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Conventional galaxy mass estimation methods suffer from model assumptions and degeneracies. Machine learning (ML), which reduces the reliance on such assumptions, can be used to determine how well present-day observations can yield predictions for the distributions of stellar and dark matter. In this work, we use a general sample of galaxies from the TNG100 simulation to investigate the ability of multibranch convolutional neural network (CNN) based ML methods to predict the central (i.e. within 1−2 effective radii) stellar and total masses, and the stellar mass-to-light ratio (M */ L). These models take galaxy images and spatially resolved mean velocity and velocity dispersion maps as inputs. Such CNN-based models can, in general, break the degeneracy between baryonic and dark matter in the sense that the model can make reliable predictions on the individual contributions of each component. For example, with r -band images and two galaxy kinematic maps as inputs, our model predicting M */ L has a prediction uncertainty of 0.04 dex. Moreover, to investigate which (global) features significantly contribute to the correct predictions of the properties above, we utilize a gradient-boosting machine. We find that galaxy luminosity dominates the prediction of all masses in the central regions, with stellar velocity dispersion coming next. We also investigate the main contributing features when predicting stellar and dark matter mass fractions (f *, f DM) and the dark matter mass M DM, and discuss the underlying astrophysics. [ABSTRACT FROM AUTHOR]

We present a novel natural language processing (NLP) approach to deriving plain English descriptors for science cases otherwise restricted by obfuscating technical terminology. We address the limitations of common radio galaxy morphology classifications by applying this approach. We experimentally derive a set of semantic tags for the Radio Galaxy Zoo EMU (Evolutionary Map of the Universe) project and the wider astronomical community. We collect 8486 plain English annotations of radio galaxy morphology, from which we derive a taxonomy of tags. The tags are plain English. The result is an extensible framework, which is more flexible, more easily communicated, and more sensitive to rare feature combinations, which are indescribable using the current framework of radio astronomy classifications. [ABSTRACT FROM AUTHOR]

Classification and evaluation of reservoirs conforming to geological characteristics are the proposed premises of the high‐quality development of unconsolidated sandstone heavy oil reservoirs. The P oilfield in Bohai Bay is one of the largest offshore oilfields in China, but the reservoirs are highly heterogeneous, have complex pore structures, and change fluid properties, which make the classification of reservoirs very difficult. At present, the most commonly used reservoir classification methods are based on the results of logging interpretation, which cannot eliminate the constraints of linear relationships such as empirical formulas. Machine learning has significant advantages for identifying reservoir classification problems that are complex and nonlinear with geological characteristics. First, this study fully considered the pore structure and fluid properties and selected four representative evaluation parameters. An improved K‐means method was used to establish a reservoir classification evaluation system. Characteristics, such as the sedimentary microfacies, pore structure and oilfield production performance, of different types of reservoirs were then analysed. Finally, six logging curves were selected as input results, reservoir classification was used as an output result, and XGBoost was used to carry out reservoir classification evaluation for the entire area. The accuracy of XGBoost was 85.35%. Furthermore, XGBoost was compared with three other machine learning methods to confirm its reliability. The results showed that the reservoirs in the study area can be divided into three types. Sandstone thickness and pore structure were the most important parameters that affected reservoir quality. Among various machine learning algorithms, XGBoost can accurately and quickly achieve a quantitative evaluation of reservoir quality. [ABSTRACT FROM AUTHOR]

Owing to a lengthy oil‐bearing interval, strong anisotropism, and significant difference in the fluid properties of the sandstone oil reservoir in P Oilfield, it is quite challenging to accurately the productivity of the oil well at the initial stage. In this study, a deep neural network model is established, based on a gradient boosting algorithm, XGBoost, to forecast the initial productivity of oil wells, followed by an evaluation of the main controlling factors of productivity. One hundred oil wells in the study area were divided into training and verification groups. With a specific productivity index of an oil well with a stable period of approximately 6 months at the initial production stage as the target data, and geological, engineering, and oil reservoir parameters as input data, hyper‐parameters for adjustment and optimization were selected, and a deep‐learning‐based unconsolidated sandstone productivity forecast model was established to forecast the initial productivity of oil wells in the target area. The mean square root error of the forecast result was <0.15, which is highly consistent with actual productivity. Finally, by adopting the XGBoost algorithm, the weight ranking of the controlling factors of productivity was clarified as follows: microscopic pore structure parameter > crude oil viscosity > median grain size > lithology index > well completion method > flow zone indicator. Machine learning has the advantages of effective forecasting of oil well productivity and the main controlling factors using multiple dimensions and big data. [ABSTRACT FROM AUTHOR]

The Permian strata in the southwest Tarim Basin contain organic reefs with good exploration prospects. Based on observations of outcrops and thin section examination of the Permian Keziliqiman Formation reef in the Sangzhu section of Pishan County, Xinjiang, northwest China, the basic characteristics of the reef are studied. This organic reef, as a point reef which grew along the platform margin, has a complete subfacies system of base, core, front, back, and cap. The lithology of the lower zone of the core is mainly sponge bafflestone, while that of the upper zone is coral framestone. The development of reefs was controlled by the rise and fall of sea level. It was when the sea level rose in southwest Tarim Basin that the Keziliqiman reef gradually came into existence. Later, with rapid decline of sea level in that area, the Sangzhu section turned into a hot and dry supratidal zone, where algae began to flourish, dolomitization intensified, reef building organisms died en masse, and eventually the reef died. Paleontological and geochemical characteristics of the Sangzhu reef indicate that the sea-level decline in southwest Tarim Basin may be related to the Early Permian glaciers. Since then, the reef began to be transformed by diagenesis. But on the whole, its effect was not significant. Furthermore, its diagenetic process had more to do with marine fluids than with nonmarine fluids, for nonmarine fluids was powerful enough to affect bioclasts but powerless to affect micritic matrix. [ABSTRACT FROM AUTHOR]

