Logarithmic Curve Research Articles

Quantitative identification of triassic top unconformity: vertical structure and its reservoir significance in the sanbian area of the ordos basin

The Triassic top unconformity in the Ordos Basin, which serves as a transfer station for hydrocarbon migration, has become a bottleneck for Mesozoic oil and gas exploration. Taking the Sanbian area as an example, based on core observations, petrophysical properties, and a weathering index analysis of five coring wells, a standard for the quantitative identification of the vertical structure of the unconformity is established using the optimal segmentation method and principal component analysis of conventional logging curves. The standard is then applied to 40 real wells, and 32 typical unconformity reservoirs are dissected. The results show that the reclassification of the unconformity surface corrects the 17.5% error in the geological stratification as an unconformity. On this basis, a quantitative identification standard for the structure of the unconformity is established via the principal component curve. The analysis of unconformity structure types applied to five paleogeomorphic units reveals that the slope mouth and slope develop three layers of structure, namely residual layer, weathered clay layer, and weathered leaching zone, while highlands, river valleys, and inter-river hills lack weathered clay layer. As an independent oil and gas-bearing layer, the unconformity has two types of reservoir-forming models. The first is the hydrocarbon accumulation in the Chang1–Chang2 member shielded by weathered clay layer in the slope mouth and slope. The second is hydrocarbon migrated from the residual layer to the local structural high part of the Yan 10–Yan 9 member in the slope mouth. The hydrocarbon in the unconformity is complementary to the upper Yan 10–Yan 9 member and the lower unweathered rock layer of Yanchang Formation. The results of this study are of great significance to the quantitative identification of unconformity structures in exploration wells without coring data in the study area, as well as to future hydrocarbon exploration in the Mesozoic strata.

Maternal pruritus gravidarum and its long-term effect on dermatological morbidity in the offspring

Purpose Pruritus gravidarum is characterized by general pruritus in the absence of primary skin lesions. In this study, we sought to evaluate whether the offspring (≤ 18 years) of mothers diagnosed with pruritus gravidarum, are at increased risk of long-term dermatology-related hospitalization. Methods A population-based, retrospective cohort study of all singleton deliveries between 1991 and 2021 was conducted at a tertiary medical center. Offspring of mothers diagnosed with pruritus gravidarum were compared to offspring of non-exposed mothers. First admission involving dermatological morbidity of the offspring were analyzed using ICD-9 codes. Kaplan-Meier survival curves were used to compare the cumulative hospitalization incidence between the groups and Cox regression models were utilized to adjust for confounding variables. Results A total of 849 women out of 356,356 deliveries that fulfilled the inclusion criteria were diagnosed with pruritus gravidarum during pregnancy (0.23%). Among offspring to mothers with pruritus gravidarum versus non-pruritus gravidarum mothers, hospitalization rates involving dermatological morbidity, were higher (7.1% vs. 4.6%, p < .001) a finding that was consistent with the Kaplan-Meier survival curve (Log rank p = .002). In the Cox regression model, pruritus gravidarum was found to be a significant independent risk factor for dermatological-related hospitalizations in the offspring after controlling for gestational age, hypertensive disorders, diabetic disorders, meconium-stained amniotic fluid exposure and fertility treatments (adjusted HR = 1.44, 95% CI 1.12–1.85, p = .004). Conclusions Maternal pruritus gravidarum is an independent risk factor for long-term dermatology-related hospitalization in the offspring up to the age of 18 years.

