A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks

Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales,as well as the flow characteristics in different types of thin layers(tight sandstone gas,shale gas,and coalbed gas).Moreover,a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir.A semi-analytical solution for the production rate is obtained using a matrix iteration method.A specific well is selected for fitting dynamic production data,and the calculation results show that the tight sandstone has the highest gas production per unit thickness compared with the other types of reservoirs.Moreover,desorption and diffusion of coalbed gas and shale gas can significantly contribute to gas production,and the daily production of these two gases decreases rapidly with decreasing reservoir pressure.Interestingly,the gas production from fractures exhibits an approximately U-shaped distribution,indicating the need to optimize the spacing between clusters during hydraulic fracturing to reduce the area of overlapping fracture control.The coal matrix water saturation significantly affects the coalbed gas production,with higher water saturation leading to lower production.

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

A flexible ultra-broadband multi-layered absorber working at 2 GHz-40 GHz printed by resistive ink

A flexible extra broadband metamaterial absorber(MMA)stacked with five layers working at 2 GHz–40 GHz is investigated.Each layer is composed of polyvinyl chloride(PVC),polyimide(PI),and a frequency selective surface(FSS),which is printed on PI using conductive ink.To investigate this absorber,both one-dimensional analogous circuit analysis and three-dimensional full-wave simulation based on a physical model are provided.Various crucial electromagnetic properties,such as absorption,effective impedance,complex permittivity and permeability,electric current distribution and magnetic field distribution at resonant peak points,are studied in detail.Analysis shows that the working frequency of this absorber covers entire S,C,X,Ku,K and Ka bands with a minimum thickness of 0.098λ_(max)(λ_(max) is the maximum wavelength in the absorption band),and the fractional bandwidth(FBW)reaches 181.1%.Moreover,the reflection coefficient is less than-10 dB at 1.998 GHz–40.056 GHz at normal incidence,and the absorptivity of the plane wave is greater than 80%when the incident angle is smaller than 50°.Furthermore,the proposed absorber is experimentally validated,and the experimental results show good agreement with the simulation results,which demonstrates the potential applicability of this absorber at 2 GHz–40 GHz.

Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM

Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.

Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Synergistic anionic/zwitterionic mixed surfactant system with high emulsification efficiency for enhanced oil recovery in low permeability reservoirs

Emulsification is one of the important mechanisms of surfactant flooding. To improve oil recovery for low permeability reservoirs, a highly efficient emulsification oil flooding system consisting of anionic surfactant sodium alkyl glucosyl hydroxypropyl sulfonate(APGSHS) and zwitterionic surfactant octadecyl betaine(BS-18) is proposed. The performance of APGSHS/BS-18 mixed surfactant system was evaluated in terms of interfacial tension, emulsification capability, emulsion size and distribution, wettability alteration, temperature-resistance and salt-resistance. The emulsification speed was used to evaluate the emulsification ability of surfactant systems, and the results show that mixed surfactant systems can completely emulsify the crude oil into emulsions droplets even under low energy conditions. Meanwhile,the system exhibits good temperature and salt resistance. Finally, the best oil recovery of 25.45% is achieved for low permeability core by the mixed surfactant system with a total concentration of 0.3 wt%while the molar ratio of APGSHS:BS-18 is 4:6. The current study indicates that the anionic/zwitterionic mixed surfactant system can improve the oil flooding efficiency and is potential candidate for application in low permeability reservoirs.

Detecting Phishing Using a Multi-Layered Social Engineering Framework

As businesses develop and expand with a significant volume of data,data protection and privacy become increasingly important.Research has shown a tremendous increase in phishing activities during and after COVID-19.This research aimed to improve the existing approaches to detecting phishing activities on the internet.We designed a multi-layered phish detection algorithm to detect and prevent phishing applications on the internet using URLs.In the algorithm,we considered technical dimensions of phishing attack prevention and mitigation on the internet.In our approach,we merge,Phishtank,Blacklist,Blocklist,and Whitelist to form our framework.A web application system and browser extension were developed to implement the algorithm.The multi-layer phish detector evaluated ten thousandURLs gathered randomly from the internet(five thousand phishing and five thousand legitimate URLs).The system was estimated to detect levels of accuracy,true-positive and false-positive values.The system level accuracy was recorded to be 98.16%.Approximately 49.6%of the websites were detected as illegitimate,whilst 49.8%were seen as legitimate.

