Interpretation Of Logging Data Research Articles

A novel approach to classify lithology of reservoir formations using GrowNet and Deep‐Insight with physic‐based feature augmentation

AbstractManual interpretation of geophysical logging data can be a tedious and time‐consuming task in the case of the nonlinear behavior of well‐logging signals. This study aims to enhance lithology classification of reservoir formations through advanced machine learning (ML) and deep learning (DL) techniques, introducing and comparing three novel algorithms, GrowNet, Deep‐Insight, and blender, against traditional models like random forest (RF) and support vector machine (SVM). Data from the South and North Viking Graben regions, encompassing 12 lithological facies, was preprocessed through cleaning, normalization, transformation, and imputation of missing values using regression models. The data set was enhanced with physic‐based features and balanced using SMOTE and NearMiss algorithms. Deep‐Insight converted tabular data into images for a convolutional neural network (CNN), significantly improving classification accuracy compared to conventional models such as decision trees (DTs). GrowNet and blender models leveraged hybrid approaches for enhanced performance. These hybrid approaches successfully addressed data imbalance and enhanced model learning, outperforming classic methods. The GrowNet and blender models for lithology classification successfully increased the penalty score and accuracy compared to the FORCE 2020 competition. Additionally, introducing the class prediction error plot visualizes multiclass classification performance more effectively than using a confusion matrix. These novel models in multiclass classification contribute to the petroleum industry by providing more accurate and reliable lithology classification, thereby improving reservoir characterization and exploration efficiency.

Evaluation of Fracturing Effect of Tight Reservoirs Based on Deep Learning.

The utilization of hydraulic fracturing technology is indispensable for unlocking the potential of tight oil and gas reservoirs. Understanding and accurately evaluating the impact of fracturing is pivotal in maximizing oil and gas production and optimizing wellbore performance. Currently, evaluation methods based on acoustic logging, such as orthogonal dipole anisotropy and radial tomography imaging, are widely used. However, when the fractures generated by hydraulic fracturing form a network-like pattern, orthogonal dipole anisotropy fails to accurately assess the fracturing effects. Radial tomography imaging can address this issue, but it is challenged by high manpower and time costs. This study aims to develop a more efficient and accurate method for evaluating fracturing effects in tight reservoirs using deep learning techniques. Specifically, the method utilizes dipole array acoustic logging curves recorded before and after fracturing. Manual labeling was conducted by integrating logging data interpretation results. An improved WGAN-GP was employed to generate adversarial samples for data augmentation, and fracturing effect evaluation was implemented using SE-ResNet, ResNet, and DenseNet. The experimental results demonstrated that ResNet with residual connections is more suitable for the dataset in this study, achieving higher accuracy in fracturing effect evaluation. The inclusion of the SE module further enhanced model accuracy by adaptively adjusting the weights of feature map channels, with the highest accuracy reaching 99.75%.

Petrophysical Properties Estimation by Using Well Log and Core Data Interpretation for Tertiary Reservoir in Ajeel Oil Field

Understanding the petrophysical properties of reservoirs is paramount for assessing their characteristics and estimating the potential of oil-bearing formations. This study focuses on the tertiary reservoir in the Ajeel oil field, renowned for its heterogeneous carbonate nature and diverse production formations, including Jeribe, Dhiban, and Euphrates. The formation of the tertiary reservoir is evaluated through a comprehensive analysis of petrophysical properties utilizing well log data from well AJ-25 and core analysis data (routine and special analysis). The study reveals significant insights into the petrophysical properties of the formations. The effective porosity values for the Jeribe, Dhiban, and Euphrates formations are determined as 15.41%, 4.65%, and 9.85%, respectively, with lithology predominantly consisting of dolomite rock interspersed with limestone slices and anhydrite nodules. A high Secondary Porosity Index (SPI) indicates fractures. Archie's Parameters, obtained from a Pickett Plot, yield cement coefficient (m=1.8), saturation exponent (n=1.9), and tortuosity factor (a=1.19). Water saturation levels for the Jeribe, Dhiban, and Euphrates formations are 33%, 86%, and 81%, respectively, with porosity and water saturation cutoff values determined as 10% and 60%, respectively. Net to Gross of Jeribe, Dhiban, and Euphrates formation are 0.706, 0.029, and 0.011, respectively. Jeribe Formation is identified as an oil-bearing zone. In contrast, the Dhiban and Euphrates formations are identified as water-bearing zones. To enhance the accuracy of petrophysical assessments, modern well logging techniques, such as the Formation Micro Scanner log (FMI log), are recommended to investigate fractures and their impact on field performance, as traditional logs may not adequately capture these features. Additionally, our comparative analysis highlights superior petrophysical properties of the Euphrates Formation compared to the Jeribe Formation. Therefore, prioritizing drilling and completion activities in the Euphrates Reservoir within the field, contingent upon its positioning relative to the oil-water contact level, is suggested for optimizing reservoir performance.