High‐resolution reservoir stochastic modelling based on optimized estimation of vertical autocorrelation

AbstractThe high‐resolution model of elastic properties is of great significance for fine reservoir characterization and precise oil and gas exploration. However, it is difficult to obtain a satisfactory high‐resolution reservoir model with the existing technologies. In this paper, a novel high‐resolution stochastic modelling strategy based on the fast Fourier transform moving average is proposed. In this strategy, several structural parameters are optimized to improve the rationality of the stochastic model, including vertical autocorrelation length, horizontal autocorrelation length, roughness factor and angle parameter. Among them, the optimization of the vertical autocorrelation length is crucial for vertical high‐resolution modelling. To this end, a nonlinear optimal inversion strategy of the vertical autocorrelation length is designed based on the idea of minimizing the spectral Jensen–Shannon divergence between the modelling result and the logging curve. However, nonlinear inversion is usually unstable, so it is necessary to introduce a regularization operator in the inversion to improve the stability. Considering that the heterogeneity of the subsurface medium is consistent or gradual within the stratums, but discontinuous and abrupt at the interfaces, edge‐preserving regularization is applied to obtain a blocky estimation of the vertical autocorrelation length. The optimal estimation experiment of the vertical autocorrelation length based on the measured logging data shows that the edge‐preserving regularization significantly improves the stability of the nonlinear optimal inversion, and blocky estimation results with sharp edges are obtained. Then, the optimized vertical autocorrelation length and the other structural parameters are applied to fast Fourier transform moving average modelling on an actual reservoir profile. The result shows that the resolution of the model is significantly improved, which realizes the fine reservoir characterization. In addition, the optimized structural parameters effectively constrain the small‐scale heterogeneity and ensure the rationality of the stochastic model.

An adaptive ensemble learning by opposite multiverse optimizer and its application in fluid identification for unconventional oil reservoirs

Unconventional reservoirs are rich in petroleum resources. Reservoir fluid property identification for these reservoirs is an essential process in unconventional oil reservoir evaluation methods, which is significant for enhancing the reservoir recovery ratio and economic efficiency. However, due to the mutual interference of several factors, identifying the properties of oil and water using traditional reservoir fluid identification methods or a single predictive model for unconventional oil reservoirs is inadequate in accuracy. In this paper, we propose a new ensemble learning model that combines 12 base learners using the multiverse optimizer to improve the accuracy of reservoir fluid identification for unconventional reservoirs. The experimental results show that the overall classification accuracy of the adaptive ensemble learning by opposite multiverse optimizer (AIL-OMO) is 0.85. Compared with six conventional reservoir fluid identification models, AIL-OMO achieved high accuracy on classifying dry layers, oil–water layers, and oil layers, with accuracy rates of 94.33%, 90.46%, and 90.66%. For each model, the identification of the water layer is not accurate enough, which may be due to the classification confusion caused by noise interference in the logging curves of the water layer in unconventional reservoirs.

An intelligent identification method of interlayers in deep clastic rock – An example of Donghe Sandstone in Hade Oilfield, Tarim Basin

The identification of interlayer types is the key to improve the geological model to study the characteristics of oil and water distribution. The Donghe Sandstone in Hade Oilfield is used as the research object to calibrate the interlayer type and location by means of the outcrop, core, conventional logging curves and electrical imaging data. However, the logging response characteristics of different types of interlayers are similar, which is difficult to be accurately characterized by the conventional method. Therefore, a Random Forest (RF) intelligent method based on the Ensemble Empirical Mode Decomposition (EEMD) and Hilbert Huang Transform (HHT) is proposed to identify the type of intercalation layer. The model consists of two parts: firstly, EEMD-HHT is used to automatically identify the location of the interlayer, secondly, RF is used to classify the interlayer type. The results show that the EEMD-HHT-RF model corresponds to the results of core identification of interlayer, which can achieve rapid identification and accurate prediction in the block.