NEW MODEL OF GAS FLOW PROBLEM IN MULTI-LAYERED GAS RESERVOIR AND APPLICATION

In this paper, the new model of the real gas filtration problem has been presented multi-layered gas reservoir, when a gas well output and wellbore storage may be variable, and have obtained the exact solutions of pressure distribution for each reservoir bed under three kinds of typical out-boundary conditions. As a special case, according to the new model have also obtained the qxact solutions of presssure distribution in homogeneous reservoir and is given important application in gas reservoir development.

Experimental study on the degree and damage-control mechanisms of fuzzy-ball-induced damage in single and multi-layer commingled tight reservoirs

Fuzzy-ball working fluids(FBWFs)have been successfully applied in different development phases of tight reservoirs.Field reports revealed that FBWFs satisfactorily met all the operational and reservoir damage control requirements during their application.However,the damage-control mechanisms and degree of formation damage caused by fuzzy-ball fluids have not been investigated in lab-scale studies so far.In this study,the degree of fuzzy-ball-induced damage in single-and double-layer reservoirs was evaluated through core flooding experiments that were based on permeability and flow rate indexes.Additionally,its damage mechanisms were observed via scanning electron microscope and energy-dispersive spectroscopy tests.The results show that:(1)For single-layer reservoirs,the FBWF induced weak damage on coals and medium-to-weak damage on sandstones,and the difference of the damage in permeability or flow rate index on coals and sandstones is below 1%.Moreover,the minimum permeability recovery rate was above 66%.(2)For double-layer commingled reservoirs,the flow rate index revealed weak damage and the overall damage in double-layer was lower than the single-layer reservoirs.(3)There is no significant alteration in the microscopic structure of fuzzy-ball saturated cores with no evidence of fines migration.The dissolution of lead and sulfur occurred in coal samples,while tellurium in sandstone,aluminum,and magnesium in carbonate.However,the precipitation of aluminum,magnesium,and sodium occurred in sandstone but no precipitates found in coal and carbonate.The temporal plugging and dispersion characteristics of the FBWFs enable the generation of reservoir protection layers that will minimize formation damage due to solid and fluid invasion.

Hydrocarbon accumulation characteristics in basement reservoirs and exploration targets of deep basement reservoirs in onshore China

Based on the global basement reservoir database and the dissection of basement reservoirs in China,the characteristics of hydrocarbon accumulation in basement reservoirs are analyzed,and the favorable conditions for hydrocarbon accumulation in deep basement reservoirs are investigated to highlight the exploration targets.The discovered basement reservoirs worldwide are mainly buried in the Archean and Precambrian granitic and metamorphic formations with depths less than 4500 m,and the relatively large reservoirs have been found in rift,back-arc and foreland basins in tectonic active zones of the Meso-Cenozoic plates.The hydrocarbon accumulation in basement reservoirs exhibits the characteristics in three aspects.First,the porous-fractured reservoirs with low porosity and ultra-low permeability are dominant,where extensive hydrocarbon accumulation occurred during the weathering denudation and later tectonic reworking of the basin basement.High resistance to compaction allows the physical properties of these highly heterogeneous reservoirs to be independent of the buried depth.Second,the hydrocarbons were sourced from the formations outside the basement.The source-reservoir assemblages are divided into contacted source rock-basement and separated source rock-basement patterns.Third,the abnormal high pressure in the source rock and the normal–low pressure in the basement reservoirs cause a large pressure difference between the source rock and the reservoirs,which is conducive to the pumping effect of hydrocarbons in the deep basement.The deep basement prospects are mainly evaluated by the factors such as tectonic activity of basement,source-reservoir combination,development of large deep faults(especially strike-slip faults),and regional seals.The Precambrian crystalline basements at the margin of the intracontinental rifts in cratonic basins,as well as the Paleozoic folded basements and the Meso-Cenozoic fault-block basements adjacent to the hydrocarbon generation depressions,have favorable conditions for hydrocarbon accumulation,and thus they are considered as the main targets for future exploration of deep basement reservoirs.