[Display omitted] • An H4R target pathway model for high-throughput screening tests was developed. • Cryptotanshinone was a new H4R non-competitive antagonist. • Cryptotanshinone interacts with H4R at a novel allosteric binding site. Histamine 4 receptor (H4R), the most recently identified subtype of histamine receptor, primarily induces inflammatory reactions upon activation. Several H4R antagonists have been developed for the treatment of inflammatory bowel disease (IBD) and atopic dermatitis (AD), but their use has been limited by adverse side effects, such as a short half-life and toxicity. Natural products, as an important source of anti-inflammatory agents, offer minimal side effects and reduced toxicity. This work aimed to identify novel H4R antagonists from natural products. An H4R target-pathway model deconvoluted downstream G i and MAPK signaling pathways was established utilizing cellular label-free integrative pharmacology (CLIP), on which 148 natural products were screened. Cryptotanshinone was identified as selective H4R antagonist, with an IC 50 value of 11.68 ± 1.30 μM, which was verified with Fluorescence Imaging Plate Reader (FLIPR) and Cellular Thermal Shift (CTS) assays. The kinetic binding profile revealed the noncompetitive antagonistic property of cryptotanshinone. Two allosteric binding sites of H4R were predicted using SiteMap, Fpocket and CavityPlus. Subsequent molecular docking and dynamics simulation indicated that cryptotanshinone interacts with H4R at a pocket formed by the outward interfaces between TM3/4/5, potentially representing a new allosteric binding site for H4R. Overall, this study introduced cryptotanshinone as a novel H4R antagonist, offering promise as a new hit for drug design of H4R antagonist. Additionally, this study provided a novel screening model for the discovery of H4R antagonists. [ABSTRACT FROM AUTHOR]

The lower Wuerhe formation reservoir of the 8th district is a blocky, ultra-low-permeability gravel reservoir with poor waterflooding development, and it is urgent to attack the gas injection gravity flooding. The barrier property of seepage barriers such as interlayers developed inside the reservoir is very important for the study of gas injection gravity flooding. The mineral composition, pore throat structure, and physical characteristics of the interlayer rocks were studied by X-ray diffraction (XRD) whole-rock analysis and nuclear magnetic resonance (NMR). The gas injection breakthrough pressure of the interlayer was studied by core breakthrough experiment and digital core simulation. Based on the determination of the interlayer criteria, logging was used to interpret and characterize the interlayer. The effects of different types of interlayer combinations on gas injection were studied by combining the physical model and numerical simulation methods. The results showed that the lithology of the interlayer in the lower Wuerhe formation of the 8th district was mainly mud-bearing fine gravel with microporosity, average porosity of 6.1% and permeability of 0.0043 mD. The interlayer gas injection breakthrough pressure and permeability were in a logarithmic linear relationship, and the lower limit of gas injection breakthrough under reservoir conditions was 0.003 mD. Initially, it is difficult to flood the upper remaining oil of the gas injection due to the blockage of the interlayer, while in the middle and late stage, the gas-liquid interface gradually reached stability with the increase in injected gas, which has little impact on the final recovery. These results indicate that it is feasible to carry out gas injection gravity flooding in this reservoir. [ABSTRACT FROM AUTHOR]

The Neogene Guantao Formation Reservoir in the PLOilfield is a unconsolidated sandstone with high porosity and high permeability. The reservoir diagenesis is weak and dominated by compaction diagenesis. At present, insufficient research into the relationship between the pore characteristics and sedimentary microfacies of shallow delta sandstone reservoirs restricts the prediction of favorable reservoir distribution. This article takes the unconsolidated sandstone reservoir of the Guantao Formation as the research object and analyzes the potential coupling relationship between pore characteristics and sedimentary microfacies. In this study, seven typical sedimentary microfacies were identified and the microscopic characteristics of different sedimentary microfacies reservoirs are described. The results show that the pore structure of various sedimentary microfacies is comprehensively influenced by the sedimentary rock texture, siliceous minerals, and clay mineral distribution. Characterized by more abundant hard quartz and feldspar minerals, positive skewness, and lower pore sorting coefficients, the arenaceous microfacies possess larger pore throat radius and lower pore fractal dimensions than argillaceous microfacies. Finally, due to the difficulty of coring in offshore oilfields and the lack of data on mercury injection experiments, empirical formulas for the porosity, permeability, and pore throat radius of conventional core tests were established, and the pore radius that corresponded to 35% mercury saturation (r35) was used as the characteristic pore structure parameter. The grey correlation method was used to analyze the influence of sedimentary structure factors and mineral content differences on r35 and to determine the main controlling factors. [ABSTRACT FROM AUTHOR]