A Method for Judging the Effectiveness of Complex Tight Gas Reservoirs Based on Geophysical Logging Data and Using the L Block of the Ordos Basin as a Case Study

As an important unconventional oil and gas resource, the tight gas reservoir faces many technical challenges due to its low porosity, low permeability, and strong heterogeneity. Among them, the accurate definition of effective reservoirs and ineffective reservoirs in tight gas reservoirs directly affects the formulation and adjustment of subsequent development plans. This paper proposes a reservoir effectiveness identification method based on double factors based on conventional geophysical logging data and core experimental data. The double factors considered are based on the logging response and physical parameters of the reservoir. The identification factor F1 is obtained by using the difference in the logging response values of the natural gamma logging curve, compensated density logging curve, and acoustic time difference logging curve in different reservoirs combined with mathematical operation, and the identification factor F2 is calculated by using porosity parameters combined with Archie’s formula. The validity of the reservoir can be judged by the intersection of the above double factors. This method is applied to the Shihezi Formation in the L block, and the applicability of the double factors is compared and analyzed using the traditional method. The results show that the method has strong applicability in tight gas reservoirs and that the accuracy rate reaches 96%. Compared with the direct use of the porosity lower limit method, the accuracy of the judgment is significantly improved, and the calculation is simple, easy to implement, and unaffected by mud invasion. For study areas with different geological backgrounds, the process of this method can also be used to determine the effectiveness of the reservoir. The reservoir effectiveness identification method proposed in this paper has practical engineering significance and lays a solid foundation for subsequent fluid property identification, production calculation, and development plan formulation and adjustment.

The Intensification of Prolonged Cooling Climate-Exacerbated Late Ordovician–Early Silurian Mass Extinction: A Case Study from the Wufeng Formation–Longmaxi Formation in the Sichuan Basin

The Late Ordovician–Early Silurian period was a significant transitional phase in geological history and has garnered global interest. This study focuses on the black shale series of the Wufeng Formation–Longmaxi Formation of the Upper Ordovician–Lower Silurian period in the Sichuan Basin. Based on the logging curves and lithological characteristics of the Yucan-1 Well, 46 black shale samples were collected from the target layer section for clay mineral XRD (46 samples) analysis and whole-rock XRF (14 samples) analysis. The results indicate that three third-order sequences (SQ1, SQ2, and SQ3) are present in the Wufeng Formation–Longmaxi Formation of the Yucan-1 Well, and two subfacies and three microfacies were identified. In conjunction with the characteristics as well as the characteristic parameters of whole-rock oxide and clay mineral content ((I/C), (S + I/S)/(I + C), CIA, CIA-error, CIW, PIA, MAP, and LST), the Wufeng Formation–Longmaxi Formation of the Yucan-1 Well is divided into three intervals. Interval I is the Wufeng Formation. During this interval, weathering intensity, surface temperature, and precipitation gradually decreased, while the climate shifted from warm and humid to cold and dry. This corresponds to two pulse-type biological extinction events and represents an interval of increasing organic carbon burial. Interval II encompasses the bottom-middle part of the Longmaxi Formation. Weathering intensity, surface temperature, and precipitation were characterized by smooth, low values. Subsequently, the climate was predominantly cold and dry. This was the primary interval of organic carbon enrichment. Interval III extends from the upper part to the top of the Longmaxi Formation. Weathering intensity, surface temperature, and precipitation gradually increased. The climate transitioned from cold and dry to warm and humid. Organic carbon burial gradually decreased, while sea levels dropped. This indicates that climate cooling was the primary controlling factor for this biological extinction event. In combination with previous divisions of graptolite zones in the Yucan-1 Well, it is postulated that this biological extinction event may primarily have been pulse extinction. The continuous cooling of the climate in the later period led to the continuous extinction of organisms that survived the disaster. Until approximately 438.76 Ma at the top of the Longmaxi Formation, the climate environment recovered to pre-extinction conditions, with a transition to a warm and humid climate again.

Study on Permeability Calculation Method Based on J Function and Fractal Theory.

