Porosity Volume Research Articles

Estimation of porosity distribution from formation image logs and comparing the results with NMR log analysis: Implications for the heterogeneity analysis of carbonate reservoirs with an example from the Asmari reservoir, southwest Iran

Estimating heterogeneity in carbonate rocks is the most important parameter in identifying reservoir and non-reservoir areas. Diagenetic and sedimentary processes directly control reservoir heterogeneity. In this regard, the high hydrocarbon production rate and the reduction of the complexity of the carbonate reservoirs require the evaluation of a new architecture of the reservoir, in which the simultaneous impact of the diagenetic-sedimentary processes on the petrophysical logs is investigated. The current study studies the Oligocene-Miocene Asmari Formation Iran's giant carbonate reservoir. Based on petrographic studies, sedimentary facies, depositional environment and diagenetic processes were characterized. Formation evaluation was conducted to determine lithology, water saturation, fluid volume, and effective porosity. The estimated porosity from the evaluation of the conventional logs (full suite) was compared with the results of estimating the porosity from the NMR T2 distribution curve and the porosity histogram of the image logs. Lorenz's coefficient of heterogeneity was used to understand the heterogeneity of the reservoir. Diagenetic-sedimentary processes and petrophysical logs were used to investigate the pore type and their distribution. The results of petrographic studies, NMR T2 distribution curve, and porosity histogram show that the diagenetic-sedimentary process is the most important factor enhancing the reservoir heterogeneity. Diagenetic and sedimentary processes were traced by evaluating NMR and Image logs. Based on the results, the porosity distribution using the T2 curve and Image show a good agreement. Diagenetic processes mainly dissolution and dolomitization increased the heterogeneity of the main production zones (zones 3 and 4) of the Asmari reservoir that was confirmed using NMR and Image logs.

In Situ Construction of (NiCo)3Se4 Nanobeads Embedded in N-Doped Carbon 3D Interconnected Networks for Enhanced Sodium Storage.

Transition metal selenides, boasting remarkable specific capacity, have emerged as a promising electrode material. However, the substantial volume fluctuations during sodium ion insertion and extraction result in inadequate cyclic stability and rate performance, impeding their practical utility. Here, we synthesized N-doped carbon three-dimensional (3D) interconnected networks encapsulating (NiCo)3Se4 nanoparticles, denoted as ((NiCo)3Se4/N-C), exhibiting a bead-like structure and carbon confinement through electrospinning and subsequent thermal treatment. The N-doped carbon 3D interconnected networks possess high porosity and ample volume buffering capacity, enhance conductivity, shorten ion diffusion paths, and mitigate mechanical stress induced by volume changes during cycling. The uniformly distributed (NiCo)3Se4 nanoparticles, featuring a stable structure, demonstrate rapid electrochemical kinetics and numerous available active sites. The distinctive structure and composition of the optimized (NiCo)3Se4/N-C material showcase a high specific capacity (656.2 mAh g-1 at 0.1 A g-1) and an outstanding rate capability. A kinetic analysis confirms that (NiCo)3Se4/N-C stimulates the pseudocapacitive Na+ storage mechanism with capacitance contributing up to 89.2% of the total capacity. This unique structure design and doping approach provide new insights into the design of electrode materials for high-performance batteries.

The influence range of the biogas desaturation method for mitigating sand liquefaction

To clarify the influence range and saturation distribution after the biogas desaturation method is applied, a three-dimensional model is established with TOUGH2 software to analyze the effect of construction parameters such as grouting volume, grouting rate, grouting depth, nitrogen source concentration, and soil porosity. After that, the sensitivity of the parameters on the influence range is determined. The grouting volume and soil porosity are the most sensitive to the lateral and vertical influence range, respectively. This study provides a basis for the engineering practice of treating liquefiable subgrade by the biogas desaturation method.

