Inter-layer interference for multi-layered tight gas reservoir in the absence and presence of movable water

Due to the dissimilarity among different producing layers,the influences of inter-layer interference on the production performance of a multi-layer gas reservoir are possible.However,systematic studies of inter-layer interference for tight gas reservoirs are really limited,especially for those reservoirs in the presence of water.In this work,five types of possible inter-layer interferences,including both absence and presence of water,are identified for commingled production of tight gas reservoirs.Subsequently,a series of reservoir-scale and pore-scale numerical simulations are conducted to quantify the degree of influence of each type of interference.Consistent field evidence from the Yan'an tight gas reservoir(Ordos Basin,China)is found to support the simulation results.Additionally,suggestions are proposed to mitigate the potential inter-layer interferences.The results indicate that,in the absence of water,commingled production is favorable in two situations:when there is a difference in physical properties and when there is a difference in the pressure system of each layer.For reservoirs with a multi-pressure system,the backflow phenomenon,which significantly influences the production performance,only occurs under extreme conditions(such as very low production rates or well shut-in periods).When water is introduced into the multi-layer system,inter-layer interference becomes nearly inevitable.Perforating both the gas-rich layer and water-rich layer for commingled production is not desirable,as it can trigger water invasion from the water-rich layer into the gas-rich layer.The gas-rich layer might also be interfered with by water from the neighboring unperforated water-rich layer,where the water might break the barrier(eg weak joint surface,cement in fractures)between the two layers and migrate into the gas-rich layer.Additionally,the gas-rich layer could possibly be interfered with by water that accumulates at the bottom of the wellbore due to gravitational differentiation during shut-in operations.

Gas-Water Production of a Continental Tight-Sandstone Gas Reservoir under Different Fracturing Conditions

A numerical model of hydraulic fracture propagation is introduced for a representative reservoir(Yuanba continental tight sandstone gas reservoir in Northeast Sichuan).Different parameters are considered,i.e.,the interlayer stress difference,the fracturing discharge rate and the fracturing fluid viscosity.The results show that these factors affect the gas and water production by influencing the fracture size.The interlayer stress difference can effectively control the fracture height.The greater the stress difference,the smaller the dimensionless reconstruction volume of the reservoir,while the flowback rate and gas production are lower.A large displacement fracturing construction increases the fracture-forming efficiency and expands the fracture size.The larger the displacement of fracturing construction,the larger the dimensionless reconstruction volume of the reservoir,and the higher the fracture-forming efficiency of fracturing fluid,the flowback rate,and the gas production.Low viscosity fracturing fluid is suitable for long fractures,while high viscosity fracturing fluid is suitable for wide fractures.With an increase in the fracturing fluid viscosity,the dimensionless reconstruction volume and flowback rate of the reservoir display a non-monotonic behavior,however,their changes are relatively small.

Water source identification in mines combining LIF technology and ResNet

The problem of mine water source has always been an important hidden danger in mine safety production.The water source under the mine working face may lead to geological disasters,such as mine collapse and water disaster.The research background of mine water source identification involves many fields such as mining production,environmental protection,resource utilization and technological progress.It is a comprehensive and interdisciplinary subject,which helps to improve the safety and sustainability of mine production.Therefore,timely and accurate identification and control of mine water source is very important to ensure mine production safety.Laser-Induced Fluorescence(LIF)technology,characterized by high sensitivity,specificity,and spatial resolution,overcomes the time-consuming nature of traditional chemical methods.In this experiment,sandstone water and old air water were collected from the Huainan mining area as original samples.Five types of mixed water samples were prepared by varying their proportions,in addition to the two original water samples,resulting in a total of seven different water samples for testing.Four preprocessing methods,namely,MinMaxScaler,StandardScaler,Standard Normal Variate(SNV)transformation,and Centering Transformation(CT),were applied to preprocess the original spectral data to reduce noise and interference.CT was determined as the optimal preprocessing method based on class discrimination,data distribution,and data range.To maintain the original data features while reducing the data dimension,including the original spectral data,five sets of data were subjected to Principal Component Analysis(PCA)and Linear Discriminant Analysis(LDA)dimensionality reduction.Through comparing the clustering effect and Fisher's ratio of the first three dimensions,PCA was identified as the optimal dimensionality reduction method.Finally,two neural network models,CT+PCA+CNN and CT+PCA+ResNet,were constructed by combining Convolutional Neural Networks(CNN)and Residual Neural Networks(ResNet),respectively.When selecting the neural network models,the training time,number of iterative parameters,accuracy,and cross-entropy loss function in the classification problem were compared to determine the model best suited for water source data.The results indicated that CT+PCA+ResNet was the optimal approach for water source identification in this study.