Permeability is a required parameter for studying aquifer properties. However, for sandstone aquifers with low permeability, it is difficult to measure permeability directly through experiments. Based on fractal theory and the J function, a new method to calculate the permeability of a sandstone aquifer is derived. This work first solves the J function under each water saturation according to its definition. Combined with mercury pressure data, the J function and logarithmic curve equation of water saturation are then fitted by the drawing method, and the fractal dimension and tortuosity of the aquifer are further solved. Finally, the aquifer's permeability is calculated using the new permeability calculation method. To verify the accuracy of the proposed method, 15 rock samples from the Chang 7 Group, Ordos Basin, are taken as research objects. The permeability is calculated using the new method combined with mercury injection data and aquifer characteristic parameters, and the results are compared with the real permeability. The relative error of most samples is <20%, which shows the permeability calculated by this method is accurate and reliable. The effects of fractal dimension, tortuosity, and porosity on permeability are also analyzed.

Petrophysical parameters inversion for heavy oil reservoir based on a laboratory-calibrated frequency-variant rock-physics model

Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs.

A comparative study of property-constant and property-variable icing models

ABSTRACT Icing on cold surfaces is ubiquitous in many natural and engineering processes, and various icing models have been proposed with little advice given on model selection. Here, we calculate the ice accretion characteristics using property-constant and property-variable icing models under different airflow parameters. The ice thickness, water film thickness, temperature profile, critical ice thickness, and critical time are compared. The property-variable icing model yields a larger ice thickness at the early icing stage but a smaller one at the later stage. The water film appears earlier, and the water film thickness is larger in the property-variable model. The temperature profiles are a logarithmic curve and a straight line in the property-variable and property-constant models. The property-variable model yields a shorter critical time and a smaller critical ice thickness. A smaller liquid water content, airflow velocity, and collection efficiency or a lower airflow temperature enlarges the difference in the ice accretion characteristics between the property-variable and property-constant models. The property-variable icing model is recommended when the airflow coefficient is smaller than 50. The findings in this work provide guidance for the model selection in icing prediction.

THE INFLUENCE OF SODIUM CARBOXYMETHYL CELLULOSE ON THE SEDIMENTATION BEHAVIOUR OF NICKEL PHOSPHATE PRECIPITATE AT VARYING TEMPERATURES

The sedimentation data of nickel phosphate precipitate formed with or without a modifier - sodium carboxymethyl cellulose (Na-CMC) biopolymer were studied under controlled conditions of temperature. The main objective was to access the influence of Na-CMC and temperature on On-set Sedimentation Rate (OSR) and Sedimentation Volume Ratio (SVR) of nickel phosphate. Na-CMC at different concentrations (200ppm - 2000ppm) was mixed with constant volume of disodium hydrogen phosphate solution in a graduating measuring cylinder. On mixing the resulting solution with constant volume of nickel chloride solution, a precipitate was formed, stirred for 1 min and placed in the sedimentation measurement device - PreSed Meter. The settling of the precipitate was monitored and recorded at different temperatures (30oC, 40oC and 50oC). Blank sedimentation (0ppm Na-CMC) was also run at various temperatures by adding 10ml of deionized water (instead of 10ml of Na-CMC solution). A plot of precipitate displacement per settling time established a logarithmic curve which flattened with time. Regression analyses of OSR (0.71 ≤ R2 ≥ 0.94) and SVR (0.51 ≤ R2 ≥ 0.93) indicated the dependence of sedimentation on concentration of Na-CMC thus implying chemical interaction between the chemical species.&#x0D;

Determination of the conditions of sedimentation of the Jurassic deposits of the Karaton field based on a comparison of electrofacies and sedimentological description of the core

This paper presents the results of lithofacies analysis of log curves and sedimentological description of the core material of wells from the Karaton field to determine the environmental condition and determine the similarity of the behavior of log curves. The field is located in the Karaton-Tengiz zone of uplifts, which are characterized by a rather complicated environmental conditions. Based on typical models of facies groups and a description of the core material of the Jurassic deposits, it was possible to identify zones of development of sandy deposits and determine the main environmental condition. Keywords: lithology; sedimentology; facies; electrofacies; generic model; depositional environment.