Effects of ultrasonic pre-treatment on the porosity, shrinkage behaviors, and heat pump drying kinetics of scallop adductors considering shrinkage correction

Shrinkage has a negative impact on drying efficiency and quality. However, insufficient information about the effect of shrinkage on drying kinetics hampers the comprehension of the underlying mechanism. This study aims to investigate the effects of ultrasonic (US) pre-treatment and drying conditions on volume ratio (VR), apparent density, and porosity, as well as drying kinetics with and without shrinkage correction of scallop adductors during heat pump drying. The VR and apparent density decreased, while porosity increased with higher drying temperatures and longer drying times. US pre-treatment resulted in decreased apparent density, but enhanced VR and porosity, demonstrating the effective role of US in alleviating shrinkage and promoting pore formation during drying. Ignoring shrinkage phenomenon caused a weak underestimation in drying efficiency but a significant overestimation in the effective moisture diffusivity coefficient. Therefore, shrinkage effect must be considered to properly comprehend drying behaviors. The mechanism of shrinkage was closely related to the glass transition theory. The critical moisture ratio at which the samples underwent a glass transition was increased by 15 % with US pre-treatment in comparison to the control. US-pretreated samples could achieve a glassy state more quickly than the control under the same drying conditions, leading to reduced volumetric shrinkage.

Green synthesis of Vitis vinifera extract-appended magnesium oxide NPs for biomedical applications

Abstract Biologically active magnesium oxide (MgO) nanoparticles were synthesised using green reduction with an extract derived from the Vitis vinifera plant. The investigation focused on examining the structure and carbon abundance resulting from the thermal degradation of adsorbed biomolecules. It was accomplished using powder X-ray diffraction, Raman spectroscopy, and FT-IR analysis techniques. X-ray photoelectron spectroscopy studies conducted on MgO nanoparticles indicate the absence of any supplementary peaks, thereby indicating the purity of the material. The morphological characteristics, which have been examined using field emission scanning electron microscopy and TEM methodologies, demonstrate the presence of particles with a spherical shape, exhibiting minimal agglomeration and a uniform distribution across the surfaces of MgO. The porous structure, porosity, and pore volume of the MgO particles were evaluated using Brunauer-Emmett-Teller surface analysis. The experimental findings reveal that the surface area of the MgO nanoparticles is 23.8742 m2/g, while the total pore volume is 0.12528 cm3/g. Additionally, the average pore diameter is determined to be 1.7 nm. These observations collectively suggest the presence of microporous structures within the MgO nanoparticles. This article discusses the biological studies to assess the antibacterial, antifungal, anti-inflammatory, and anti-diabetic activities of the synthesised MgO nanoparticles.

A Voronoi-based gaussian smoothing algorithm for efficiently generating RVEs of multi-phase composites with graded aggregates and random pores

This paper presents an innovative numerical modeling framework capable of generating highly realistic 3D mesoscale multi-phase concrete models with unprecedented efficiency and accuracy. Addressing a significant wide range in aggregate volume fraction (0 to 80%) and featuring rapid model generation capabilities, our framework marks a breakthrough in reducing computational time—achieving simulations of 1 million elements within mere 30 s on readily available hardware. By analyzing randomly generated concrete samples across varying compositions, our algorithm can provide deep mesoscopic insights into their compressive properties, validated against a wide array of experimental results. Additionally, our comprehensive analytical model sheds light on the intricate roles of aggregate volume fraction and porosity, enhancing understanding of the meso-scale compressive behavior. We also make the source code available on GitHub, offering a valuable tool for the engineering and research community to optimize concrete material design and performance.

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. An iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

Prediction of reservoir properties and fluids using rock physics techniques in the Rio Del Rey Basin, Cameroon

The application of rock physics modeling has been a breakthrough in oil and gas industry and has greatly managed exploration and interpretation risk. In the Rio del Rey Basin, the rock physics method was used to ascertain the reservoir's characteristics and relate them to the elastic characteristics. Using conventional techniques to connect to the elastic properties and assess various rock physics diagnostics, the estimated petrophysical parameters were water saturations, porosity, and shale volume. By connecting the saturated bulk modulus to its porosity, the bulk modulus of the porous frame, the bulk modulus of the mineral matrix, and the bulk modulus of the pore filling fluids, the Gassmann fluid replacement modeling was used to simulate various fluid scenarios. Finally, an evaluation was conducted on rock physics boundaries and cement models. The reservoirs are rated as extremely good based on the results. The rock physics model generated showed the friable sand model is a suitable model for the said basin and the rock physics bounds that were evaluated indicated that the sediments are deposited below the critical porosity and less compacted thereby depicting a soft sand model. Conventional petrophysical study would not be able to reveal the clustering of the gas sands from the brine sand and the shale zone in connection to the geologic trend as demonstrated by the rock physics template. The anticipated model will be useful to extrapolate the study to other sedimentary basins in Cameroon and estimate porosity from the impedance acquired from seismic data throughout the basin.

