a consistent and reliable multilayered formation resistivity model that was constructed in real time during drilling. A good net/gross ratio was achieved of approximately 75% for one well and 50% for the other. Post-drilling analysis showed that geometric drilling without reservoir-navigation technology would lower the net/gross ratio to less than 40%.

SummaryThe West Salym is a Salym Petroleum Development oil field in the Khanty-Mansi region, 120 km southwest of Surgut, Russia. The West Salym oil field was discovered in 1987 and was brought on stream in 2004. The reservoirs vary from fluvial/deltaic to shallow marine deposits. Primary development of the central area of West Salym Field is complete, but the field edges remain undeveloped and potentially attractive.The edges of the field are presented by a mouth bar and characterized by significant structural formation changes, including unknown formation dips and local carbonate concretions and stripes. The sand thickness of the target layer is 15 m, with a minimum oil height of 1 m, which is caused by structural dips and nearby oil/water contact (OWC). These conditions make it difficult to drain the area with geometrically placed wells within the hydrocarbon-saturated layer using well correlation and 3D seismic-interpretation results. Another challenge is the low resistivity cont...

This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water resistivity for the formation (Rw = 0.021), the average resistivity of the mud filtration (Rmf = 0.57), and the Archie parameters determined by the picket plot method, where m value equal to 1.94, n value equal to 2 and a value equal to 1. Porosity ...

The petrophysics science is concerned with the study and characterization of oil and gas reservoirs for the hydrocarbon potential availability and productivity through the quantitative of rock properties. Porosity is one of the most important property in petrophysics. Estimation of porosity values are classified into two techniques, direct and indirect methods. The direct method has been used to estimate the porosity from core analysis, because the well log records are considered as indirect technique, which depend on the measurments of the physical features related with the porosity values. In this study two methods are used to evaluate the porosity of carbonate reservoir. The first one has been applied to the well logging interpretation, while the second method uses imaging technique interpretation based on core slides. The result of the second method shows a more accurate results of porosity in comparison with first method. The porosity values are varied from 2% to 3% by using Ne...

In recent years, wireline temperature profiling methods have evolved to offer new insight into fractured rock hydrogeology. Important advances in wireline temperature logging in boreholes make use of active line source heating alone and then in combination with temporary borehole sealing with flexible impervious fabric liners to eliminate the effects of borehole cross-connection and recreate natural flow conditions. Here, a characterization technique was developed based on combining fiber optic distributed temperature sensing (DTS) with active heating within boreholes sealed with flexible borehole liners. DTS systems provide a temperature profiling method that offers significantly enhanced temporal resolution when compared with conventional wireline trolling-based techniques that obtain a temperaturedepth profile every few hours. The ability to rapidly and continuously collect temperature profiles can better our understanding of transient processes, allowing for improved identification of hydraulically active fractures and determination of relative rates of groundwater flow. The advantage of a sealed borehole environment for DTS-based investigations is demonstrated through a comparison of DTS data from open and lined conditions for the same borehole. Evidence for many depth-discrete active groundwater flow features under natural gradient conditions using active DTS heat pulse testing is presented along with high resolution geologic and geophysical logging and hydraulic datasets. Implications for field implementation are discussed.

Four subsurface sections and electrical, porosity logs, and gamma-ray logs of the Khasib Formation (age Late Turonian-Lower Coniacian) were studied to identify reservoir characteristics and to evaluate the reservoir properties of the Khasib reservoir units in the East Baghdad oilfield. The lithology of the formation is limestone throughout the whole sequence in all studied wells EB-83, EB-87, EB-92, and EB94. It is bounded conformably from the top by Tanuma Formation and has a conformable lower contact with Kifl Formation. The lower and upper boundaries of the formation were determined using well log analysis, and the formation was divided into three main rock units (Kh1, Kh2, and Kh3), depending on the porosity logs. The porosity was calculated using acoustic or sonic, neutron, and density logs. The effective porosity (average 0.0-0.32 %) is the predominant porosity in the formation and to less extent; the secondary porosity. The volume of shale is very low (average 0.0-0.13 %), indicating limestone is the main rock of the Khasib Formation. The study of the reservoir water (average 0.11-1.0%) and hydrocarbon saturations (average 0.0-0.88 %) showed that the formation contains varying proportions and quantities of water and hydrocarbons suspended in the wall void, and hydrocarbons capable of being produced. The lithological study reflected that the predominant lithic formation is limestone. It was found that Kh 2 unit is the best oil reservoir unit in all selected wells in terms of porosity, water saturation, diagenesis processes, and microfacies analysis.