The Lower Silurian Longmaxi Formation in the southern Sichuan Basin is composed of a series of dark carbonaceous shales deposited in a hydrostatic shelf reduction environment. In this study, the ratio of uranium to thorium (U/Th), the total organic carbon (TOC), and the biological silicon content (SiBio) were selected as the characteristic parameters to precisely analyze the sedimentary environment and its impact on reservoir quality. The results show that the Weiyuan area in the Early Silurian Longmaxi period experienced two transgression-regression cycles, forming two third-class sequences, SSQ1 and SSQ2, which can be divided into six sedimentary microfacies: organic-rich siliceous argillaceous shelf, organic-rich silicon-containing argillaceous shelf, organic-rich silty argillaceous shelf, deep-water silty argillaceous shelf, shallow-water silty argillaceous shelf, and shallow-water argillaceous silty shelf microfacies. The organic-rich siliceous argillaceous shelf and organic-rich silicon-containing argillaceous shelf microfacies developed in the deepest transgressive system tract (TST1), with high U/Th, high TOC, and high SiBio, which are identified as the main control facies for reservoir development. These two microfacies are located in the middle of the study area, while a transition occurs in the east affected by the Neijiang Uplift. According to the classification criteria proposed in this article, the favourable shale gas reservoirs in Weiyuan area are characterized with high U/Th (>1.25), high TOC (>3%), and high SiBio (>15%). This paper proposed an evaluation method for shale sedimentary facies based on elemental and electrical logging characteristics, avoiding the limitations of core samples, which makes the quantitative division of shale sediments and the efficient recognition of high-quality reservoirs available. It is of great significance for delineating the potential production areas in the study area and beneficial for the scaled development of shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Due to the diversity of pore types, it is challenging to characterize the Middle East's Cretaceous carbonate reservoir or accurately predict its petrophysical properties. In this paper, pore structure in the reservoir is first classified using a comprehensive method. Then, based on the identified pore structure types, a new permeability model with high prediction precision is established. The reservoir is dominated by 6 pore types, such as intergrain pores and moldic pores, and 6 rock types. Grainstone, algal packstone, algal wackestone, and foraminifera wackestone are porous rock types, and echinoderm wackestone and mudstone are nonporous rock types. The types of pore structure in the study area can be divided into four types. Type I has midhigh porosity and medium-high permeability due to its large throat, while type II has a fine throat type with midhigh porosity and midpermeability. Due to their isolated pores, the permeability is low in types III and IV, and out of these two, type III has better storage capacity. Movable fluid saturation calculated by the spectral coefficient method and r apex can characterize the boundary between the connected pores and unconnected pores very well in the research area. It is not accurate enough to simply classify the pore structure by permeability and porosity. The combination of porosity, permeability, r apex , flow zone indicator, and the reservoir quality index can effectively distinguish and classify pore structure types in noncoring wells. The characteristics of each pore structure type are consistent with those of the fractal dimension, which thereby proves the effectiveness of the pore structure classification. New permeability prediction models are proposed for different pore structure types, and good prediction results have been obtained. This study is of great significance for enhancing oil recovery. [ABSTRACT FROM AUTHOR]

The transportation and capture of particulate suspension in a rough fracture are widely encountered in hydrocarbon exploitation. According to a full review of the literature, traditional studies mainly focus on the placement and settlement of coarse particles such as proppants and lost circulation materials. Furthermore, a fracture is often considered to be equivalent to smooth parallel plates, whereas actual fractures are roughly walled with microconvex and are affected by normal stresses. The particulate suspension transport mechanism in a fracture under different normal stresses is still unclear. This paper proposes an approach to evaluate the permeability impairment caused by size‐exclusion of solid particles in a fracture under different normal stresses. The morphology of fracture flow space under different normal stresses is obtained by using optical scanning and FEM. Furthermore, the unresolved CFD‐DEM method is used to study the mechanism of the capture and migration of the particulate suspension in a fracture. The simulation results are in agreement with the experimental results. Furthermore, the effects of the particle size, particle concentration, injected particle volume, fracture occurrence, and applied pressure on particle invasion are discussed. [ABSTRACT FROM AUTHOR]

The tight sandstone reservoirs of the Permian Shihezi and Shanxi Formation with strong heterogeneity constitute the main producing zone of the eastern Sulige gas field. The process of differential densification results in various reservoir qualities. Mineral composition, structural characteristic, pore system, and diagenesis were investigated with analyses of well logs, thin sections, porosity, and horizontal permeability of the core plugs; environmental scanning electron microscopy (ESEM); nuclear magnetic resonance (NMR); X-ray computed tomography (X-CT); and fluid inclusion homogenization temperature. The results show that lithic sandstone reservoirs experienced complex and various diagenetic evolutions. Eight types of densification modes can be divided according to the diagenesis paths; these modes represent lithofacies with different densification times and reservoir qualities. Intense mechanical compaction is the main reason for the formation of lithofacies 1, 2, and 5. Lithofacies 4, 6, and 7 formed due to intense cementation, increasing the impermeability of the diagenetic system. The primary pore space in lithofacies 3 is preserved due to the overpressure and chlorite coatings. The dissolution and weak cementation of lithofacies 8 contribute to reservoir development. The middle-lower part of braided channel lags and channel bars, the middle part of meandering riverbed lags, and the middle part of point bars are favourable for reservoir development. [ABSTRACT FROM AUTHOR]