Prediction of Structural Fracture Distribution and Analysis of Controlling Factors in a Passive Continental Margin Basin—An Example of a Clastic Reservoir in Basin A, South America

Structural fracture distribution is essential in oil and gas transportation and development in passive continental margin basins. In this paper, taking as an example the clastic reservoirs in the A-Basin, a passive continental margin in northeastern South America, the paleotectonic stress field of the Late Cretaceous Maastrichtian formation in Basin A was numerically simulated by finite element technique through the integrated interpretation of seismic total data, logging data and core data, and the distribution of tectonic fractures was later predicted based on rock fracture criterion. The results of the study show that: (1) The distribution of tectonic stress and fractures during the Late Cretaceous Maastrichtian formation of Basin A is affected by the fracture zone, mechanical properties of rocks and tectonic stress, regions with extensive fracture development are susceptible to stress concentrations, resulting in significant stress gradients. (2) The development of structural fractures in the study area was predicted using the Griffiths criterion, and the tensile rupture coefficient T was introduced to quantitatively characterise the intensity of fracture development, with larger values reflecting a higher degree of fracture development. The well-developed and relatively well-developed fractures are mainly located in the fracture zones and the interior of submarine fans. (3) Fracture zones and sedimentary phases mainly control structural fractures in Basin A; within 5 km outside the fracture zones, the development of fractures is controlled by the fracture zones, beyond which the regional tectonic stress field controls them; inside the sedimentary fan, the development of fractures is controlled by the sedimentary subphase, which decreases in the order of the upper fan, the middle fan, and the lower fan; inside the subphase, they are controlled by the regional tectonic stress field, and the fractures show the increasing trend in the direction of NW-NE.

Impacts of sedimentary characteristics and diagenesis on reservoir quality of the 4th member of the Upper Triassic Xujiahe formation in the western Sichuan basin, southwest China

The 4th member of Xujiahe Formation (Xu4) in the western Sichuan Depression is a typical porous tight sandstone reservoir. Finding reservoirs with relatively high porosity controlled by sedimentation and diagenesis is crucial for successful tight gas exploration. In this study, the Xu4 sandstone was studied by diverse methods, including outcrop and core observation, logging data interpretation, thin section and cathodoluminescence examination, scanning electron microscopy analysis, and X-ray diffraction, to determine sedimentary and diagenetic characteristics and to discuss their impact on the sandstone reservoir quality. During the depositional period of Xu4, subaqueous distributary channel sandstone of braided river delta front developed extensively under controls of bidirectional provenance (LASP and SASP), mainly consisting of litharenite and sublitharenite, with low feldspar and high rock fragments volume, respectively. Strong compaction and carbonate cementation have largely destroyed primary porosity, while secondary pores constitute the main pore space in the Xu4 sandstone. The sediment provenance, sedimentary microfacies and A/S determine the clastic composition of sandstone, genetic type and thickness of sand bodies, furthermore affect the subsequent diagenetic variations. The larger the thickness of the sand body indicates a higher-energy depositional environment, coarser grain size, better sorting, and lower shaliness content of the sandstone during deposition period. This results in stronger resistance to compaction of the sandstone, which is conducive to the preservation of primary pores and dissolution of organic acids, resulting in better physical properties of sandstone. Among them, the physical properties of the sandstones of the Xu4s and Xu4x are better than those of the Xu4z; moreover, LASP's sandstone is superior to SASP. It is worth noting that subaqueous distributary channel sandstones with thickness exceeding 13 m in Xu4s and Xu4x from LASP represent favorable areas for high-quality reservoirs. The work can be used as a reference for the exploration and evaluation of similar tight sandstone gas in the world.