Rate transient analysis methods for water-producing gas wells in tight reservoirs with mobile water

Tight gas reservoirs with mobile water exhibit multi-phase flow and high stress sensitivity.Accurately analyzing the reservoir and well parameters using conventional single-phase rate transient analysis methods proves challenging.This study introduces novel rate transient analysis methods incorporating evaluation processes based on the conventional flowing material balance method and the Blasingame type-curve method to examine fractured gas wells producing water.By positing a gas-water two-phase equivalent homogenous phase that considers characteristics of mobile water,gas,and high stress sensitivity,the conventional single-phase rate transient analysis methods can be applied by integrating the phase's characteristics and defining the phase's normalized parameters and material balance pseudotime.The rate transient analysis methods based on the equivalent homogenous phase can be used to quantitatively assess the parameters of wells and gas reservoirs,such as original gas-in-place,fracture half-length,reservoir permeability,and well drainage radius.This facilitates the analysis of production dynamics of fractured wells and well-controlled areas,subsequently aiding in locating residual gas and guiding the configuration of well patterns.The specific evaluation processes are detailed.Additionally,a numerical simulation mechanism model was constructed to verify the reliability of the developed methods.The methods introduced have been successfully implemented in field water-producing gas wells within tight gas reservoirs containing mobile water.

Gas liquid cylindrical cyclone flow regime identification using machine learning combined with experimental mechanism explanation

The flow regimes of GLCC with horizon inlet and a vertical pipe are investigated in experiments,and the velocities and pressure drops data labeled by the corresponding flow regimes are collected.Combined with the flow regimes data of other GLCC positions from other literatures in existence,the gas and liquid superficial velocities and pressure drops are used as the input of the machine learning algorithms respectively which are applied to identify the flow regimes.The choosing of input data types takes the availability of data for practical industry fields into consideration,and the twelve machine learning algorithms are chosen from the classical and popular algorithms in the area of classification,including the typical ensemble models,SVM,KNN,Bayesian Model and MLP.The results of flow regimes identification show that gas and liquid superficial velocities are the ideal type of input data for the flow regimes identification by machine learning.Most of the ensemble models can identify the flow regimes of GLCC by gas and liquid velocities with the accuracy of 0.99 and more.For the pressure drops as the input of each algorithm,it is not the suitable as gas and liquid velocities,and only XGBoost and Bagging Tree can identify the GLCC flow regimes accurately.The success and confusion of each algorithm are analyzed and explained based on the experimental phenomena of flow regimes evolution processes,the flow regimes map,and the principles of algorithms.The applicability and feasibility of each algorithm according to different types of data for GLCC flow regimes identification are proposed.

Intelligent risk identification of gas drilling based on nonlinear classification network

During the transient process of gas drilling conditions,the monitoring data often has obvious nonlinear fluctuation features,which leads to large classification errors and time delays in the commonly used intelligent classification models.Combined with the structural features of data samples obtained from monitoring while drilling,this paper uses convolution algorithm to extract the correlation features of multiple monitoring while drilling parameters changing with time,and applies RBF network with nonlinear classification ability to classify the features.In the training process,the loss function component based on distance mean square error is used to effectively adjust the best clustering center in RBF.Many field applications show that,the recognition accuracy of the above nonlinear classification network model for gas production,water production and drill sticking is 97.32%,95.25%and 93.78%.Compared with the traditional convolutional neural network(CNN)model,the network structure not only improves the classification accuracy of conditions in the transition stage of conditions,but also greatly advances the time points of risk identification,especially for the three common risk identification points of gas production,water production and drill sticking,which are advanced by 56,16 and 8 s.It has won valuable time for the site to take correct risk disposal measures in time,and fully demonstrated the applicability of nonlinear classification neural network in oil and gas field exploration and development.