Effect of Exposure Conditions on Mortar Subjected to an External Sulfate Attack.

This study aims to investigate the influence of exposure conditions on the behavior of mortar subjected to an external sulfate attack (ESA). Three different exposure conditions (full immersion, semi-immersion, and drying/wetting cycles) were tested on mortar prisms made with Portland cement and two w/c ratios (0.45 and 0.6). To monitor degradation, it was necessary to evaluate variations in length (expansion), mass changes, compressive and tensile strengths, changes in the total porosity measured using water accessible porosity tests, and changes in the macroscopic behavior of the samples. Mercury intrusion porosimetry (MIP) was used to determine the size distribution of the pores. It was demonstrated that mixing mortar with the lower w/c ratio of 0.45 results in improved performance against an ESA. This study also demonstrates that the type of exposure to an ESA has no significant effect on the kinetics of sulfate penetration during the exposure period. However, the sample's surface becomes more cracked when subjected to repeated drying and wetting cycles. For all the considered exposure conditions, expansion occurred in three stages. In stage 1, the reaction product (ettringite) precipitated in large voids, without causing significant expansion (the expansion remained low and stable). During the second stage, the reaction products generated growing internal stress. The final stage of expansion resulted in microcracks, strength losses, and the formation of macropores, which ultimately lead to material failure. The MIP results indicate that major changes in the porosity and pore volume distribution occur at the surface layer in regard to the gel and capillary pore ranges.

Thermal comfort and mechanical analysis of vigorous diamond and diaper weaves; warp, weft and balanced float fabrics with equal thread densities

Diamond (pointed twill) and diaper (herringbone twill) woven assemblies are considered ideal for applications where thermal insulation, heat retention, wrinkle resistance, strength, softness, and breathability attributes are crucial. Limited research has been found on the optimization of thermal comfort and mechanical performance of warp face, weft face and balanced float diaper and diamond woven assemblies. In this work six different woven assemblies have been engineered using cotton (cellulosic yarn) on a dobby machine, having warp face (4/2) weft face (2/4) and balanced float (3/3) based diamond and diaper weave designs with equal number of thread densities. Thermal comfort (dry fluid transmission, thermal resistance, stiffness, and overall wet fluid management capability) and mechanical (tensile, puncture and tear strength) tests were performed for developed woven fabrics. The results of diamond warp face sample showed the highest dry fluid transmission and volume porosity. Diamond weft face specimens showed the highest thermal conductivity behavior and diaper weft face exhibited the highest overall wet fluid management capability behavior. Stiffness was the highest in diamond balanced float. Diamond warp faced fabric showed the highest tearing durability and diaper weft face showed the highest tensile resilience in mechanical performance attributes.

Thermomechanical Response of Smart Magneto-Electro-Elastic FGM Nanosensor Beams with Intended Porosity