The LRLC reservoir zone has been identified in SN-3 well, at the DAP-1 interval on Gumai Formation. This interval has a low resistivity value from 3-5 ohm.m and the drill stem test (DST) results show oil with gas without water. This study is objected to identify the causes of LRLC reservoir in gumai formation and finding a suitable sw calculation method. Some data such as well logs, reports, cores, and XRD are used to calculate petrophysical parameters such as Vsh, Phie, and Sw, and would be validated by DST data. Water saturation (Sw) calculations from Archie and the CEC method (Waxman Smits, Dual Water, Juhasz) were performed and the results were compared. The results showed that the main cause of the DAP-1 interval LRLC zone was the presence of clay minerals consisting of mixed layers (Illite/smectite). These clay minerals will be associated with high cation exchange capacity (CEC) values, with the value 70 (meq/100g), which can increase conductivity and reduce resistivity values. Based on lumping the more optimistic results of sw calculation from Waxman Smits Sw method (Sw based on CEC method). The DST data on the SN-3 well does not have water test data, so the calculation of the Sw value that is close to the Swirr value is considered the most suitable Sw for the low resistivity reservoir conditions of the Gumai Formation in the study area. The best practice for low resistivity reservoir for suitable petrophysical calculation is necessary to pay attention to the rock lithology conditions, the presence of mineral clay, and determining suitable Sw appropriate to the reservoir conditions.

Due to complexities in geologic structure, heterogeneity, and insufficient borehole information, shale formation faces challenges in accurately estimating the elastic properties of rock which triggers severe technical challenges in safe drilling and completion. These geomechanical properties could be computed from acoustic logs, however, accurate estimation is critical due to log deficit and a higher recovery expense of inadequate datasets. To fill the gap, this study focuses on predicting the sonic properties of rock using deep neural network (Bi-directional long short-time memory, Bi-LSTM) and random forest (RF) algorithms to estimate and evaluate the geomechanical properties of the potential unconventional formation, Permian Basin, situated in West Texas. A total of three wells were examined using both single-well and cross-well prediction algorithms. Log-derived single-well prediction models include a 75:25 ratio for training and testing the data whereas the cross-well includes ...

To help understand volcanic facies in the subsurface, data sets that enable detailed comparisons between down-hole geophysical data and cored volcanic intervals are critical. However, in many cases, the collection of extended core intervals within volcanic sequences is rare and often incomplete due to challenging coring conditions. In this contribution we outline and provide initial results from borehole logging operations within two fully cored lava-dominated borehole sequences, PTA2 and KMA1, on the Big Island of Hawai'i. Data for spectral gamma, magnetic susceptibility, dipmeter resistivity, sonic, total magnetic field, temperature and televiewer wireline logs were successfully acquired for the open hole interval ca. 889 m to 1567 m within the PTA2 borehole. Spectral gamma was also collected from inside the casing of both wells, extending the coverage for PTA2 to the surface and covering the interval from ca. 300 to 1200 m for KMA1. High-quality core material was available for both boreholes with almost complete recovery which enabled high-resolution core-to-log integration. Gamma data are generally low commonly in the range ca. 7-20 gAPI but are shown to increase up to API of ca. 60 with some intrusions and with increases in hawaiite compositions in the upper part of PTA2. Velocity data are more variable due to alteration within porous volcanic facies than with burial depth, with a general degrease down-hole. The high-resolution televiewer data have been compared directly to the core, enabling a comprehensive analysis of the variations in the televiewer responses. This has enabled the identification of key features including individual vesicles, vesicle segregations, strained vesicles, chilled margins, rubble zones, intrusive contacts and pāhoehoe lobe morphologies, which can be confidently matched between the televiewer data and the full diameter core. The data set and results of this study include findings which should enable improved borehole facies analysis through volcanic sequences in the future, especially where down-borehole data and images but no core are available.

By determining the hydraulic flow units (HFUs) in the reservoir rock and examining the distribution of porosity and permeability variables, it is possible to identify areas with suitable reservoir quality. In conventional methods, HFUs are determined using core data. This is while considering the non-continuity of the core data along the well, there is a great uncertainty in generalizing their results to the entire depth of the reservoir. Therefore, using related wireline logs as continuous data and using artificial intelligence methods can be an acceptable alternative. In this study, first, the number of HFUs was determined using conventional methods including Winland R35, flow zone index, discrete rock type and k-means. After that, by using petrophysical logs and using machine learning algorithms including support vector machine (SVM), artificial neural network (ANN), LogitBoost (LB), random forest (RF), and logistic regression (LR), HFUs have been determined. The innovation of th...

