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The technique of refracturing is an effective method to solve the rapid decline in oil well production caused by factors such as severe reservoir energy loss and fracture failure after the initial hydraulic fracturing of low-permeability reservoirs. The key to designing refracturing lies in establishing a model for evaluating the potential fracturing layers. Based on the geological characteristics of the low-permeability conglomerate reservoir in the Lower Wuerhe area of the Eig District of the Xinjiang Oilfield, this paper studies the influence of different development approaches on the distribution pattern of remaining oil in the reservoir. A coupled model of remaining oil distribution and the in situ stress field is established and discusses the characteristics of the four-dimensional in situ stress field under different development modes. This paper analyzes the influence of geological factors and well network factors on the distribution of residual oil, and analyzes the influence of various factors, such as reservoir properties and injection and extraction parameters, on ground stress. Based on the residual oil distribution and ground stress changes, an evaluation method for screening potential fractured layers in reservoirs with different development modes (water injection development and depletion development) is developed. [ABSTRACT FROM AUTHOR]

The output power of PV systems is influenced by various factors, resulting in strong volatility and randomness, which makes it difficult to forecast. Therefore, this paper proposes an Informer prediction model based on optimised VMD for predicting short-term PV power. Firstly, the temporal coding of the Informer model is improved and, secondly, the original sequence is decomposed into multiple modal components using VMD, and then optimisation of the results of VMD in conjunction with the optimisation strategy of SSA improves the characteristics of the time series data. Finally, the refined data are fed into the Informer framework for modelling and prediction, utilising the self-attention mechanism and multiscale feature fusion of Informer to precisely forecast PV power. The power of PV prediction data from the SSA-VMD-Informer model and four other commonly used models is compared. Experimental results indicate that the SSA-VMD-Informer model performs exceptionally well in short-term PV power prediction, achieving higher accuracy than traditional methods. As an example, the results of predicting the PV power on 24 April in a region of Xinjiang are 1.3882 for RMSE, 0.8310 for MSE, 1.14 for SDE, and 0.9944 for R2. [ABSTRACT FROM AUTHOR]

Oil shale, as a vast potential resource, is considered an important alternative energy source, and its effective development and economic utilization are of significant importance in alleviating the contradiction between energy supply and demand. Presently, the in situ conversion technology for oil shale has gained significant global attention, with numerous extraction methods undergoing active research and development. One of these methods is the in situ conversion of oil shale based on the hydration reaction of calcium-oxide-based composite material (CaO-CM). This approach harnesses the heat produced by the reaction between CaO-CM and water as a heat source for the pyrolysis of oil shale. This paper conducted experiments to assess the feasibility of temperature associated with this method. The feasibility study mainly includes two aspects: First, it is necessary to investigate whether the temperature generated by the hydration reaction of CaO-CM can meet the temperature requirements for the pyrolysis of oil shale. Through pyrolysis experiments of Xinjiang oil shale, the minimum temperature required for oil shale pyrolysis was determined to be 330 °C. High-temperature and high-pressure reaction vessels were employed to explore the temperature generated by the hydration reaction of CaO-CM. The results show that with the increase in environment pressure, environment temperature, and reaction mass, the maximum temperature generated by the hydration reaction of CaO-CM also increases (reach 455.5 °C), meeting the temperature requirements for the pyrolysis of oil shale. Second, the study evaluates whether the hydration reaction of CaO-CM can induce pyrolysis hydrocarbons of the oil shale. Through the pyrolysis experiments of oil shale based on the hydration reaction of CaO-CM, the changes in the content of pyrolysis hydrocarbons (S2) in oil shale before and after pyrolysis are measured. The results show that under 10 MPa pressure, the content of pyrolysis hydrocarbons in the oil shale decreased from 40.96 mg/g to 0.08 mg/g after pyrolysis. This confirms the feasibility of the temperature conditions for the in situ conversion of oil shale based on the hydration reaction of CaO-CM. [ABSTRACT FROM AUTHOR]

Accurate wind power data prediction is crucial to increase wind energy usage since wind power data are characterized by uncertainty and randomness, which present significant obstacles to the scheduling of power grids. This paper proposes a hybrid model for wind power prediction based on complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN), sample entropy (SE), bidirectional long short-term memory network (BiLSTM), and Markov chain (MC). First, CEEMDAN is used to decompose the wind power series into a series of subsequences at various frequencies, and then SE is employed to reconstruct the wind power series subsequences to reduce the model's complexity. Second, the long short-term memory (LSTM) network is optimized, the BiLSTM neural network prediction method is used to predict each reconstruction component, and the results of the different component predictions are superimposed to acquire the total prediction results. Finally, MC is used to correct the model's total prediction results to increase the accuracy of the predictions. Experimental validation with measured data from wind farms in a region of Xinjiang, and computational results demonstrate that the proposed model can better fit wind power data than other prediction models and has greater prediction accuracy and generalizability for enhancing wind power prediction performance. [ABSTRACT FROM AUTHOR]