SUMMARY: Due to the strong heterogeneity of the reservoir, it is difficult to extend the classical reservoir parameter prediction model to the new work area. Traditional geological methods rely on experience, while machine learning algorithms lack consideration of reservoir heterogeneity. This makes it impossible for these methods to achieve good predictive performance in new work areas. In this paper, we discuss designing a multilayer deep transfer learning network (MDTL). The network enables accurate prediction of reservoir parameters in new areas based on core and logging data from mature areas. For the architectural design, we establish a network structure that realizes data interaction in different work areas. For network parameter optimization, we design a multilayer maximum mean discrepancy loss function. It guides network training to learn feature knowledge about data in different work areas. For logging data processing, we explore a support vector machine method to remove abnormal noise in logging data. We apply MDTL to predict shale gas porosity and total organic carbon content in southern Sichuan. Compared to state-of-the-art reservoir parameter prediction models, MDTL achieves the best performance in new well areas. The network integrates the idea of multilayer transfer learning, reduces the influence of reservoir heterogeneity and effectively ensures the prediction accuracy. [ABSTRACT FROM AUTHOR]

The main source of production in the middle and late stages of shale gas extraction is the adsorbed gas in shale, and the adsorbed gas in shale mainly comes from organic matter casein and clay minerals in shale; therefore, this paper uses sodium-based montmorillonite to characterize the clay minerals in shale and study the CH4 adsorption law in clay minerals, and this study has certain guiding significance for shale gas extraction. In addition, this paper also conducts a study on the competitive adsorption law of CH4 and CO2, and at the same time, predicts the theoretical sequestration of CO2 in shale clay minerals, which is a reference value for the study of CO2 burial in shale and is beneficial to the early realization of carbon neutral. In this paper, the slit model of sodium-based montmorillonite and the fluid model of CH4 and CO2 were constructed using Materials Studio software, and the following two aspects were studied based on the Monte Carlo method: Firstly, the microscopic adsorption behavior of CH4 in sodium-based montmorillonite was studied, and the simulations showed that the adsorption capacity of montmorillonite decreases with increasing temperature, increases and then decreases with increasing pressure, and decreases with increasing pore size. CH4 has two states of adsorption and free state in the slit. The adsorption type of CH4 in montmorillonite is physical adsorption. Secondly, the competitive adsorption of CH4 and CO2 in sodium-based montmorillonite was studied, and the simulations showed that the CO2 repulsion efficiency increased with increasing CO2 injection pressure, and the CO2/CH4 competitive adsorption ratio decreased with increasing pressure. The amount of CO2 storage decreased with increasing temperature and increased with increasing CO2 injection pressure. [ABSTRACT FROM AUTHOR]

Low-permeability near-critical volatile reservoirs are characterized by light oil, complex fluid phase, and strong reservoir inhomogeneity, etc. Purely injecting CO2 will create a series of problems, such as serious gas channeling, low sweep efficiency, and low oil recovery. Therefore, in this paper, through a combination of experiments and simulations and in the process of studying the problem from simple to complex, we carried out phase equilibrium experiments for CO2-near-critical volatile oil and CO2-near-critical volatile oil-formation water, as well as experiments for minimum miscible pressure of slim-tube with pure CO2 and CO2–water co-injection to the comparative study of the miscible characteristics and displacement oil efficiency between pure CO2 injection and CO2–water co-injection. It provides an important reference for improving oil recovery by CO2–water co-injection in low-permeability near-critical volatile reservoir. The results of CO2-near-critical volatile oil/CO2-near-critical volatile oil-formation water phase equilibrium experiments show that the saturation pressure, density, and gas–oil ratio of the system increase, and the viscosity decreases with the increase in CO2 injection. In the three-phase system of CO2-near-critical volatile oil-formation water, the CO2 content in the flash gas of crude oil, gas–oil ratio, and gas–water ratio are negatively correlated with the water saturation. The results of slim-tube experiments and simulations on the miscible characteristics and displacement oil efficiency of pure CO2 injection and CO2–water co-injection show that the recovery degree of crude oil under CO2–water co-injection is higher than that of pure CO2 injection, and the CO2 dissolved transition section in oil and gas is shorter and the gas breakthrough time is later under CO2–water co-injection, which effectively increases the sweep efficiency and improves the degree recovery of crude oil. When CO2–water co-injection, the ratio of water is higher, the later the gas–oil ratio rises, the later the CO2 breakthrough, and the higher the degree of crude oil recovery. It indicates that when CO2–water co-injection, the ratio of water is higher, the more CO2 is dissolved in water, which effectively inhibits the occurrence of gas channeling and increases the sweep area, thus improving the degree recovery of crude oil. The research results of this paper provide an experimental basis and theoretical foundation for CO2–water co-injection for enhanced crude oil recovery in low-permeability near-critical volatile reservoirs. [ABSTRACT FROM AUTHOR]