Rock physics-based anisotropy parameters estimation of Marcellus Shale using log data acquired in a vertical well

The elastic properties of shale rock exhibit anisotropy due to the presence of highly anisotropic clay minerals and their alignment. This anisotropy has a significant impact on geophysical and geomechanical responses. However, the elastic anisotropy of shale is often overlooked due to the difficulty in measuring sufficient parameters in the field, resulting in a gap between theoretical understanding and practical implementation. To address this issue, a rock physics-based approach was tested on log data obtained from a vertical well in the Marcellus Shale to estimate anisotropy parameters. The approach utilized a rock physics model based on the Sayers-den Boer method with model parameters optimized using measured stiffness parameters C33, C55, and C66. Anisotropy parameters δ and ε were then calculated using these optimized model parameters. The optimized model parameters and estimated anisotropy parameters are consistent with existing studies, indicating the correctness of the model. Additionally, the rock physics model was used to investigate the impact of gas saturation on the vertical VP/VS ratio and ε/γ ratio. It was found that gas saturation has a significant impact on these ratios. This carries important implications for acoustic log data interpretation and seismic characterization of shales.

Jurassic sedimentary evolution model and its implication for the sandstone-type uranium mineralization in the Kamusite area in eastern Junggar Basin, NW China

The Junggar Basin in the northern Xinjiang Province, northwestern China, is a large hydrocarbon basin with tremendous reserves of oil, gas and coals. Tens of sandstone-type uranium showings, occurrences and/or anomalies have also been discovered in the Junggar Basin since the 1960s, yet hitherto only one large uranium deposit, the Kamusite deposit, has been identified in the Middle Jurassic Toutunhe Formation sandstones in the eastern part of the basin. Sand bodies with high-permeability are the prerequisite for the formation of the in situ leachable sandstone-hosted uranium deposit, nevertheless the spatial distribution and genetic types of the sand bodies, as well as the deposition model in Jurassic time in the Kamusite area both remain unclear, which largely hindered the understanding of the sedimentary evolution and uranium exploration directions in the region.In this contribution, based on the outcrop observation, core logging and well logging data interpretation, and comprehensive analysis, the sedimentary characteristics, sedimentary facies types, sand body morphology, plane distribution characteristics, as well as the sedimentary evolution history in Jurassic time in the Kamusite area have been illustrated in details. From early to late, the Jurassic sediments in Kamusite can be divided into the Badaowan, Sangonghe, Xishanyao, Toutunhe and Qigu formations, of which the sand bodies favorable for the sandstone-type uranium mineralization have been systematically analyzed, and the depositional model in the Kamusite area have been established. The Early Jurassic Badaowan Formation is a set of coal-bearing coarse-grained clastic sediments of the braided river–braided river delta facies, followed by the lake transgression and fine-grained lacustrine deposition in the Sangonghe Formation. The Middle Jurassic Xishanyao Formation is a set of braided river delta facies coal-bearing clastic sediments, while the uranium orebody-bearing Toutunhe Formation underwent the paleoclimate transition from warm and humid to hot and arid, and developed a set of braided river delta to meandering river facies sequences with an overall positive sedimentary rhythm. The Qigu Formation is dominated by a series of meandering river to lacustrine facies fine-grained sediments and largely denuded by later tectonic activities. Three sets of sand bodies favorable for the sandstone-type uranium mineralization are recognized, including those in the lower Toutunhe Formation, the lower Xishanyao Formation, and the upper Badaowan Formation, from bottom to top. A four-stage sedimentary evolution model from the Badaowan Formation to the Toutunhe Formation has been established thereafter, and general exploration suggestions were proposed in the last of the contribution. More drilling is recommended to the south of the Kalasayi Fault, aiming the lower Toutunhe, lower Xishanyao and upper Badaowan formations. To the north of the Kalasayi Fault, more uranium mineralization could also be expected, and the exploration is suggested to focus on the Jurassic Toutunhe, Xishanyao formations and Cretaceous Tugulu Group.