The LRLC reservoir zone has been identified in SN-3 well, at the DAP-1 interval on Gumai Formation. This interval has a low resistivity value from 3-5 ohm.m and the drill stem test (DST) results show oil with gas without water. This study is objected to identify the causes of LRLC reservoir in gumai formation and finding a suitable sw calculation method. Some data such as well logs, reports, cores, and XRD are used to calculate petrophysical parameters such as Vsh, Phie, and Sw, and would be validated by DST data. Water saturation (Sw) calculations from Archie and the CEC method (Waxman Smits, Dual Water, Juhasz) were performed and the results were compared. The results showed that the main cause of the DAP-1 interval LRLC zone was the presence of clay minerals consisting of mixed layers (Illite/smectite). These clay minerals will be associated with high cation exchange capacity (CEC) values, with the value 70 (meq/100g), which can increase conductivity and reduce resistivity values. Based on lumping the more optimistic results of sw calculation from Waxman Smits Sw method (Sw based on CEC method). The DST data on the SN-3 well does not have water test data, so the calculation of the Sw value that is close to the Swirr value is considered the most suitable Sw for the low resistivity reservoir conditions of the Gumai Formation in the study area. The best practice for low resistivity reservoir for suitable petrophysical calculation is necessary to pay attention to the rock lithology conditions, the presence of mineral clay, and determining suitable Sw appropriate to the reservoir conditions.

The Khasib Formation of Late Cretaceous (Upper Turonian – Lower Coniacian) is considered important reservoir in the Amara oil field.Knowledge of reservoirs rocks composition including fluid saturation and mineralogical components is essential for formation evaluations. The current study represents an evaluation study of the Khasib Formation using logs and cored data to evaluate the Khasib Formation in terms of its mineralogical, lithological composition and its petrophysical properties such as porosity and fluid saturation. Logs data of 15 drilled wells in the Amara Field and cored intervals of the well Am11 from the Khasib Formation were conventionally processed and integrated. Also, the mineralogical components of the Khasib Formation were revealed using a simultaneous equation approach by computer processed interpretation (CPI), where, combination of 5 logs including gamma ray, sonic, density, neutron and resistivity was integrated.The results show that the Khasib can be subdivid...

Well logs data are the most widely used data to evaluate subsurface rocks, their petrophysical properties include porosity, permeability and fluid saturation. They are essential for the hydrocarbon reserves estimations and perforation zones determination for production purposes and fields development. Well logging operations of the targeted reservoirs could not be done in NO-10 Well, Noor Oilfield, Southern Iraq due to some problems related to the well condition. The gamma-ray and sonic logs were the only recorded logs, while neutron, density and deep resistivity logs are missed. The missing neutron, density and deep resistivity logs of the Early Cretaceous Nahr Umr Sandstone and the Late Cretaceous Mishrif formations of the well NO-10 were produced and compared together using the Artificial Neural Network ANN in Petrel software. The results show that the total correlation of the ANN Nahr Umr model for the neutron, density and deep resistivity logs are 0.81, 0.49 and 0.51 respectively. Interestingly, the ANN Mishrif Formation model recorded 0.88, 0.92 and 0.81 for neutron, density and resistivity logs respectively. The results show excellent relationships between the original and the predicted logs in the Mishrif model, unlike the Nahr Umr model expect in ANN of the neutron log. It was expected that the total relationships are low in Nahr Umr due to the lithology variation that includes interbedded consolidated and unconsolidated sandstone interbedded with the shale. It is also observed that the gamma log shows low values and the caliper logs is smoothed in the Mishrif. In contrast, the Nahr Umr sandstone logs show that many washouts have occurred. Therefore, logs' responses highly possible to be affected in the Nahr Umr Formation which leads to a decreasing in the coefficient of determinations.