Particle migration in oil and gas reservoirs is a common phenomenon in the process of oil and gas development, and is considered to be an important reason for the damage of reservoir permeability and the reduction of oil and gas productivity. The mechanism of this phenomenon includes the desorption, migration, and precipitation of particles, which eventually clogs the throat and causes reservoir damage. Therefore, it is necessary to accurately characterize the complex mechanism of particle migration and identify the main controlling factors of particle migration, which is very important for efficient oilfield development and plugging solution. First, the reservoir types are divided into three types and the pore structure models of different types of reservoirs are established. Then, computational fluid dynamics and discrete element coupling method numerical simulation and microscopic visualization of pore throat structure model were combined, to characterize the rules of particles and migration, and analyze the main controlling factors. Finally, a typical model of particle migration and clogging is established. The results show that particle size/throat and particle concentration are the key factors affecting particle plugging, and particle migration has the least effect on the permeability of Type I reservoir and the greatest damage to Type III reservoir. According to the mechanical and hydrodynamic behavior of particles in porous media, three mechanisms and six modes of particle plugging are proposed. [ABSTRACT FROM AUTHOR]

Lu, H.; Tang, H.M.; Wang, M., and Wang, Y.J., 2020. Characterization of a carbonate reservoir formed in a low energy environment. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 775–784. Coconut Creek (Florida), ISSN 0749-0208. The Cretaceous oil and gas reservoir located in the Middle East is one of the most important reservoirs in the world. However, it is highly inhomogeneous and porous and displays low permeability. These characteristics affect is potential as high quality reservoir. The present research integrated conventional petrophysical tests, high-pressure mercury intrusion analysis, scanning electron microscopy (SEM) and petrological analysis to determine the rock characteristics of the Kh2 upper cretaceous oil field. With this information we classified the reservoir in different types. The results showed that the reservoir was formed in a low energy environment, is an open platform running from above the wave base level to below the low tide line. The lithology was dominated by foraminiferal biomicritie, echinate biomicritie, micritie, pelsparite, algae biopelmicrite, algal biomicritie, and algal fossiliferous micrite. Based on the regional structure and palaeogeodetic sedimentary background, the presence of open sea (MF1), high-energy pellets shoal (MF2), intershoal sea (MF3), low-energy pellets shoal (MF4), and low-energy bioclastic shoal (MF5) were identified. The porosity ranged from 10% to 29%, with an average of 23.73%. The permeability varied between 0.4 mD and 490 mD, with an average value of 21.21 mD. In addition, the petrophysical properties were controlled by sedimentary microfacies and diagenesis, and the quality of these properties decreased in the order MF2, MF4, MF5, MF3, MF1. Diagenesis transformed the reservoir; however, the basis for diagenesis was the sedimentary environment. The reservoir was divided into 3 types, which corresponded to 3 types of pore structures. The first type (pore throat structure I) mainly developed in MF2 and MF4, where the average throat radius was larger than 2.2 µm, and the permeability higher than 20 mD. The second type (pore throat structure II) was identified in MF4 and MF5, presenting an average throat radius between 0.5 µm and 2.2 µm, and a permeability between 5 mD and 20 mD. The third type (pore throat structure III) occurred in MF1 and MF3, presented average throat radius smaller than 0.5 µm, and permeability smaller than 5 mD. The Kh2 layer was a type II reservoir. The results presented herein will be of great significance for the identification of potential oil research and development areas. [ABSTRACT FROM AUTHOR]

The abundant reserve of shale gas in Sichuan Basin has become a significant natural gas component in China. To achieve efficient development of shale gas, it is necessary to analyze the stress state, pore pressure, and reservoir mechanical properties such that an accurate geomechanical model can be established. In this paper, Six wells of Neijiang-Dazu and North Rongchang (NDNR) Block were thoroughly investigated to establish the geomechanical model for the study area. The well log analysis was performed to derive the in-situ stresses and pore pressure while the stress polygon was applied to constrain the value of the maximum horizontal principal stress. Image and caliper data, mini-frac test and laboratory rock mechanics test results were used to calibrate the geomechanical model. The model was further validated by comparing the model prediction against the actual wellbore failure observed in the field. It was found that it is associated with the strike-slip (SS) stress regime; the orientation of SHmax was inferred to be 106–130° N. The pore pressure appears to be approximately hydrostatic from the surface to 1000 m true vertical depth (TVD), but then becomes over-pressured from the Xujiahe formation. The geomechanical model can provide guidance for the subsequent drilling and completion in this area and be used to effectively avoid complex drilling events such as collapse, kick, and lost circulation (mud losses) along the entire well. Also, the in-situ stress and pore pressure database can be used to analyze wellbore stability issues as well as help design hydraulic fracturing operations. [ABSTRACT FROM AUTHOR]

In recent years, the shale gas in the southern Sichuan Basin has achieved great commercial development, and the Silurian Longmaxi Formation is the main development stratum. In order to solve the problems of great difference production and inaccurate gas content of the Longmaxi Formation shale gas field in the southern Sichuan Basin, based on thin section identification, argon ion polishing-field emission scanning electron microscopy, high pressure mercury injection, low temperature nitrogen adsorption and the fractal method, the micropore structural heterogeneity of the siliceous shale reservoir of the Longmaxi Formation has been studied. The results show the following: The pores of siliceous shale are mainly intergranular pores and organic pores. Image analysis shows that there are obvious differences in size and distribution of shale pores among different types. The micropore structural heterogeneity is as follows: intragranular pore > intergranular pore > organic pore. In the paper, the combination of low temperature nitrogen adsorption method and high-pressure mercury injection method is proposed to characterize the micropore size distribution and fractal dimension, which ensures the credibility of pore heterogeneity. The shale pores are mainly composed of mesopores (2–20 nm), followed by macropores (100–300 nm). For different pore sizes, the fractal dimension from large to small is mesopore, micropore and macropore. Shale pore structure and fractal dimension are correlated with mineral composition and total organic carbon (TOC) content, but the correlation is significantly different in different areas, being mainly controlled by the sedimentary environment and diagenesis. [ABSTRACT FROM AUTHOR]