Fatigue crack propagation performance of Q690 high-strength steel and butt welds

The fatigue performance of high-strength steels is an important issue in bridge engineering. In this study, fatigue crack propagation rate tests and theoretical studies of high-strength steel Q690 base material and butt welds were conducted. Two types of compact tensile (CT) specimens—one for the Q690 compact tensile specimens and the other for the butt welds—were used for the test under stress ratios of R = 0.1, 0.3, and 0.5, with a loading frequency of 15 Hz. The fatigue crack length was measured using the flexural method with an extensometer, and the load value and the corresponding cycle number in the tests were also obtained. These results were processed using the seven-point polynomial method to obtain the fitting curve of log (da/dN) to log ΔK. Finally, the modified Paris formula of Q690 was presented, and the corrected values of the material parameters C and m were determined. The test results show that the fatigue crack propagation rate of Q690, both for the compact tensile specimens and those with butt welds, increased with the stress ratio R. The fatigue crack propagation rate of Q345qD was 1.8 times higher than that of Q690 high-strength steel. In addition, the fatigue resistance of Q690 was significantly higher than that of other standard steels. The fatigue crack propagation rate of the Q690 specimens with butt welds at a low-stress amplitude was lower than that of the Q690 compact tensile specimen. At a high-stress amplitude, the fatigue crack propagation rate of Q690 is greater than that of the Q690 compact tensile specimen.

Multifractal analysis of the heterogeneity of nanopores in tight reservoirs based on boosting machine learning algorithms

Exploring the geological factors that affect fluid flow has always been a hot topic. For tight reservoirs, the pore structure and characteristics of different lithofacies reveal the storage status of fluids in different reservoir environments. The size, connectivity, and distribution of fillers in different sedimentary environments have always posed a challenge in studying the microscopic heterogeneity. In this paper, six logging curves (gamma-ray, density, acoustic, compensated neutron, shallow resistivity, and deep resistivity) in two marker wells, namely, J1 and J2, of the Permian Lucaogou Formation in the Jimsar Basin are tested by using four reinforcement learning algorithms: LogitBoost, GBM, XGBoost, and KNN. The total percent correct of training well J2 is 96%, 96%, 96%, and 96%, and the total percent correct of validation well J1 is 75%, 68%, 72%, and 75%, respectively. Based on the lithofacies classification obtained by using reinforcement learning algorithm, micropores, mesopores, and macropores are comprehensively described by high-pressure mercury injection and low-pressure nitrogen gas adsorption tests. The multifractal theory servers for the quantitative characterization of the pore distribution heterogeneity regarding different lithofacies samples, and as observed, the higher probability measure area of the generalized fractal spectrum affects the heterogeneity of the local interval of mesopores and macropores of the estuary dam. In the micropore and mesopore, the heterogeneity of the evaporation lake showed a large variation due to the influence of the higher probability measure area, and in the mesopore and macropore, the heterogeneity of the evaporation lake was controlled by the lower probability measure area. According to the correlation analysis, the single-fractal dimension is well related to the multifractal parameters, and the individual fitting degree reaches up to 99%, which can serve for characterizing the pore size distribution uniformity. The combination of boosting machine learning and multifractal can help to better characterize the micro-heterogeneity under different sedimentary environments and different pore size distribution ranges, which is helpful in the exploration and development of oil fields.