Automated processing of well logging data to monitor the position of the gas-water contact in underground gas storage facilities

Natural oil and gas deposits in most fields include some fluid contacts, such as oil–water, gas–water, or gas–oil. Monitoring the position of the gas–water contact in underground gas storage (UGS) facilities is crucial for monitoring the safety of the subsurface environment. As UGS facilities are geological features of long-term operation, the condition of these features must be regularly monitored for possible gas leaks due to various reasons, whether geological or technical. Periodic surveys of production wells using geophysical methods make it possible to timely detect the reasons for abnormal technical conditions and higher-than-normal water cuts of reservoirs, and to assess shifts in gas–water contact. The suite of production logging methods for surveying and monitoring underground gas storage facilities includes nuclear logging with the use of steady radiation sources (i.e., gamma ray logging and neutron logging). Analysis and interpretation of these methods make it possible to track the shift over time of the gas–water contact in gas-saturated sandstones with an interparticle porosity of >15%. Data from nuclear logging, temperature logs, and composition-based and flow-based surveying are processed and interpreted with the use of known methods and diagnostic indicators to achieve the following goals: to determine the intervals of inter-reservoir and behind-the-casing fluid movement on the base of the well log, to assess the technical condition of the wellbore, to monitor the position of the gas–water contact in the reservoir, to assess the gas saturation of the reservoir, and to monitor the thickness and integrity of the clay caprocks of UGS facilities [1]. This paper discusses the results of automated processing and interpretation of well data recorded during the survey of an UGS facility to determine the current position of the gas–water contact in the reservoir and the gas–water interface in the well. Quantitative interpretation of the neutron logging data with the use of steady radiation sources was performed, and the current gas saturation factor was estimated. Keywords: gas–water contact (GWC); gas saturation; underground gas storage; processing algorithm; gas–water interface (GWI).

Hybrid parameters for fluid identification using an enhanced quantum neural network in a tight reservoir

This paper proposes a fluid classifier for a tight reservoir using a quantum neural network (QNN). It is difficult to identify the fluid in tight reservoirs, and the manual interpretation of logging data, which is an important means to identify the fluid properties, has the disadvantages of a low recognition rate and non-intelligence, and an intelligent algorithm can better identify the fluid. For tight reservoirs, the logging response characteristics of different fluid properties and the sensitivity and relevance of well log parameter and rock physics parameters to fluid identification are analyzed, and different sets of input parameters for fluid identification are constructed. On the basis of quantum neural networks, a new method for combining sample quantum state descriptions, sensitivity analysis of input parameters, and wavelet activation functions for optimization is proposed. The results of identifying the dry layer, gas layer, and gas–water co-layer in the tight reservoir in the Sichuan Basin of China show that different input parameters and activation functions affect recognition performance. The proposed quantum neural network based on hybrid parameters and a wavelet activation function has higher fluid identification accuracy than the original quantum neural network model, indicating that this method is effective and warrants promotion and application.

3D modeling of salt domes according to detailed drilling data in the Precaspian region

To create three-dimensional models of arcomorph structures based on detailed data of drilling without involving genetic considerations and indirect information, the potential fields method is effective, which consists of finding an approximating three-dimensional function, the set of isolevel surfaces of which are identified with stratigraphic boundaries, using the coordinates of the formation intersection points. For approximation, mainly three-dimensional splines expressed in terms of Green’s functions were used. The main difficulties are associated with the presence of structural unconformities, to take into account which the initial data, and the models built on their basis, are subjected to special spatial transformations. To avoid the influence of high-amplitude arcomorphs on the geometry of the layers of the pre-salt complex, the modeling of the latter was carried out separately from the intensely deformed evaporates and overlying layers. Assaying of the method was carried out at one of the sites in the Caspian Sea. On the study area, according to the interpretation of logging data from 249 wells, a three-dimensional model was created, including several arcomorph structures, and covering the stratigraphic interval from the Emsian stage of the Lower Devonian to Quaternary deposits. The results confirmed the presence of arcomorphs with overturned beds. Such structural forms are poorly fixed by 2D–3D seismic survey methods. The proposed method can be applied in geological studies in the search and exploration of hydrocarbons in salt dome areas.