We present a model for generating postage stamp images of synthetic Fanaroff–Riley Class I and Class II radio galaxies suitable for use in simulations of future radio surveys such as those being developed for the Square Kilometre Array. This model uses a fully connected neural network to implement structured variational inference through a variational autoencoder and decoder architecture. In order to optimize the dimensionality of the latent space for the autoencoder, we introduce the radio morphology inception score (RAMIS), a quantitative method for assessing the quality of generated images, and discuss in detail how data pre-processing choices can affect the value of this measure. We examine the 2D latent space of the VAEs and discuss how this can be used to control the generation of synthetic populations, whilst also cautioning how it may lead to biases when used for data augmentation. [ABSTRACT FROM AUTHOR]

Carbonate burial dissolution is generally associated with faults and fractures, accompanied by formation of the fracture–vug system that can provide important reservoir space for oil and gas accumulation. Taking the Lower Triassic Daye Formation in the Huandiqiao Section, Huangshi Area, Middle Yangtze Paraplatform, China, as an example, this study elaborates genetic mechanisms of faults and fractures, features of burial dissolution and cementation, and properties of karst water, accompanied by establishment of a genetic model that illustrates the whole process of burial dissolution and cementation. There are a total of nine reverse faults with dominant northwest dips in the study section. Fractures are selectively developed in hanging walls of the nine faults, with tensile features and dominant north–northeast and north–northwest strikes. Dendritic dissolution and subsequent cementation is prevalent in the hanging wall, while they are rare in the footwall. Most of the cements in the fractures of the hanging walls are calcites, with a fluid inclusion homogenization temperature range of 70∼120 °C, overgrowth bands at the pore edge with different luminous intensities, low contents of Na, Ba, K, and Sr, and high contents of Fe, Mn, and Mg. All these characteristics indicate the karst fluid to originate from calcium-rich formation water with hydrothermal genesis. The formation of the dendritic vug and fracture system is ascribed to the upward migration of hydrothermal fluids along the fault planes and fractures that result in selective dissolution. As the water circulation weakens, CaCO3 is gradually supersaturated in the distal zone with reference to the fault as well as the stagnant and weak-circulation zone, eventually forming a complex vug and fracture system. [ABSTRACT FROM AUTHOR]

Understanding the pore size distribution (PSD) of tight sandstone and the effect of clay minerals on the PSD is important for reservoir evaluation. Due to the complex shape of clay minerals, the multiscale pore size of tight sandstone, and the limitation of different experimental methods, it is hard to characterize the full PSD of tight sandstone, especially the point of connection (POC) of different derived PSD curves. In this paper, a more comprehensive technique integrated different precision methods of N2/CO2 low-pressure adsorption isotherms (N2/CO2-LPAI), mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR), and synchrotron X-ray computed tomography (XCT) to investigate the full PSD for three typical tight sandstones in China. Two different forms of PSD data presentations, differential pore volume versus diameter (d V / d R) and the log differential pore volume versus diameter (d V / dlog R), were firstly used to determine the POC. The full integrated PSD curves and scanning electron microscopy (SEM) images were carried out on the different clay-rich tight sandstones. The results show that the pores are classified into three types: intercrystalline pores (less than 0.01 μm), clay-related pores and residual intergranular pores (0.01 μm to 10 μm), and microfractures and dissolution pores (greater than 10 μm). The percentage of intercrystalline pores has a small relation on the porosity and connectivity, while there is a strong correlation among microfractures, dissolution pores, porosity, and especially connectivity. The microfractures and dissolution pores are the main connection channels, so a little change of the main connection channels will have a great effect on the permeability of the tight sandstones. [ABSTRACT FROM AUTHOR]

Pore structure impacts the capability of seepage pattern of subsurface fluid mineral and mineral exploitation efficiency. Because of the strong heterogeneity in carbonate reservoirs, the pore structure is nonlinearly varying and complex in reservoirs. It is necessary to establish a method for pore structure type (PST) prediction. Machine learning provides an efficient prediction method by finding the relationship between core test data and well‐logging data. In this paper, a reservoir identification method based on Gradient Boost Decision Trees (GBDT) is proposed for the pore structure characteristics of carbonate reservoirs integrating core test and logging data. Core testing data are utilized to form the training set for PST prediction. Then, we adopt the mutual information method to optimize the logging data as the input of the machine learning model. GBDT hyperparameters are optimized using the learning curve to make it have optimal performance. Finally, we compare the predicted result of GBDT with K‐Nearest Neighbor and support vector machines, demonstrating the superior performance of GBDT. The results indicate that the four PS are different in some properties, such as permeability, pore radius and shape of pore and throat. 20%, 10 and 0.15 are recommended as the optimal parameter values for Maximum feature, iteration number and Sub‐sample number to improve GBDT accuracy in carbonate reservoir PST prediction. Evaluation indicators of machine learning, including the Kappa coefficient, Heming distance, Jaccard similarity coefficient and Confusion matrices, indicate that GBDT has better performance. This research proves the high accuracy and applicability of machine learning technology in the carbonate reservoir and also provides a meaningful reference for the identification of the carbonate reservoirs in the central area of Iraq. [ABSTRACT FROM AUTHOR]