This paper presents the results of correlauons of the geophysical well logs obtained from wells drilled at the Cerro Pneto geothermal field From this correlation, a structural interpretation of the 'receptacle' holding the geothermal flmds has been obtained Based on the temperature and electrical reslst~wty logs, the presence of two mare geothermal reservmrs has been estabhshed It was also found that most of the wells were completed such that production is obtained s~multaneously from several sandy layers In all probablhty this has created some mechamcal problems m the wells m addmon to a certain confusion m the interpretations based on fired production data An hypothesis is postulated about the deposmon enwronment and the genesis of the reservmr, on the basts of which it is concluded that the reservoir is a paleochannel It is also postulated that thmnlng of the basement rocks Is the fundamental cause of the heat transmission to the reservoirs Tables hstmg the correlating marker horizons for each well and maps showing the top of the two mam reservoirs and the lsopacks for the shallow one are presented From these data have been referred the areas showing the best posslblht~es for immedmte geothermal development

The identification of lithofacies from well is usually an interpretative process based on geophysical logs since core and sidewall samples are not usually available. Despite being always sampled and described, cuttings are useful only as a reference for determining the rocks because a number of problems occur during the drilling and sampling activities. Well logs are in situ continuous records of different physical properties of the drilled rocks, which can be associated with different lithofacies by experienced log analysts. This task needs a relatively great amount of time and it is likely to be imperfect because the human analysis is subjective. Thus, any alternative method of classification with high accuracy and promptness is very welcome by the log analysts. This paper is based on Neural Networks (NNs) applied in well data from the Leão Coal Mine, southern Brazil, in order to classify organic mudrocks, coals and siliciclastic sandstones, the main rocks present in the Rio Bonito and Palermo formations, by using their well logs as database. The training and validation set of the NN contain data from eight cored and logged boreholes. The input included 409 values of depth and logs of gamma-ray, spontaneous potential, resistance and resistivity for each electrofacies. The neural network model was the feedforward multilayer perceptron (MLP) and the neural networks were trained with variations of the backpropagation algorithm: Levenberg-Marquardt and Resilient backpropagation. Although an accuracy of approximately 80% had been achieved in the general classification, discrepant accuracies in the classification of the different electrofacies are discussed in order to better understand the reasons that affected negatively the NN performance.

The concept of information fusion has gained a widespread interest in many fields due to its complementary properties. It makes systems more robust against uncertainty. This paper presents a new approach for the well-logging estimation problem by using a fusion methodology. The natural gammaray tool (NGT) is considered as an important instrument in the well logging. The NGT detects changes in natural radioactivity emerging from the variations in concentrations of micronutrients as uranium (U), thorium (Th), and potassium (K). The main goal of this paper is to have precise estimation of the concentrations of U, T h, and K. Four types of Kalman filters are designed to estimate the elements using the NGT sensor. Then, a fusion of the Kalman filters is utilized into an integrated framework by an ordered weighted averaging (OWA) operator to enhance the quality of the estimations. A real covariance of the output error based on the innovation matrix is utilized to design weighting factors for the OWA operator. The simulation studies indicate not only a reliable performance of the proposed method compared with the individual Kalman filters but also a better response in contrast with previous fusion methodologies.

The structural complexities of hydrocarbon reservoirs make it difficult to correlate geological and petrophysical properties. A successful field development depends on accurately mapping the spatial distributions of reservoir key parameters. In this study, we present results on rock type analysis, estimation, and uncertainty evaluation of geological and petrophysical data of 33 wells in one of the south Iranian gas fields. This paper is divided into two parts. In the first part, we used a reservoir rock classification theme based on identifying electrofacies (EFs) and hydraulic flow units by analyzing both log and core data. In the second part of the paper, we performed estimation, uncertainty evaluation, and assessment of the porosity-thickness relationship of the high-quality EFs using geostatistical techniques. We used sequential simulation schemes to map the spatial distributions of porosity and thickness of the high-quality EFs across the field. Using probabilistic approaches, the generated multiple realizations were used to quantify the local and spatial uncertainties. Variogram analysis showed that property distributions had a higher continuity and minimum variance in the NW-SE direction. Based on spatial uncertainty analysis, we found that the indicator-based sequential simulated maps exhibited less spatial uncertainty. Furthermore, the obtained probability maps indicated that the SE part of the study area is more suitable for drilling and production scenarios.