Fluid Identification Method of Nuclear Magnetic Resonance and Array Acoustic Logging for Complex Oil and Water Layers in Tight Sandstone Reservoir

In order to improve the logging interpretation accuracy for complex oil and water layers developed in tight sandstone reservoirs, this study takes the Chang 8 member of the Yanchang Formation in the Huanxian area as the research object, and two new fluid identification methods were constructed based on nuclear magnetic resonance (NMR) logging and array acoustic logging. Firstly, the reservoir characteristics of physical properties and conductivity were studied in the research area, and the limitations of conventional logging methods in identifying complex oil and water layers were clarified. Then, the sensitive parameters for identifying different pore fluids were established by analyzing the relationship between NMR logging and array acoustic logging with different pore fluids. On this basis, the fluid identification plate, composed of movable fluid apparent diffusion coefficient and effective porosity difference (Da-Δφe) by NMR logging data of D9TWE3 observation mode, and the other fluid identification plate, composed of apparent bulk modulus of pore fluid and elastic parameter sensitive factor (Kf-Fac), were constructed, respectively. Finally, these two fluid identification methods were used for reservoir interpretation of actual logging data. This study shows that the two new fluid identification methods constructed by NMR logging and array acoustic logging can effectively eliminate the interference of rock skeleton on logging interpretation, which make them more effective in identifying complex oil and water layers than the conventional logging method. Additionally, the two methods have their own advantages and disadvantages when used separately for interpreting complex oil and water layers, and the comprehensive interpretation of the two methods provides a technical development direction for further improving the accuracy of logging the interpretation of complex oil and water layers.

A sandwich resonant bar method with transfer matrices for measuring the elastic parameters of rock at low frequency

Abstract Rocks and other geological materials have appreciable dispersion in their elastic properties. Rock elastic parameters within the same frequency range as the logging frequency band (1–20 kHz) should be determined to facilitate reservoir prediction and interpretation of logging data. This study suggests a technique for determining the elastic characteristics of rock cores at low frequencies using a sandwich resonant bar by integrating transfer matrices into the one-dimensional transmission model. The frequency response expression of the sandwich resonant bar is derived analytically and then the response is simulated accurately based on this expression. Numerical results show that the first two-order longitudinal resonance frequencies are approximately linearly related to the inverse of the sample's Young's modulus and the density, respectively. In addition, an inversion algorithm based on Gauss–Newton iteration, which converges faster and more efficiently, is proposed in this paper. The residuals between the model's first two resonant frequencies and the simulated results are used as the error function, and the elasticity parameters that minimize the error function are the best estimate for creating the model. This research is valuable for measuring rock elastic parameters accurately in the kilohertz range, which is of practical significance in dispersion-related studies relating to rock cores.

Oil potentialities of West Esh El-Mallaha area, southern Gulf of Suez as deduced from well log data interpretation

Oil potentialities of West Esh El-Mallaha area, southern Gulf of Suez as deduced from well log data interpretation

Processing and Understanding Moodle Log Data and Their Temporal Dimension

The increased adoption of online learning environments has resulted in the availability of vast amounts of educationallog data, which raises questions that could be answered by a thorough and accurate examination of students’ onlinelearning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensionsthat help to characterize what actions students take, when, and where (in which course and in which part of thecourse). Temporal analysis has been shown to be relevant in learning analytics (LA) research, and capturingtime-on-task as a proxy to model learning behaviour, predict performance, and prevent drop-out has been thesubject of several studies. In Moodle, one of the most used learning management systems, while most events arelogged at their beginning, other events are recorded at their end. The duration of an event is usually calculated asthe difference between two consecutive records assuming that a log records the action’s starting time. Therefore,when an event is logged at its end, the difference between the starting and the ending event identifies their sum,not the duration of the first. Moreover, in the pursuit of a better user experience, increasingly more online learningplatforms’ functions are shifted to the client, with the unintended effect of reducing significant logs and conceivablymisinterpreting student behaviour. The purpose of this study is to present Moodle’s logging system to illustratewhere the temporal dimension of Moodle log data can be difficult to interpret and how this knowledge can be usedto improve data processing. Starting from the correct extraction of Moodle logs, we focus on factors to considerwhen preparing data for temporal dimensional analysis. Considering the significance of the correct interpretation oflog data to the LA community, we intend to initiate a discussion on this domain understanding to prevent the loss ofdata-related knowledge.