The Evolutionary Map of the Universe (EMU) large-area radio continuum survey will detect tens of millions of radio galaxies, giving an opportunity for the detection of previously unknown classes of objects. To maximize the scientific value and make new discoveries, the analysis of these data will need to go beyond simple visual inspection. We propose the coarse-grained complexity, a simple scalar quantity relating to the minimum description length of an image that can be used to identify unusual structures. The complexity can be computed without reference to the broader sample or existing catalogue data, making the computation efficient on new surveys at very large scales (such as the full EMU survey). We apply our coarse-grained complexity measure to data from the EMU Pilot Survey to detect and confirm anomalous objects in this data set and produce an anomaly catalogue. Rather than work with existing catalogue data using a specific source detection algorithm, we perform a blind scan of the area, computing the complexity using a sliding square aperture. The effectiveness of the complexity measure for identifying anomalous objects is evaluated using crowd-sourced labels generated via the Zooniverse.org platform. We find that the complexity scan identifies unusual sources, such as odd radio circles, by partitioning on complexity. We achieve partitions where 5 per cent of the data is estimated to be 86 per cent complete, and 0.5 per cent is estimated to be 94 per cent pure, with respect to anomalies and use this to produce an anomaly catalogue. [ABSTRACT FROM AUTHOR]

Pores, fractures, caves, and other storage spaces are commonly distributed in fractured-vuggy carbonate reservoirs. During the drilling process, more than half of all drill-in fluid loss issues are caused by developed caves. Cave scales range from centimeters to meters, making leak prevention increasingly difficult through the use of traditional technologies. Currently, there is still high demand for the understanding of feasible loss control techniques, especially in fractured-vuggy carbonate reservoirs. Multistage Bridge Plugging (MBP) technology has facilitated pioneering experiments in many oilfields, but the success rate of plugging is less than 50%, and the effects of plugging are uncontrollable and difficult to predict. This is due to a lack of clarity regarding the plugging mechanism and the key controlling factors. In this study, we used the Discrete Element Method (DEM) simulation method to investigate the controlling factors of MBP technology, and analyzed its applicable conditions. We found that the prerequisite for the success of MBP is the presence of a constricted throat near the wellbore when drilling the well hole; the first-stage bridging ball is the key to the success of MBP. Larger ball radius, cave inclination and initial flow rate, and lower ball velocity are beneficial to the first-stage bridging. All discussion in this research is based on the ideal situation. However, the cave pattern is difficult to describe using several models, let alone by one ideal model. With the progress of seismic fine description technology and mud logging, more accurate characterization of caves in carbonate reservoirs will help to accurately formulate the plugging scheme and greatly improve the success rate of plugging technology. Additionally, the engineering risks of this technology, such as plugging the coiled tubing, need to be further studied. [ABSTRACT FROM AUTHOR]

In this work, we examine the classification accuracy and robustness of a state-of-the-art semi-supervised learning (SSL) algorithm applied to the morphological classification of radio galaxies. We test if SSL with fewer labels can achieve test accuracies comparable to the supervised state of the art and whether this holds when incorporating previously unseen data. We find that for the radio galaxy classification problem considered, SSL provides additional regularization and outperforms the baseline test accuracy. However, in contrast to model performance metrics reported on computer science benchmarking data sets, we find that improvement is limited to a narrow range of label volumes, with performance falling off rapidly at low label volumes. Additionally, we show that SSL does not improve model calibration, regardless of whether classification is improved. Moreover, we find that when different underlying catalogues drawn from the same radio survey are used to provide the labelled and unlabelled data sets required for SSL, a significant drop in classification performance is observed, highlighting the difficulty of applying SSL techniques under data set shift. We show that a class-imbalanced unlabelled data pool negatively affects performance through prior probability shift, which we suggest may explain this performance drop, and that using the Fréchet distance between labelled and unlabelled data sets as a measure of data set shift can provide a prediction of model performance, but that for typical radio galaxy data sets with labelled sample volumes of |$\mathcal {O}(10^3)$|⁠ , the sample variance associated with this technique is high and the technique is in general not sufficiently robust to replace a train–test cycle. [ABSTRACT FROM AUTHOR]