Development of a dynamic ice penetration model for runway de-icing products through performance experimental characterization

During winter, the clear runway concept is crucial to airports for maintaining passenger and employee safety. Research can optimize de-icing product application rates, thereby reducing costs and environmental impact. Currently, three aerospace standards exist for evaluating the performance of runway de-icing products. These comparative tests—ice melting, ice undercutting, and ice penetration tests—are carried out jointly in a systematic way and indicate whether a runway de-icing product is effective in actively reducing the presence of ice. Here we present a numerical model for the ice penetration method, for fluid runway de-icing product, with the goal of deepening the knowledge in this field. We apply a series of laboratory-based tests to measure the performance of runway de-icing products, and develop a new model to analyze the behavior of each product. The principal observation is that the product is more effective at 1 min and effectiveness decreases following an inverse logarithmic curve trend to 30 min. Through modeling, we observe that the dominant mode of heat transfer is natural laminar convection, and the model predicts a uniform melt length for the entire tube section. Thus, simplified ice penetration modeling using AS6211 can acceptably predict the rate of ice penetration as a function of time (mm/min), with the modeling confirmed by our experimental results. The future application of our simplified model to other existing de-icing fluid characterization test methods could identify the effects of diluted or undiluted solid runway de-icing products on ice penetration rates and ultimately on spreading rates.

Aging Effects on Installed Submarine Optical Cables

Aging effects in submarine optical cables were evaluated with OTDR measurements along 24 years’ time span. Logarithmic trend curves indicate a Lifetime of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula> 75 years before penalty reaches the threshold value of 0.005 dB/km. Penalties from splice losses were found to be twofold higher than those from fiber attenuation. Aging effects in warehouse stored spare cables were tenfold higher than in deployed cables.

Eocene Statistics of the Semi-Deep-Deep Lake-Level Evolution of the Jijuntun Formation in the Fushun Basin, Northeast China.

The fluctuation of lake levels in semi-deep and deep lake environments has long been a central topic in the study of ancient lake evolution. This phenomenon has a significant impact on the enrichment of organic matter and the overall ecosystem. The study of lake-level changes in deep lake environments is hindered by the scarcity of records in continental strata. To address this issue, we conducted a study on the Eocene Jijuntun Formation in Fushun Basin, specifically focusing on the LFD-1 well. Our study involved finely sampling the extremely thick oil shale (about 80 m), which was deposited in the semi-deep to deep lake environment of the Jijuntun Formation. The TOC was predicted by multiple methods, and the lake level study was restored by combining logging INPEFA and Dynamic noise after orbital tuning (DYNOT) techniques. The oil shale of the target layer is type I kerogen, and the source of organic matter is basically the same. The γ ray (GR), resistivity (RT), acoustic (AC), and density (DEN) logging curves are in the normal distribution, indicating that the logging data are better. The accuracy of TOC simulated by improved Δlog R, SVR, and XGBoost models is affected by the number of sample sets. The improved Δlog R model is most affected by the change of sample size, followed by the SVR model, and the XGBoost model is the most stable. In addition, compared with the prediction accuracy of TOC by improved Δlog R, SVR, and XGBoost models, it is shown that the improved Δlog R method has limitations in the prediction of TOC in oil shale. The SVR model is more suitable for the prediction of oil shale resources with small sample size, and the XGBoost model is applicable when the sample size is relatively large. According to the DYNOT analysis of logging INPEFA and TOC, the lake level changes frequently during the deposition of ultra-thick oil shale, and the lake level has experienced five stages of rising-stabilizing-frequent fluctuation-stabilizing- decreasing. The research results provide a theoretical basis for revealing the plane change of stable deep lake lakes and provide a basis for the study of lake levels in faulted lake basins in Paleogene Northeast Asia.

Characteristics, logging identification and major controlling factors of bedding-parallel fractures in tight sandstones