A review of reservoir damage during hydraulic fracturing of deep and ultra-deep reservoirs

Deep and ultra-deep reservoirs have gradually become the primary focus of hydrocarbon exploration as a result of a series of significant discoveries in deep hydrocarbon exploration worldwide.These reservoirs present unique challenges due to their deep burial depth(4500-8882 m),low matrix permeability,complex crustal stress conditions,high temperature and pressure(HTHP,150-200℃,105-155 MPa),coupled with high salinity of formation water.Consequently,the costs associated with their exploitation and development are exceptionally high.In deep and ultra-deep reservoirs,hydraulic fracturing is commonly used to achieve high and stable production.During hydraulic fracturing,a substantial volume of fluid is injected into the reservoir.However,statistical analysis reveals that the flowback rate is typically less than 30%,leaving the majority of the fluid trapped within the reservoir.Therefore,hydraulic fracturing in deep reservoirs not only enhances the reservoir permeability by creating artificial fractures but also damages reservoirs due to the fracturing fluids involved.The challenging“three-high”environment of a deep reservoir,characterized by high temperature,high pressure,and high salinity,exacerbates conventional forms of damage,including water sensitivity,retention of fracturing fluids,rock creep,and proppant breakage.In addition,specific damage mechanisms come into play,such as fracturing fluid decomposition at elevated temperatures and proppant diagenetic reactions at HTHP conditions.Presently,the foremost concern in deep oil and gas development lies in effectively assessing the damage inflicted on these reservoirs by hydraulic fracturing,comprehending the underlying mechanisms,and selecting appropriate solutions.It's noteworthy that the majority of existing studies on reservoir damage primarily focus on conventional reservoirs,with limited attention given to deep reservoirs and a lack of systematic summaries.In light of this,our approach entails initially summarizing the current knowledge pertaining to the types of fracturing fluids employed in deep and ultra-deep reservoirs.Subsequently,we delve into a systematic examination of the damage processes and mechanisms caused by fracturing fluids within the context of hydraulic fracturing in deep reservoirs,taking into account the unique reservoir characteristics of high temperature,high pressure,and high in-situ stress.In addition,we provide an overview of research progress related to high-temperature deep reservoir fracturing fluid and the damage of aqueous fracturing fluids to rock matrix,both artificial and natural fractures,and sand-packed fractures.We conclude by offering a summary of current research advancements and future directions,which hold significant potential for facilitating the efficient development of deep oil and gas reservoirs while effectively mitigating reservoir damage.

Target Controllability of Multi-Layer Networks With High-Dimensional

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

Fine quantitative characterization of high-H2S gas reservoirs under the influence of liquid sulfur deposition and adsorption

In order to clarify the influence of liquid sulfur deposition and adsorption to high-H2S gas reservoirs,three types of natural cores with typical carbonate pore structures were selected for high-temperature and high-pressure core displacement experiments.Fine quantitative characterization of the cores in three steady states(original,after sulfur injection,and after gas flooding)was carried out using the nuclear magnetic resonance(NMR)transverse relaxation time spectrum and imaging,X-ray computer tomography(CT)of full-diameter cores,basic physical property testing,and field emission scanning electron microscopy imaging.The loss of pore volume caused by sulfur deposition and adsorption mainly comes from the medium and large pores with sizes bigger than 1000μm.Liquid sulfur has a stronger adsorption and deposition ability in smaller pore spaces,and causes greater damage to reservoirs with poor original pore structures.The pore structure of the three types of carbonate reservoirs shows multiple fractal characteristics.The worse the pore structure,the greater the change of internal pore distribution caused by liquid sulfur deposition and adsorption,and the stronger the heterogeneity.Liquid sulfur deposition and adsorption change the pore size distribution,pore connectivity,and heterogeneity of the rock,which further changes the physical properties of the reservoir.After sulfur injection and gas flooding,the permeability of TypeⅠreservoirs with good physical properties decreased by 16%,and that of TypesⅡandⅢreservoirs with poor physical properties decreased by 90%or more,suggesting an extremely high damage.This indicates that the worse the initial physical properties,the greater the damage of liquid sulfur deposition and adsorption.Liquid sulfur is adsorbed and deposited in different types of pore space in the forms of flocculence,cobweb,or retinitis,causing different changes in the pore structure and physical property of the reservoir.

Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process.

Recent advances in reservoir characterization:Introduction

Reservoir characterization refers to the process of creating a comprehensive model that characterizes the reservoir based on its ability to store and produce hydrocarbons.This includes analyzing reservoir fluid behavior under various conditions and identifying optimal production techniques to maximize hydrocarbon recovery.For this,a holistic understanding is required that integrates data from geophysics,geostatistics,petrophysics,geology,and reservoir engineering.

Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia

Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive task.Many researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir heterogeneity.However,these attributes take seismic data as input and might not be sensitive to lateral lithology variation.To incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance inversion.Our proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as input.To evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,Australia.This study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional approach.In addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir characterization.This study also suggests a well-bounded potential reservoir facies distribution along the parallel fault lines.Thus,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage.

Reservoir Quality Controlling Factor of the Asmari Reservoir in an Oil Field in Dezful Embayment, SW Iran

The Asmari Formation Oligo-Miocene in age is one of the most important reservoir rocks in SW Iran and Zagros basin and composed of carbonate rocks and locally sandstones and evaporates. In this research, reservoir quality controlling factors have been investigated in a well in one of the oil fields in Dezful Embayment, SW Iran. Based on this research, depositional environment, diagenesis and fracturing have been affected on reservoir quality. 3 distinct depositional settings can be recognized in the studied interval including tidal flat, lagoon, and shoal. Among these depositional setting, shoal environment with ooid grainstone microfacies along with interparticle porosity shows good reservoir characteristics. Diagenetic processes also play an important role on reservoir quality;dolomitization and dissolution have positive effects on porosity and enhances reservoir quality, while cementation, anhydritization and compaction have negative effect on it. Fracturing is another important factor affected on the carbonate reservoirs especially in the Asmari Formation.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

Microplastics in sediment of the Three Gorges Reservoir:abundance and characteristics under different environmental conditions

Freshwater microplastic pollution is an urgent issue of global concern,and research on the distribution in reservoirs is lacking.We investigated the microplastic pollution levels in wet sediments collected from the Three Gorges Reservoir,the largest reservoir of China.Results show that microplastics were ubiquitous in the sediments of the Three Gorges Reservoir,and their abundance ranged from 59 to 276 pp/kg(plastic particles per kg,dry weight).Economic development and total population were important factors affecting the spatial heterogeneity of microplastic abundance,and the contribution of large cities along the reservoir to microplastic pollution should be paid with more attention.Fibrous microplastics were the most abundant type of microplastic particles in reservoir sediments,whereas polystyrene,polypropylene,and polyamide were the main types of polymers.The apparent spatial heterogeneity in morphology and color of microplastics is attributed to different anthropogenic or landbased pollution sources.Moreover,the accumulation of microplastics near the inlet of tributaries reflects the role of potential contributors of tributaries.More importantly,multiple bisphenols(BPs)and heavy metals detected at the microplastic surfaces indicate that microplastics can act as carriers of these pollutants in the environment in the same way as sediments did,which may alter the environmental fate and toxicity of these pollutants.Therefore,we conclude that the Three Gorges Reservoir had been contaminated with microplastics,which posed a stress risk for organisms who ingest them along with their associated pollutants(BPs,heavy metals).

Multi-layer phenomena in petawatt laser-driven acceleration of heavy ions

Laser-accelerated high-flux-intensity heavy-ion beams are important for new types of accelerators.A particle-in-cell program(Smilei) is employed to simulate the entire process of Station of Extreme Light(SEL) 100 PW laser-accelerated heavy particles using different nanoscale short targets with a thickness of 100 nm Cr, Fe, Ag, Ta, Au, Pb, Th and U, as well as 200 nm thick Al and Ca. An obvious stratification is observed in the simulation. The layering phenomenon is a hybrid acceleration mechanism reflecting target normal sheath acceleration and radiation pressure acceleration, and this phenomenon is understood from the simulated energy spectrum,ionization and spatial electric field distribution. According to the stratification, it is suggested that high-quality heavy-ion beams could be expected for fusion reactions to synthesize superheavy nuclei. Two plasma clusters in the stratification are observed simultaneously, which suggest new techniques for plasma experiments as well as thinner metal targets in the precision machining process.