Evaluation of Petrophysical Characteristics using well-log data in the Bornu-Chad Basin, NorthEastern Nigeria has been performed. The main goal of the research is to evaluate the reservoir potentials of the field through the analysis, and evaluation of key petrophysical parameters from wireline logs which could be used to generate an effective reservoir model. A total of six wells were evaluated parameters on Porosity, Permeability, Density, Shale Volume and the Share and Compressional velocities. The research uses empirical relations to compute the properties at depths using Excel software. From the results of the analysis, about three possible reservoir zones were delineated. Wells Albarka, Mbeji, Kemari, Gubio and Wadi correlated against Kasade all shows these possible reservoir units at different depths. Porosity values in the drilled columns are 10-42%, 3-70%, 12-57%, 3-43%, 1-40% respectively. Permeability ranges from 3.36-58.69mD in Kasade, 0.79-17.49mD in Albarka, 0.73-66.49mD in Gubio, 0.05-69.21mD in Mbeji, 1.38-63.09mD in Kemari and 0.02-60.14mD in Wadi. Shaliness ranges from 0-0.99, Density ranges between 1.066kgm-3-1.343kgm-3 having an average value of 1.212kgm-3. The studies delineate six different lithological units; Clay, Shaly-Sand, Sand, Clean Sand, Shale and Mudstone with average porosity and permeability values of 20.375% and 16.254mD, 36.7% and 32.541mD, 42% and 39.485mD, 61.4% and 64.017mD, 19.625% and 16.79mD. and 18.5% and 8.99mD respectively. The results of this work could be used in formation evaluation in the area of study.

This paper provides an overview of the site characterization work at the Heletz site, in preparation to scientifically motivated CO2 injection experiments. The outcomes are geological and hydrogeological models with associated medium properties and baseline conditions. The work has consisted on first re-analyzing the existing data base from ~ 40 wells from the previous oil exploration studies, based on which a 3-dimensional structural model was constructed along with first estimates of the properties. The CO2 injection site is located on the saline edges of the Heletz depleted oil field. Two new deep (>1600 m) wells were drilled within the injection site and from these wells a detailed characterization program was carried out, including coring, core analyses, fluid sampling, geophysical logging, seismic survey, in-situ hydraulic testing and measurement of the baseline pressure and temperature. The results are presented and discussed in terms of characteristics of the reservoir and cap-rock, the mineralogy, water composition and other baseline conditions, porosity, permeability, capillary pressure and relative permeability. Special emphasis is given to petrophysical properties of the reservoir and the seal, such as comparing the estimates determined by different methods, looking at their geostatistical distributions as well as changes in them when exposed to CO2.

This study is focused on identifying the formations, whether are they reservoir formations or not. The effective porosity and permeability evaluating of the oil reservoir is the most important methods to recognize the formations. In this study, the effective porosity and permeability of the Yamama formation in an oil field of southern Iraq can be calculated by applying, the neutron-density and the sonic logs. The calculated effective porosity of the formation ranged between (6%-17%), and the porosity in the joints was less than (0.04). The permeability in Yamama Formation calculated by three methods: Timur, Morris Biggs oil, and Schlumberger methods. By comparing the values of the permeability calculated by these methods, it was found that the methods of Timor and Schlumberger gave the same results, and also when the permeability calculated by these methods compared with the permeability of the cores, the method of Timur and Schlumberger closer than the results of the cores. So, the Schlumberger and Timor method is the one used in calculating the permeability. The permeability values for most of Yamama formation range from: 0.1-10 md, and the permeability in the joints was less than 0.001 md.

The Thunder Horse Field targets Middle Miocene deepwater turbiditic reservoirs. Despite of being prolific, the mapping of the ~180 m thick, partly amalgamated reservoir sandstones is challenging. Seismic quality is reduced by the presence of salt structures. The salt overburden and high formation pressure requires the use of heavy mud weights and oil-based drilling fluids, which limit the resolution and interpretation potential of borehole image logs (BHI). Halokinetic movements caused significant postdepositional deformation of the already complex gravitydriven sediment stack and the reservoir beds drape against an E-W oriented salt wall. Consequently, the assessment and removal of the structural dip component is not trivial and the evaluation of paleotransport directions is considerably more complicated compared to undisturbed deepwater reservoirs. The intention of this paper is to bring the main results from Henry et al. (2018) into context with the eigenvector methodology from Ruehlicke et al. (2019) and to emphasize its value for reservoir characterization.