More and more tight oil and gas exploration practices show that bedding-parallel fractures (BPFs) are closely related to hydrocarbon migration and accumulation. However, there is still a lack of studies on the detailed characterization, the logging identification method and the major controlling factors of BPFs. The tight sandstones in the northern Sanbian of Ordos Basin have developed numerous BPFs which are typical research objects. In this study, the development characteristics and oil-bearing of BPFs were firstly analyzed based on cores, thin sections and image logs. Then, constrained by the BPFs appearing in cores and image logs, the identification method of BPFs was established by conventional log curves. Finally, the major controlling factors for the formation of BPFs were discussed. Resultsshow that the oil-bearing of BPFs is markedly better than high-angle fractures (HAFs), which indicates that BPFs have a great significance to tight oil migration and accumulation in the northern Sanbian. The bedding-parallel fractures index (BPFI), which consists of the composite fracture index (CFI), fracture dip index (FDI) and principal component analysis (PCA), can identify the BPFs of tight sandstones, and the identification rate can reach 85% with the detection result of image logs. Fine sandstones with parallel bedding and cross bedding which easily enriched mica, underwater distributary channel sedimentary microfacies with comparatively strong hydrodynamic conditions, and a certain mudstone thickness that can produce differential compaction overpressure are the major factors affecting the development of BPFs.

Wide field electromagnetic method calculation in arbitrary orientation and its effectiveness analysis

The wide field electromagnetic method E_Ex observation method requires the horizontal electrical field source (AB) to be parallel to the measure station (MN), but the complex terrain conditions make it difficult to meet the AB parallel MN in field construction, and there is always an azimuthal difference α between them, which will bring a large calculation error and cause distortion of the interpretation parameters if the calculation method E_Ex continues to be used. In order to tackle this problem, we analyse and study the E_Ex method and derive the new calculation method of E_EMN for the wide field electromagnetic method along the MN (E_EMN). The method is based on the intrinsic relationship between the electric field components Ex, Ey and the azimuthal difference α and derives the expression for the electric field E_EMN along the MN direction, and then uses the E_EMN to calculate the wide field apparent resistivity. In this paper, we design a three-layer geoelectric model and calculate the azimuthal angle difference α = 0° and α = 15°wide field apparent resistivity parameters, respectively. The results show that the relative error between the calculated apparent resistivity and the theoretical value is less than 1%, which verifies the correctness and validity of the method. To further verify the accuracy of the method, experimental work on azimuthal difference α was carried out next to a known well in Sichuan. The results show that: firstly, when α is 1°, 3°, 5°, 10°, and 15°, respectively, the relative error of each frequency point increases with α increasing. Secondly, when α is 1°, 3°, 5°, 10°, and 15°, respectively, the relative error of each frequency point is less than 10% when the EMN method is used to calculate the wide field apparent resistivity value; thirdly, taking α = 15° as an example, single-station inversions are performed with Ex and EMN apparent resistivity parameters, in which the Ex inversion results are more different from the trend of the logging curve, while the EMN inversion results are relatively more consistent with the trend of the logging curve. The arbitrary orientation EMN calculation method proposed in this paper can effectively reduce the influence of α on the interpretation parameters and improve the accuracy of interpretation, and also greatly expand the applicability and flexibility of Ex wide field electromagnetic method in the observation of complex terrain areas, which has important theoretical research and practical production significance.

Multiparameter Logging Evaluation of Chang 73 Shale Oil in the Jiyuan Area, Ordos Basin

The accurate evaluation of shale oil and gas reservoirs is of great significance to the integrated development of geology and engineering. Based on the core analysis, conventional logging, and array acoustic logging data, the total organic carbon, hydrocarbon generation potential, brittleness, and anisotropy of shale reservoirs were calculated. The p-wave time difference curves calculated by the artificial neural network (ANN) method and the conventional logging curve fitting method were compared. The multiresolution graph-based clustering (MRGC) method was used to classify shale reservoirs into three categories and evaluate the classification results. Brittle minerals such as quartz and feldspar were mainly found to be present in shale reservoirs and clay minerals which mainly consisted of illite. The Chang 73 reservoir is rich in organic matter and has great potential for survival. The p-wave time difference calculated by the fitting formula of the shear wave time difference meter demonstrated high accuracy and did not require a complex ANN model. MRGC method can well classify shale reservoir types. The classification results reduce the interference of human factors and are more scientific and reasonable. This research method is of great significance for the scientific classification and evaluation of shale reservoirs.