AbstractThis study investigates the behavior of free vibrations in a variety of porous functionally graded nanobeams composed of ferroelectric barium-titanate (BaTiO3) and magnetostrictive cobalt-ferrite (CoFe2O4). There are four different models of porous nanobeams: the uniform porosity model (UPM), the symmetric porosity model (SPM), the porosity concentrated in the bottom region model (BPM), and the porosity concentrated in the top region model (TPM). The nanobeam constitutive equation calculates strains based on various factors, including classical mechanical stress, thermal expansion, magnetostrictive and electroelastic properties, and nonlocal elasticity. The study investigated the effects of various factors on the free vibration of nanobeams, including thermal stress, thermo-magneto-electroelastic coupling, electric and magnetic field potential, nonlocal features, porosity models, and changes in porosity volume. The temperature-dependent mechanical properties of BaTiO3 and CoFe2O4 have been recently explored in the literature for the first time. The dynamics of nanosensor beams are greatly influenced by temperature-dependent characteristics. As the ratios of CoFe2O4 and BaTiO3 in the nanobeam decrease, the dimensionless frequencies decrease and increase, respectively, based on the material grading index. The dimensionless frequencies were influenced by the nonlocal parameter, external electric potential, and temperature, causing them to rise. On the other hand, the slenderness ratio and external magnetic potential caused the frequencies to drop. The porosity volume ratio has different effects on frequencies depending on the porosity model.

Geochemical evaluation of Washita-Fredericksburg formation as a carbon storage reservoir

Geological carbon sequestration is a promising technique to reduce atmospheric greenhouse gas emissions. The Washita-Fredericksburg formation in the southeastern United States is being considered as a prospective storage formation. This requires understanding the geochemical impact of CO2 injection on the formation, which is the focus of this work. Here, sandstone samples from the Washita-Fredericksburg formation are analyzed to understand their overall mineralogical composition and the potential geochemical processes that might occur following CO2 injection. Powder X-ray diffraction (XRD) analysis, Scanning Electron Microscopy (SEM) imaging, and image analysis were used to identify mineral phases. SEM images were processed to create a segmented mineral map, which was then used to calculate mineral volume fractions and porosity. Results show that the sample has a porosity of 20% and is mainly composed of quartz, K-feldspar, muscovite, and clays. Accessory minerals such as titanite were also found. Reactive transport models were constructed to assess potential CO2-brine-mineral interactions following CO2 injection. Simulation results suggest that the overall extent of mineral dissolution and precipitation reactions over 10,000 days is limited, with muscovite dissolution increasing porosity to 22%. Limited mineral reactions suggest more injected CO2 will exist in free and dissolved forms, which may require more extensive long-term monitoring.

Improving Sweet Bread Properties with Diacetyl Tartaric Acid Ester of Monoglyceride (DATEM)

Diacetyl Tartaric Acid Ester of Monoglyceride (DATEM) has been used in bread making to improve its dough and final product properties. The efficiency of DATEM in bread with the presence of sugar is yet to be studied. Therefore, this study aims to examine the effects of DATEM addition on sweet bread properties, i.e., its water content, loaf volume expansion, porosity and organoleptic properties. Completely Randomized Design (CRD) was employed with 5 treatments and 4 replications. The variables were the addition of DATEM, i.e., 0%, 0.15%, 0.3%, 0.45%, 0.6% (w/w) of the total flour. The data were analyzed using Analysis of Variance (ANOVA) with the significance level of 5%. The study showed that DATEM significantly impacts the physical and organoleptic properties of sweet bread. As DATEM concentration increases, so does moisture content, porosity, and loaf volume. Consequently, the texture becomes softer, and fewer crumbs are produced. Overall, DATEM enhances sweet bread properties, with 0.6% concentration yielding the best results. Sweet bread with 0.6% DATEM exhibited 34.05% moisture content, 76.86% loaf volume expansion, and 3.38 mm porosity.

Forest restoration effects on soil preferential flow in the paleo-periglacial eastern liaoning mountainous regions, China