Poly(lactic acid) (PLA) is an emerging plastic that has insufficient properties (e.g., it is too brittle) for widespread commercial use. Previous research results have shown that the strength and toughness of basalt fiber reinforced PLA composites (PLA/BF) still need to be improved. To address this limitation, this study aimed to obtain an effective compatibilizer for PLA/BF. Melt-blending of poly(butylene adipate-co-terephthalate) (PBAT) with PLA in the presence of 4,4′-methylene diphenyl diisocyanate (MDI: 0.5 wt% of the total resin) afforded PLA/PBAT-MDI triblock copolymers. The triblock copolymers were melt-blended to improve the interfacial adhesion of PLA/BF and thus obtain excellent performance of the PLA-ternary polymers. This work presents the first investigation on the effects of PLA/PBAT-MDI triblock copolymers as compatibilizers for PLA/BF blends. The resultant mechanics, the morphology, interface, crystallinity, and thermal stability of the PLA-bio polymers were comprehensively examined via standard characterization techniques. The crystallinity of the PLA-ternary polymers was as high as 43.6%, 1.44× that of PLA/BF, and 163.5% higher than that of pure PLA. The stored energy of the PLA-ternary polymers reached 20,306.2 MPa, 5.5× than that of PLA/BF, and 18.6× of pure PLA. Moreover, the fatigue life of the PLA-ternary polymers was substantially improved, 5.85× than that of PLA/PBAT-MDI triblock copolymers. Thus, the PLA/PBAT-MDI triblock copolymers are compatibilizers that improve the mechanical properties of PLA/BF. [ABSTRACT FROM AUTHOR]

There are various sedimentary structures developed in the black shales of the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation in Luzhou area, southern Sichuan Basin, southwestern China. In order to evaluate the controlling effects of sedimentary structures on the key parameters of shale reservoir properties, collected classification of sedimentary structures, scanning electron microscope observation, analysis of shale fabric and porosity characteristics, low‐pressure nitrogen adsorption, methane isothermal adsorption, and conventional triaxial compression test were carried out based on shale samples from Wells A‐H1, B‐H1, C‐H1 and D‐H1 in the study area. The sedimentary structures recorded in these shales are categorized into five types: homogeneous bedding, weak horizontal bedding, strong horizontal bedding, discontinuous ripple bedding, and gravel‐bearing massive bedding. In general, the palaeo‐hydrodynamics and oxygen content of water columns were weak when homogeneous bedding shale was deposited. The organic matter is the most abundant and the total organic carbon content is up to 4.01% on average. The average quartz content is 43.5%, and the brittleness index is the highest. The porosity and adsorption capacity were the highest, with an average of 4.57% and 79.5 scf/ton, respectively. Combined with its mechanical properties of low Poisson's ratio and high Young's modulus, homogeneous bedding sedimentary structure is associated with the shale units possessing the highest organic matter abundance, the strongest reservoir property, and the best fracability, which is the priority target for exploration and development of the Wufeng to lower Longmaxi Formation in the Sichuan Basin, southwestern China. [ABSTRACT FROM AUTHOR]

In this paper, the DBR all-visible mercury-free high-temperature and high-pressure multifunctional formation fluid PVT analyzer developed and produced by Schlumberger company is used to conduct an experimental study on phase behavior characteristics of one offshore high CO2 condensate gas wells. The experiments include two-phase flash experiment, constant composition expansion experiment (CCE experiment), and constant volume depletion experiment (CVD experiment). Experimental results show that the higher the CO2 content in the condensate gas system, the higher the gas-oil ratio of condensate gas, the greater the density of condensate oil, the higher the dew point pressure of condensate gas, the greater the relative volume of condensate gas, the smaller the amount of retrograde condensate oil. And the higher the CO2 content in the condensate gas system, the phase diagram is shifted to the left and up, the critical point of the phase diagram is shifted to the lower left, the smaller the area of the two-phase envelope, the lighter the condensate gas system, the condensate oil recovery is higher. The above experimental results revealed that CO2 is well soluble with condensate gas, the expansion capacity of the condensate gas system was slightly enhanced, and because CO2 has a good extraction capacity, the light components of condensate gas were constantly extracted, the retrograde condensate rate of condensate oil decreases, and the maximum retrograde condensate volume also decreased. However, the condensate oil was produced along with the natural gas, and the higher the CO2 content, the stronger the extraction, the more condensate oil was produced. It is mainly because CO2 has the strong gasification and extraction capacity, on the one hand, the retrograde condensation of condensate gas was inhibited, and on the other hand, reverse evaporation of condensate oil was enhanced. The above experimental results indicate the law of the effect of CO2 on the phase behavior characteristics of condensate gas reservoirs, providing theoretical basis and guidance for the efficient development of condensate gas reservoirs at sea. [ABSTRACT FROM AUTHOR]

The upcoming next-generation large area radio continuum surveys can expect tens of millions of radio sources, rendering the traditional method for radio morphology classification through visual inspection unfeasible. We present Claran — C la ssifying R adio sources A utomatically with N eural networks — a proof-of-concept radio source morphology classifier based upon the Faster Region-based Convolutional Neutral Networks method. Specifically, we train and test Claran on the FIRST and WISE (Wide-field Infrared Survey Explorer) images from the Radio Galaxy Zoo Data Release 1 catalogue. Claran provides end users with automated identification of radio source morphology classifications from a simple input of a radio image and a counterpart infrared image of the same region. Claran is the first open-source, end-to-end radio source morphology classifier that is capable of locating and associating discrete and extended components of radio sources in a fast (<200 ms per image) and accurate (≥90 per cent) fashion. Future work will improve Claran 's relatively lower success rates in dealing with multisource fields and will enable Claran to identify sources on much larger fields without loss in classification accuracy. [ABSTRACT FROM AUTHOR]