The southern Junggar Basin, Xinjiang, has abundant coalbed methane (CBM) resources. Currently, the Baiyang River development pilot test area (BYR block for short) in the Fukang east block has achieved large-scale CBM development, but the productivity characteristics and its controlling factor are still unclear. Based on the field production data of the BYR block and experimental tests, this paper summarizes the gas and water production characteristics and presents the analysis results of the geological and geochemical responses to the productivity of CBM wells. The productivity of CBM wells in the BYR block was generally characterized as medium-to-low yield. The productivity was jointly controlled by the burial depth, structure condition, thickness and number of co-production coal seams, and hydrogeological conditions. The gas production first increased and then decreased with the increase in the burial depth of the coal seam, and a burial depth between 750 and 1000 m was the most beneficial to increasing the gas production due to the good gas preservation conditions and suitable permeability and stress conditions. The total thickness of the co-production coal seams had a positive effect on the productivity of gas wells, but the productivity was also affected by the number of co-production coal seams and interlayer interference. In the BYR block, the co-production of the nos. 41 and 42 coal seams was the most favorable combination form for CBM drainage. The productivity of CBM wells had a good response to the Na+, K+ and HCO3− concentrations but a poor response to δD-H2O and δ18O-H2O. Based on the concentrations of the main ions and TDSs of the coal seam water, a productivity response index δ* was established, and there was a good positive correlation between the productivity and δ*. [ABSTRACT FROM AUTHOR]

Hydrogen is receiving unprecedented momentum and is projected to meet a sizable share of the final energy demand in the future. The coupling between the hydrogen and power systems can help integrate volatile renewable energy, reduce curtailment, and realize long-term energy storage. Different coupling modes are being proposed, yet quantitative comparisons are absent. To fill this gap, this paper firstly summarizes the system composition of potential power–hydrogen coupling modes and analyzes their advantages and disadvantages. Then, a model for power–hydrogen coordinated planning optimization is proposed for quantitative analysis. Southern Xinjiang is chosen as a representative of the northwestern area in China, which has plentiful renewable resources and a relatively small local load at present, for a case study. Through result analysis, it is found that the mode of power–hydrogen coupling at the source side, either for in situ utilization or for long-distance transport via pipelines, shows better economic competitiveness. The discussion provides suggestions and a reference to policymakers for formulating infrastructure or industry plans in advance to better accommodate the rapidly developing renewable energy. [ABSTRACT FROM AUTHOR]

Multistage fracturing in horizontal well has become one of the important techniques for the efficient development of low-permeability sandstone reservoirs. In multistage hydraulic fractured horizontal wells (MHFHWs), the depth of fracturing fluid invasion into the formation is a key parameter evaluating the imbibition enhancement after fracturing. However, few studies have been conducted on the invasion depth of fracturing fluids combining experiments and mathematical models under high-pressure differences in MHFHWs. Therefore, in this work, a mathematical model with experimental validation is proposed for evaluating the fracturing fluids invasion under high pressure. We first conducted a series of displacement experiments under different pressure differences to obtain the breakthrough time and invasion velocity. All core samples are taken from the block X of Xinjiang oilfield. A mathematical model of fracturing fluid injection was then established, considering the two-dimensional filtration of fracturing fluid. Then, the calculated invasion velocity was validated against the experimental data. Afterward, the invasion depth and invasion volume were determined for this typical horizontal well. Results show that at the end of 72 min, the invasion depth reaches 1.516 m when measured by core experiments and 1.434 m when calculated by the proposed model. The total invasion volume of all fracturing stages is estimated as 21,560.05 m3 and the actual total fluid volume injected is 24,019.6 m3. The paper formed a scientific and reasonable evaluation method of fracturing fluid invasion depth during the fracturing of horizontal wells, which provides solid theoretical support for the effective evaluation of fracturing to improve oil recovery. [ABSTRACT FROM AUTHOR]

The stability of transmission tower bases is key to ensuring the safe operation of power lines. This paper proposes a joint displacement-control technique for foundation-inclined piles and prestressed foundation tie beams to address the problem of tower base displacement and durability degradation caused by environmental factors. A finite element model of an exposed-pile transmission tower conforming to the structural characteristics of the actual line tower was established based on the current situation of Tower 292 of the ±800 kV Tianzhong line in Xinjiang, China. Three different displacement-control schemes were analyzed under the combined effects of tower line load, ice-cover load, and wind load, including changing exposed pile height, changing inclined pile tilt angle, and increasing the prestressed foundation tie beam. The analysis shows that the combined displacement-control technology of foundation-inclined piles and prestressed foundation tie beams can reduce the horizontal displacement of EHV tower foundations by more than 50%, which greatly reduces safety problems caused by tower displacement and effectively improves tower durability. [ABSTRACT FROM AUTHOR]