Identification of Mine Water Inrush Source Based on PCA-BP Neural Network

It is of great significance to analyze the chemical indexes of mine water and develop a rapid identification system of water source, which can quickly and accurately distinguish the causes of water inrush and identify the source of water inrush, so as to reduce casualties and economic losses and prevent and control water inrush disasters. Taking Ca2+, Mg2+, Na+ + K+, , , Cl-, pH value and TDS as discriminant indexes, the principal component analysis method was used to reduce the dimension of data, and the identification model of mine water inrush source based on PCA-BP neural network was established. 96 sets of data of different aquifers in Panxie mining area were selected for prediction analysis, and 20 sets of randomly selected data were tested, with an accuracy rate of 95%. The model can effectively reduce data redundancy, has a high recognition rate, and can accurately and quickly identify the water source of mine water inrush.

Source identification of methane in groundwater in shale gas development areas:A critical review of the state of the art,prospects,and future challenges

The study aims to identify a suitable site for open and bore well in a farmhouseusing ground magnetic survey in south India.It also aims to define depth to granitoid and structural elements which traverse the selected area.Magnetic data(n=84)measured,processed and interpreted as qualitative and quantitatively.The results of total magnetic intensities indicate that the area is composed of linear magnetic lows trending NE-SW direction and circular to semi-circular causative bodies.The magnetic values ranged from-137 nT to 2345 nT with a mean of 465 nT.Reduction to equator shows significant shifting of causative bodies in the southern and northern directions.Analytical signal map shows exact boundary of granitic bodies.Cosine directional filter has brought out structural element trending NE-SW direction.Results of individual profile brought to light structurally weak zone between 90 m and 100 m in all the profile lines.Sudden decrease of magnetic values from 2042 nT to 126 nT noticed in profile line 6 between 20 m and 30 m indicates fault occurrence.Magnetic breaks obtained from these maps were visualized,interpreted and identified two suitable sites for open and bore well.Radially averaged power spectrum estimates depth of shallow and deep sources in 5 m and 50 m,respectively.Euler method has also been applied to estimate depth of granitoid and structural elements using structural indexes 0,1,2,and 3 and found depth ranges from<10 m to>90 m.Study indicates magnetic method is one of the geophysical methods suitable for groundwater exploration and site selection for open and borewells.

Identification Signs and Prospects of Hydrate Gas

Gas hydrate is a kind of icy crystal body formed by water and natural gas in special conditions. The discovery of gas hydrates provides a wide sphere and a new way of thinking for finding clean and effective energy resources to replace increasingly exhausted traditional energy resources. Moreover, in our country there are a wide realm and bright prospect in the exploration of gas hydrate. This paper has summarized the progress on the study of gas hydrate. And based on the former research about gas hydrates, the integrative identification signs of gas hydrates were summarized in the aspects of seismic data, geophysical well logging, sedimentary and rock, geochemistry, topography and morphology. In the end, the author hopes it may provide some useful clues to the exploration of gas hydrate.

Shale gas transport in nanopores with mobile water films and water bridge

Gas flow properties in nanopores are significantly determined by the flow patterns. Slug flow pattern is a potential water–gas two phase flow pattern, in which gas molecules flow in form of gas slugs and water molecules separate gas slugs. Considering water slippage, a portion of water molecules accumulates at the wall with lower mobility, while the remaining water molecules take the shape of a water bridge. Adopting foam apparent viscosity model to represent slug rheological behavior, how water bridge disturbs on gas flow capacity is estimated. The results are compared with the water–gas two phase flow model that assumes annular flow pattern as well as the single gas flow model without the consideration of water. The comparison illustrates that gas molecular movement is significantly hindered by flow space reduction and loss of gas slippage. The impact from water phase of slug flow pattern is more significant than that of annular flow pattern on gas flow capacity. It is discovered that larger nanopores improve gas flow capacity while maintaining bulk water layer thickness and increasing water bridge thickness tend to reduce gas transport ability. A better understanding of the structure and transport of water and gas molecules is conducive to figure out the specific gas–water flow behavior and predict shale gas production.