Almera-1 borehole was drilled to provide a borehole geophysical logging and downhole monitoring research and training facility. Also a main objective was the exploration of the urban subsurface geology adjacent to the Institute of Earth Sciences Jaume Almera (CSIC) in Barcelona the University of Barcelona Pedralbes. Wireline drilling continuous coring was successfully applied to recover cores from the entire section (214m). Since 2011 Almera-1 hole has been extensively used for slim hole logging, coring and monitoring. Total depth was reached after drilling a Quaternary to Paleozoic section. The upper section of Almera-1 hole is cased with PVC and the lowermost is an open hole section within the Paleozoic section. A complete set of geophysical logging measurements and oriented borehole images was acquired with CSIC own slim hole logging equipment both in open hole mode and through the PVC casing. Logging measurements were acquired over the entire section. Open hole measurements incl...

In this study, in order to evaluate the geochemical characterization of Kangan Formation in well A in the South Pars Gas Field, geochemical analysis (including preliminary and complementary analysis such as Rock-Eval Pyrolysis, extraction of organic matter (EOM), bitumen fractionation, gas chromatography and gas chromatography-mass spectrometry) were carried out on core samples. Geochemical results reveal that these samples have kerogen type II and III, indicating a marine organic matter with a little terrestrial input. The organic matter 1 ناريا تفن يلم تكرش تفن تعنص هاگشهوژپ 2 لامش نارهت دحاو يملاسا دازآ هاگشناد ،تفن يسانش نيمز دشرا يسانشراك هتخومآ شنا Archive of SID

Reservoir characterization plays a critical role in appraising the economic success of reservoir management and development methods. This study identifies the different rock types that comprise reservoirs, marginal reservoirs and non-reservoirs. Porosity and permeability are the key parameters for identifying the rock types and reservoir characterization. The qualification of these parameters is usually measured directly from cores using conventional core analysis methods, and indirectly using geophysical well logs, well tests, and artificial neural network methods. However, for determination of rock types and reservoir evaluation, in addition to quantity of porosity and permeability we need to determine pore geometry and pore aperture size which are related to grain size, sorting and packing as well as to factors such as the mineralogy and diagenetic history of the reservoir. This paper presents the results of a combination of conventional core analysis, capillary pressure curve ch...

This study was carried out by using well logs to evaluate the depositional environments and hydrocarbon reservoirs in the Otuma oil field, Niger Delta basin. The gamma motif/model within- study interval in the drilled well shows blocky, symmetrical, and serrated shapes which suggest a deltaic front with mouth bar to a regressive - transgressive shoreface delta respectively. A correlation was done on the well logs across the wells and the ten well logs were used to evaluate the petrophysical characteristics of the reservoirs. The reservoirs showed highly porous and permeable channels where the wells were used for the characterization. The ten reservoirs were mapped at a depth range of 2395 m to 2919 m with thicknesses varying from 4m to 135m. The petrophysical results of the field showed that the porosity of the reservoirs ranges between 0.10 to 0.30, and permeability from 48 md to 290 md; the water saturation ranges from 0.39 to 0.52, and hydrocarbon saturation from the field 0.48 t...

Petrophysical properties evaluation of shaly sandstone reservoirs is a challenging task in comparison to clean sand reservoirs. Logging derived porosity in shaly sands requires shale correction and Archie's formula cannot be used in shaly sands for the determination of water saturation, therefore many water saturation models were proposed to get accurate water saturation of shaly sand reservoirs. In this paper, three water saturation models were used; two empirical models (Simandoux and total shale) and one theoretical model (effective medium model). Shale corrected density log was used in all models. The use of computer-generated algorithm, fuzzy log neural network is of increasing interest in the petroleum industry. This paper presents artificial neural network (ANN) as an effective tool for determining porosity and water saturation in shaly sand reservoir using well logging data. ANN technique utilizes the prevailing unknown nonlinear relationship in data between input logging data and output petrophysical parameters. Results of this work showed that ANN can be supplement or replacement of the existing conventional techniques to determine porosity and water saturation using empirical or theoretical water saturation models. Two neural networks were presented to determine porosity and water saturation using GR, resistivity and density logging data and adapted cut off for porosity and water saturation. Water saturation and porosity were determined using conventional techniques and neural network approach for two wells in a shaly sand reservoir. Neural network approach was trained for porosity and water saturation using the available well logging data. The predicted porosity and water saturation values have shown good matching with the core data in the two wells in comparison to the porosity and water saturation derived from the conventional techniques. This work showed that developed neural network (ANN) could provide an accurate porosity and water saturation in shaly sands reservoirs, it is subject to volume of available well logging data.