A research on a GA-BP neural network based model for predicting patterns of oil-water two-phase flow in horizontal wells

At present, unconventional oil reservoirs are usually exploited by means of horizontal wells. However, due to the influence of multiple factors such as well deviation, oil flowrate and water flowrate, the distribution (flow pattern) of oil and water in a wellbore is complex. In addition, an accuracy of flow pattern identification is also vital for accurately interpreting the oil-water two-phase production profile of a horizontal well. Therefore, the research on flow pattern prediction of wellbores is of great application significance. Firstly, at normal pressure and temperature, based on the multiphase flow simulation experiment device, a transparent glass wellbore with a diameter similar to the actual downhole well was used to carry out oil-water two-phase simulation experiments with different well deviations, different flowrates and different water cuts, while visual observation and whole-process HD video recording of oil-water flow states were performed. Secondly, with reference to the typical horizontal well oil-water two-phase theoretical flow pattern, the flow patterns under different experimental conditions were identified, and the distribution diagram of flow patterns at four well deviation angles was drawn. Then, the GA-BP neural network was used for learning and prediction of experimental flow pattern data, and a model for predicting four experimental flow patterns was established to realize the flow pattern prediction under different well deviations and different flowrates in horizontal well. Finally, the above prediction model was verified based on 24 data points of two sample wells. After comparison with logging data, it was found that the accuracy of identifying flow patterns through the prediction model was high, and the overall coincidence rate reached up to 87.25%, indicating that the prediction model met the requirements for interpretation of actual logging data.

Heterogeneity of reservoirs of the Qala suite (on the example of the Neft Dashlary field)

In order to study the heterogeneity of reservoir rocks based on core materials and well logging data, an analysis of the lithological-petrographic and reservoir properties of the rocks of the Qala suite of the PS of the Neft Dashlary field was carried out. For a more detailed study, an analysis of laboratory data on subformations (QaS1, QaS2, QaS3 and QaS4) has been carried out, the grainsize composition and reservoir properties (porosity, clay content, permeability and carbonate content) of reservoir rocks were studied. Based on the results of logging data interpretation and analysis of the constructed correlation schemes, heterogeneity, including the study of reservoirs thickness and the variability of their reservoir properties over the area have been studied. Keywords: Kalinskaya suite; Core; Logging; Heterogeneity.

Development and controlling factors of shale lithofacies cycles in a continental rift basin: A case study of Es4u in the Boxing Subsag of Dongying Sag, Bohai Bay Basin, China

The shale of the upper Es4 formation (Es4u), deposited during the Eocene in the Boxing Subsag of the Dongying Sag, is a typical set of lime-rich lacustrine shale in a continental rift basin. Through logging data interpretation, core and thin section observations, and geochemical elements [obtained by X radial fluorescence (XRF) mud logging] analysis, the development and controlling factors of lithofacies cycles of Es4u shale were analyzed. The results show that 22 types of lithofacies with typical characteristics are developed in Es4u, indicating the sedimentary environments, such as lower lakeshore (LL) slope zone; upper, middle, and lower shallow-lake slope zones; semi-deep-lake zone; and deep-lake zone. Lithofacies cycles in three scales are recognized in Es4u: small-scale lithofacies cycles indicated by alternate development of two lithofacies, mesoscale lithofacies cycles indicated by the repetition of lithofacies associations or regular variation of multiple lithofacies, and large-scale lithofacies cycles indicated by regular variation of well logging curves, which have the average thickness of approximately 0.4, 5, and 35 m, respectively. According to the vertical variation of astronomical parameters and lithofacies cycles, the periodic change in long eccentricity has a close relationship with the large-scale lithofacies cycle, the periodic change in slope is closely relative to the mesoscale lithofacies cycle, and the periodic change in precession is closely related to small-scale lithofacies cycle. However, the periodic change in short eccentricity correlates poorly with lithofacies cycles. The climate change reflected by long eccentricity and slope is quite distinct from the actual basin climate reflected by the paleoclimatic parameters (e.g., Rb/Sr and Sr/Cu), indicating that the basin paleoclimate was greatly influenced by the paleogeological conditions. For shale in Es4u of the Boxing Subsag, approximately 55% of the shale stratigraphic record is dominantly controlled by the astronomical climate and 45% by the paleogeological conditions. Affected by the paleogeological conditions, large-scale and mesoscale lithofacies cycles are different in lithofacies types and superimposition patterns, and just small-scale lithofacies cycles are found repetitive vertically. These findings suggest that the lithofacies cycles of shale in a continental rift basin are a product of astronomical driving mechanism (Milankovitch forcing) and variation of local paleogeological conditions, which is apparently different from the sedimentary record of marine shale that is evidently controlled by the Milankovitch cycle. Therefore, the lithofacies cycles should be comprehensively analyzed under the background of actual basin paleoclimate.