To provide a practical reference index for the protection of water conservation forests and the establishment of vegetation in different forest restoration areas, we seek to clarify the preferential flow development and its influencing factors under different rainfall events in the forest restoration areas of paleo-periglacial landform in eastern Liaoning Province of China. To quantify the preferential flow development (PFI) in soil profile-scale through soil profile indexes, we carried out dual-tracer experiments with dyeing in two types of forest restoration lands (plantation forest, PF, and natural secondary forest, NSF) in the paleo-periglacial landform forestland to obtain the soil water infiltration trajectories and water-solute transport characteristics. The indexes of preferential flow morphology and pathway diversity (solute migration) were integrated to construct a more complete evaluation system of the PFI. In addition, we explored factors affecting the PFI through soil physical properties and root characteristics. The results showed that: (1) There were obvious preferential flows in both PF and NSF. Compared with NSF, preferential flow in PF diverged earlier, had greater non-equilibrium degree, more paths and higher development degree, and preferential flow was the main infiltration form. (2) Changes in infiltration amount played a key role in altering the PFI, i.e., increasing infiltration amount reduced the PFI, especially in PF (p < 0.05); (3) After water infiltration, the solute Br− diffusion range of the soil profile was wider than that of Brilliant Blue tracer, thus the development of preferential flow was better synthetical reflected by the indexes of water flow morphology and solute distribution characteristics; (4) Differences in the PFI can be explained by variations in clay content, total porosity (TP), and root volume density (RVD), with total path coefficients of 0.824, 0.462, and 0.624, respectively. In addition to establishing different forest restoration types in similar areas, it would be worthwhile to strengthen the prevention and control measures of soil and water loss in NSF, and properly manage PF in a near-natural model to enhance ecologically sustainable development of forest land. The results of this study contribute to the understanding of the hydrological processes of forest ecosystems in paleo-periglacial landforms, and provide theoretical support for the proposed forest management strategies.

ZIF-8 nanoparticles synthesis for pH-sensitive release of corrosion inhibitor

Zeolite imidazole framework-8 (ZIF-8), with porous structure and pH sensitivity, is an ideal stimulus-response nanocarrier for delivering molecules. Choosing the appropriate synthesis conditions for achieving the accessible porosity volume is the main challenge in creating ZIF-8. This study synthesized new micro-mesoporous ZIF-8 nanoparticles with a 3.11 nm pore size using an ultrasonic bath in a methanol-dimethylformamide mixed solvent. The response surface methodology was used to explore the impact of the synthesis environments. It was found that the optimized conditions were 8.38 ligand-to-metal ion ratio, 100 % power, 64 min, and 6.11 methanol/dimethylformamide. The optimized particles loaded with a corrosion inhibitor, 2-mercaptobenzothiazole, demonstrated a faster inhibitor release in acidic pHs due to the breakdown of the ZIF-8 structure. This research concluded that blending solvents with varying strengths can yield superior physicochemical properties, facilitating micro-mesoporous ZIF-8 production with high pore volume. This discovery holds promise for producing ZIF-8-based materials that benefit various applications.

Influence of Zr4+-Co2+ substitution on structure, morphology and dielectric properties of BaZn2U-type hexaferrites

A series of Zr4+-Co2+ substituted U-type hexaferrites (Ba4Zn2Fe36-2xZrxCoxO60 (0.0 ≤ x ≤ 1.0, having Δx = 0.25)) were synthesized via sol-gel auto-combustion method. The samples were sintered at 1200 ° C for 6 h. The impact of Zr–Co substitution on phase, structure, morphology, and dielectric behavior were investigated through XRD, FTIR, SEM, XPS and VNA. XRD studies shows that the U-type hexaferrite phase has been developed and the increase in lattice constants (a & c), cell volume, c/a ratio, and percentage porosity was observed. Sample with x = 0.25 exhibited the smallest crystallite size (34.5 nm). The existence of signature metal-oxygen vibrational bands for hexaferrites was observed by FTIR spectra. SEM analysis reflects that the substitution produces a significant effect on morphology and grain size of the samples. X-ray photoelectron spectra (XPS) of sample x = 1.0 confirmed the chemical and elemental composition. The dielectric constant, dielectric loss, and ac conductivity increases with increasing frequency and decreases with Zr–Co substitution. The lowest reflection loss of RL = −64.5 dB (with MW absorption >99.9 %) was observed for the composition x = 0.5 with pellet thickness of 1.73 mm at 1.05 GHz frequency. Due to the improved bandwidth and better absorption, these hexaferrites can be used in microwave and high frequency applications.