For more and purer hydrogen-the progress and challenges in water gas shift reaction

The water gas shift(WGS) reaction is a standard reaction that is widely used in industrial hydrogen production and removal of carbon monoxide. The improved catalytic performance of WGS reaction also contributes to ammonia synthesis and other reactions. Advanced catalysts have been developed for both high and low-temperature reactions and are widely used in industry. In recent years, supported metal nanoparticle catalysts have been researched due to their high metal utilization. Low-temperature catalysts have shown promising results, including high selectivity, high shift rates, and higher activity potential. Additionally, significant progress has been made in removing trace CO through the redox reaction in electrolytic cell. This paper reviews the development of WGS reaction catalysts, including the reaction mechanism, catalyst design, and innovative research methods. The catalyst plays a crucial role in the WGS reaction, and this paper provides an instant of catalyst design under different conditions. The progress of catalysts is closely related to the development of advanced characterization techniques.Furthermore, modifying the catalyst surface to enhance activity and significantly increase reaction kinetics is a current research direction. This review goals to stimulate a better understanding of catalyst design, performance optimization, and driving mechanisms, leading to further progress in this field.

Permeability evolution and gas flow in wet coal under non-equilibrium state:Considering both water swelling and process-based gas swelling

Accurate knowledge of gas flow within the reservoir and related controlling factors will be important for enhancing the production of coal bed methane.At present,most studies focused on the permeability evolution of dry coal under gas adsorption equilibrium,gas flow and gas diffusion within wet coal under the generally non-equilibrium state are often ignored in the process of gas recovery.In this study,an improved apparent permeability model is proposed which accommodates the water and gas adsorption,stress dependence,water film thickness and gas flow regimes.In the process of modeling,the water adsorption is only affected by water content while the gas adsorption is time and water content dependent;based on poroelastic mechanics,the effective fracture aperture and effective pore radius are derived;and then the variation in water film thickness for different pore types under the effect of water content,stress and adsorption swelling are modeled;the flow regimes are considered based on Beskok’s model.Further,after validation with experimental data,the proposed model was applied to numerical simulations to investigate the evolution of permeability-related factors under the effect of different water contents.The gas flow in wet coal under the non-equilibrium state is explicitly revealed.

Self-sealing of fractures in indurated claystones measured by water and gas flow

Self-sealing of fractures in the indurated Callovo-Oxfordian(COX)and Opalinus(OPA)claystones,which are considered as host rocks for disposal of radioactive waste,was investigated on artificially fractured samples.The samples were extracted from four lithological facies relatively rich in clay mineral,carbonate and quartz,respectively.The self-sealing of fractures was measured by fracture closure,water permeability variation,gas penetration,and recovery of gas-induced pathways.Most of the fractured samples exhibited a dramatic reduction inwater permeability to low levels that is close to that of intact rock,depending on their mineralogical composition,fracture intensity,confining stress,and load duration.The self-sealing capacity of the clay-rich samples is higher than that of the carbonate-rich and sandy ones.Significant effects of sample size and fracture intensity were identified.The sealed fractures become gas-tight for certain in-jection pressures.However,the measured gas breakthrough pressures are still lower than the confining stresses.The gas-induced pathways can recover when contacting water.These important findings imply that fractures in such indurated claystones can effectively recover to hinder water transport but allow gas release under relatively low pressures without compromising the rock integrity.

Bohai crude oil identification by gas chromatogram fingerprinting quantitative analysis coupled with cluster analysis

By gas chromatogram, six crude oils fingerprinting distributed in four oilfields and four oil platforms were analyzed and the corre- sponding normal paraffin hydrocarbon （ including pristane and phytane） concentration was obtained by the internal standard methed. The normal paraffin hydrocarbon distribution patterns of six crude oils were built and compared. The cluster analysis on the normal paraffin hydrocarbon concentration was conducted for classification and some ratios of oils were used for oils comparison. The results indicated： there was a clear difference within different crude oils in different oil fields and a small difference between the crude oils in the same oil platform. The normal paraffin hydrocarbon distribution pattern and ratios, as well as the cluster analysis on the nomad paraffin hydrocarbon concentration can have a better differentiation result for the crude oils with small difference than the original gas chromatogram.

Comparative study on identification methods of pipe roughness coefficients in water networks

In this paper,we improve object functions and constraint conditions of genetic algorithms (GAs) applied in PRCs identification of water networks.This identification method can increase calculation efficiency,but can not solve an identification problem with infinitely many solutions well.Then we propose PRCs identification based on the minimal norm method,which satisfies observability conditions and has advantages of high computing efficiency and short time consumption.The two identification methods are applied in a water network,and their identification results are compared under the same conditions.From the results,we know that PRCs identification based on the minimal norm method has advantages of higher computing efficiency,shorter time consumption and higher precision.