A new semianalytical algorithm for rapid simulation of triaxial electromagnetic logging responses in multilayered biaxial anisotropic formations

A set of compact and stable formulas are developed for the computation of triaxial electromagnetic (EM) logging responses in multilayered formations with biaxial anisotropy. These formulas are based on a new global amplitude propagator matrix (GAPM) algorithm, which derives the amplitudes of upgoing/downgoing waves at the boundaries rather than the reflection/transmission coefficients of each layer. The kernel of the GAPM algorithm is assembling the local continuity equations into a global linear system, which has addressed the notorious overflow problems commonly encountered by the traditional coefficient propagator matrix approach. To fast and accurately convert the EM fields from the spectral domain into the spatial domain, an efficient twofold inverse Fourier transform (IFT) technique is established for the computation of triaxial EM logging responses. Two main techniques are developed to significantly improve the computation accuracy and speed of IFT. On the one hand, the spectral fields at the first integral quadrant can be used to express the fields at the other three quadrants. Consequently, the original twofold infinite integral is analytically simplified to a semiinfinite one and the computation cost can be reduced by three-fourths. On the other hand, a two-level subtraction scheme is developed to reduce the integral singularity. The first-level subtraction is achieved by separating the primary fields from the total fields. The second-level process includes subtracting the spectral scattered fields of an equivalent transverse isotropic (TI) layered medium, integrating the residual fields, and computing the spatial fields of the TI model. The subtractions on the primary and scattered fields can make the integral convergence increase by more than 10 orders of magnitude in favorable conditions. Numerical experiments demonstrate that the new semianalytical formulas are well suited for any dipping angle and an arbitrary number of layers, as well as for thin and thick formations. The modeling method is efficient and robust, which can provide a fast simulator for the interpretation of triaxial EM logging data.

Extracting mud invasion information using borehole radar — A numerical study

In hydrocarbon drilling, mud filtrate penetrates permeable formations and alters the pore fluid characteristics in the immediate vicinity of the borehole. Typically, the prevailing in situ pore fluids are displaced by the invading mud filtrate, which leads to gradually changing distributions of the fluid and electrical properties. Understanding this invasion process is crucial for the interpretation of logging data and associated reservoir evaluations. Conventional logging methods tend to be inadequate for this purpose as their resolution is too low. We find that invasion depth can be determined from borehole radar data using an optimized antenna configuration and time-lapse measurements. A series of parametric sensitivity analyses provide information about the effects of variations of the rock and fluid properties on the identification and extraction of borehole radar signals reflected from the invasion front. Our results suggest that by embedding the radar antennas in cavities filled with an absorbing dielectric material, it is possible to minimize the interference arising from the metal components of the logging tool. In the simulated reservoir scenario, a time-lapse measurement mode with a time interval of at least 6 h can reliably extract the radar signals reflected from the invasion front, and the proposed borehole radar has a lateral detection range from 0.15 to 1 m. A comprehensive range of parametric sensitivity analyses indicates that the signals reflected from the invasion front are principally influenced by oil viscosity, porosity, and mud and formation water salinity, as well as by molecular diffusion coefficient and cementation exponent. These properties and parameters should be carefully explored and assessed when applying borehole radar to evaluate mud invasion information in a reservoir environment.

Возможности прогнозирования перспективных зон развития коллекторов осинского горизонта на Среднеботуобинском месторождении

The prediction process of reservoir properties is one of the significant targets during an explo-ration stage on the Srednebotuobinskoye field. At the moment, there are a lot of well data, including log and core data. The authors get conclusions regarding a formation and structure of the osinskiy horizon within the Srednebotuobinskoye field. The petrophysical model and the log data interpretation in osinskiy horizon based on actual information were completed. The petrophysical basis of seismic inversion was completed. It is proposed that the employment of the optimal approach to seismic inversion process can help to get more precise prediction reservoir maps than earlier and to minimize exploitation drilling risks.