MODELING OF POROUS DRY MATERIALS USING RHEOLOGICALDYNAMICAL ANALOGY

&amp;lt;p class=&amp;quot;ABSTRACT&amp;quot;&amp;gt;A theoretical model for porous viscoelastoplastic (VEP) materials under dry conditions is examined based on the principles of mass and energy conservation using rheological-dynamical analogy (RDA). The model provides the expressions for the creep coefficient, Poisson&amp;#039;s ratio, modulus of elasticity, damage variable and strength in the function of porosity and/or void volume fraction (VVF). Compared with numerous versions of acoustic emission monitoring developed to analyze the behavior of the total wave propagation in inhomogeneous media with density variation, the RDA model is found to be comprehensive in interpretation and consistent with physical understanding. The reliability of the proposed model is confirmed by the comparison of numerical results with experimental ones on hardened concrete and rocks.&amp;lt;/p&amp;gt;

Tridimensional porosity modeling through fuzzy logic and geostatistics

The three-dimensional porosity simulation plays a pivotal role in the exploration and prospecting of oil fields. In this study, we introduce a hybrid methodology for subsismic resolution porosity estimation, combining algorithms based on fuzzy logic and geostatistics. We demonstrate how it is possible to use simulated facies association surfaces and structural surfaces as input parameters for the fuzzy logic algorithm to derive porosity trends, subsequently refined using simple kriging with magnetic resonance log obtained from wells. The selected simulation area is the Sapinhoá field, located in the Santos Basin, Brazil, covering the age interval from 123 Ma to 113 Ma. To statistically validate the results, we employed the Pearson correlation coefficient, along with graphs comparing the measured and simulated porosity in the wells. The obtained results showed satisfactory levels of accuracy in the evaluated wells. Moreover, in areas lacking well data, the simulated porosity volumes aligned with the trends modeled using fuzzy logic.

Ultrasonic velocity anisotropy of Jurassic shales with different lithofacies

Abstract Given the growing importance of organic-rich shale as unconventional reservoirs, a thorough understanding of the elastic and anisotropic behavior of shales is of great concern. However, for lacustrine shales, the complex lithofacies assemblage with geological deposition makes it challenging. Four lithofacies (argillaceous, mixed, siliceous, and calcareous) are recognized for 40 lacustrine shale samples from Jurassic formation in Sichuan Basin on the basis of their mineral compositions. We perform ultrasonic velocity measurements on 40 pairs of shale plugs at varied confining pressures, attempting to uncover the controls on the anisotropic properties of different lithofacies. The experimental results reveal that the total porosity, clay, and organic matter would positively contribute to velocity anisotropy of Jurassic shales. Combined with microstructure and pressure-dependent velocity analysis, the preferred orientations of platy clay particles and lenticular kerogen, the development of clay pores along clay fabric, and the sub-parallel micro-cracks induced by hydrocarbon expulsion are treated to be the controlling mechanisms. We add the total porosity, clay content, and kerogen volume together, intending to distinguish the elastic and anisotropic properties of four lithofacies. Generally, argillaceous shales, the dominant lithofacies in Jurassic formation, could be characterized by the highest clay and total organic content (TOC), the lowest bedding-normal velocities, and the strongest velocity anisotropy. Finally, with the laboratory data, two rock-physics-driven exponential relationships are proposed to predict the P- and S-wave velocity anisotropy with the bedding-normal velocities.

Petrophysical evaluation based on three-stream convolutional neural networks in the Berkine Basin, Algeria

Petrophysical evaluation is a key stage before formation test in exploration field, it allows the identification of the best plays in term of effective porosity, shale volume and hydrocarbon saturation. This paper introduces an innovative approach to petrophysical evaluation by leveraging deep learning techniques, our scheme is based on three streams, in each stream we predict a petrophysical parameter (Volume of shale, Effective Porosity and water saturation), each stream represents a convolutional neural network model that has been trained using traditional wireline logging data from the Silurien argilo-greseux reservoir units in the Berkine Basin, Algeria. experimental results show that our proposed method achieves stat-of-the-art predictions by giving correlated results in comparison against conventional analysis methods (calculated Shale Volume, Porosity and water saturation), furthermore assessment of test data shows also that our method gives good prediction in thin beds reservoirs and offers the ability to detect low resistivity pays. Because our method is based on Convolutional neural network models, it is fast and allows the petrophysical parameters prediction in real time.