Automatic segmentation of gas plumes from multibeam water column images using a U-shape network

Cold seeps are widely developed on the seabed of continental margins and can form gas plumes due to the upward migration of methane-rich fluids.The detection and automatic segmentation of gas plumes are of great significance in locating and studying the cold seep system that is usually accompanied by hydrate layers in the subsurface.A multibeam echo-sounder system(MBES)can record the complete backscatter intensity of the water column,and it is one of the most effective means for detecting cold seeps.However,the gas plumes recorded in multibeam water column images(WCI)are usually blurred due to the interference of the complicated water environment and the sidelobes of the MBES,making it difficult to obtain the effective segmentation.Therefore,based on the existing UNet semantic segmentation network,this paper proposes an AP-UNet network combining the convolutional block attention module and the pyramid pooling module for the automatic segmentation and extraction of gas plumes.Comparative experiments are conducted among three traditional segmentation methods and two deep learning methods.The results show that the AP-UNet segmentation model can effectively suppress complicated water column noise interference.The segmentation precision,the Dice coefficient,and the recall rate of this model are 92.09%,92.00%,and 92.49%,respectively,which are 1.17%,2.10%,and 2.07%higher than the results of the UNet.

Identification of contamination source in water distribution network based on consumer complaints

A new methodology was proposed for contamination source identification using information provided by consumer complaints from a probabilistic view.Due to the high uncertainties of information derived from users,the objective of the proposed methodology doesn't aim to capture a unique solution,but to minimize the number of possible contamination sources.In the proposed methodology,all the possible pollution nodes are identified through the CSA methodology firstly.And then based on the principle of total probability formula,the probability of each possible contamination node is obtained through a series of calculation.According to magnitude of the probability,the number of possible pollution nodes is minimized.The effectiveness and feasibility of the methodology is demonstrated through an application to a real case of ZJ City.Four scenarios were designed to investigate the influence of different uncertainties on the results in this case.The results show that pollutant concentration,injection duration,the number of consumer complaints nodes used for calculation and the prior probability with which consumers would complaint have no particular effect on the identification of contamination source.Three nodes were selected as the most possible pollution sources in water pipe network of ZJ City which includes more than 3 000 nodes.The results show the potential of the proposed method to identify contamination source through consumer complaints.

Gas monitoring data anomaly identification based on spatio-temporal correlativity analysis

Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed. The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided. By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity, the correlative coefficient values range of eight kinds of data anomaly is obtained. Then the gas moni- toring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented. In order to improve the efficiency of analysis, the gas sensors code rules which can express the spatial topological relations are sug- gested. The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.

Quantitative research of the liquid film characteristics in upward vertical gas, oil and water flows

The study of liquid film characteristics in multiphase flow is a very important research topic, however,the characteristics of the liquid film around Taylor bubble structure in gas, oil and water three-phase flow are not clear. In the present study, a novel liquid film sensor is applied to measure the distributed signals of the liquid film in three-phase flow. Based on the liquid film signals, the liquid film characteristics including the structural characteristics and the nonlinear dynamics characteristics in three-phase flows are investigated for the first time. The structural characteristics including the proportion, the appearance frequency and the thickness of the liquid film are obtained and the influences of the liquid and gas superficial velocities and the oil content on them are investigated. To investigate the nonlinear dynamics characteristics of the liquid film with the changing flow conditions, the entropy analysis is introduced to successfully uncover and quantify the dynamic complexity of the liquid film behavior.

Real-time Monitoring of Subsea Gas Pipelines,Offshore Platforms,and Ship Inspection Scores Using an Automatic Identification System

The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS).The research also focuses on the integration of shipping database,AIS data,and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines.A simple concept is used in the development of this prototype,which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship’s coordinates(longitude/latitude)as detected by AIS.Using such information,we can then build an early warning system(EWS)relayed through short message service(SMS),email,or other means when the ship enters the restricted and exclusion zone of platforms and pipelines.The ship inspection system is developed by combining several attributes.Then,decision analysis software is employed to prioritize the vessel’s four attributes,including ship age,ship type,classification,and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines,as well as the efficient use of patrol boats in monitoring the safety of the facilities.Meanwhile,ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.