There are large, heavy oil reserves in Block X of the Xinjiang oilfields, China. Due to its large burial depth (1300 m) and low permeability (26.0 mD), the traditional steam-injection technology cannot be used to obtain effective development benefits. This paper conducts experimental and simulation research on the feasibility and mechanism of CO 2 -energized fracturing of horizontal wells and N 2 foam huff-n-puff in deep heavy oil reservoirs with low permeability in order to further explore the appropriate production technology. The foaming volume of the foaming agent at different concentrations and the oil displacement effect of N 2 foam at different gas/liquid ratios were compared by the experiments. The results show that a high concentration of foaming agent mixed with crude oil is more conducive to increasing the foaming volume and extending the half-life, and the best foaming agent concentration is 3.0∼4.0%. The 2D micro-scale visualization experiment results show that N 2 foam has a good selective blocking effect, which increases the sweep area. The number of bubbles per unit area increases as the gas/liquid ratio increases, with 3.0∼5.0 being the optimal gas/liquid ratio. Numerical simulation results show that, when CO 2 -energized fracturing technology takes into account the advantages of fracturing and crude oil viscosity reduction by CO 2 dissolution, the phased oil recovery factor in the primary production period can reach approximately 13.7%. A solvent pre-slug with N 2 foam huff-n-puff technology is applied to improve oil recovery factor following primary production for 5∼6 years, and the final oil recovery factor can reach approximately 35.0%. The methodology formulated in this study is particularly significant for the effective development of this oil reservoir with deeply buried depth and low permeability, and would also guide the recovery of similar oil deposits. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) reservoir geological modeling is an advanced reservoir characterization method, which runs through the exploration and the development process of oil and gas fields. Reservoir geological modeling is playing an increasingly significant role in determining the distribution, internal configuration, and quality of a reservoir as well. Conventional variogram-based methods such as statistical interpolation and reservoir geological modeling have difficulty characterizing complex reservoir geometries and heterogeneous reservoir properties. Taking advantage of deep feedforward neural networks (DFNNs) in nonlinear fitting, this paper compares the reservoir geological modeling results of different methods on the basis of an existing lithofacies model and seismic data from the X area of Karamay, Xinjiang, China. Adopted reservoir geological modeling methods include conventional sequential Gaussian simulation and DFNN-based reservoir geological modeling method. The constrained data in the experiment mainly include logging data, seismic attribute data, and lithofacies model. Then, based on the facies-controlled well-seismic combined reservoir geological modeling method, this paper explores the application of multioutput DFNN and transfer learning in reservoir geological modeling. The results show that the DFNN-based reservoir geological modeling results are closer to the actual model. In DFNN-based reservoir geological modeling, the facies control effect is obvious, and the simulation results have a higher coincidence rate in a test well experiment. The feasibility of applying multioutput DFNN and transfer learning in reservoir geological modeling provides solutions for further optimization methods, such as solving small-sample problems and improving the modeling efficiency. [ABSTRACT FROM AUTHOR]

In this paper, alkyl aliphatic hydrazine, which is different from traditional polymer fluidity improver, was synthesized from aliphatic hydrazine and cetane bromide, and evaluated as a pour point and viscosity-reducer depressant for crude oil. The evaluation results showed that alkyl aliphatic hydrazone fully reduced the pour point and viscosity of crude oil with the increase of crude oil fluidity. The viscosity reduction rate of crude oil in Jinghe oilfield was 79.6%, and the pour point was reduced by about 11.3 °C. The viscosity reduction rate of crude oil in Xinjiang Oilfield was 74.7%, and the pour point was reduced by 8.0 °C. The long alkyl chain is beneficial to the eutectic of wax in crude oil, and the polar group inhibits the crystal growth, resulting in the decrease of pour point and viscosity. The waste oil is fully recycled into oilfield chemicals. [ABSTRACT FROM AUTHOR]

PetroChina's Xinjiang oilfield has a large quantity of tight oil reserves and hydraulic fracturing technology has been widely used to achieve commercial production. Some parts of this tight glutenite formation are laumontite-rich and the actual productivity of the hydraulically fractured wells is less than expected. To figure out the ways that laumontite affects tight glutenite well productivity, comprehensive experimental and numerical simulation studies have been conducted to investigate the rock mechanical properties, fluid flow behaviors and the major controlling factor of productivity. Laboratory results indicate that the tight glutenite formation with higher laumontite content has higher initial porosity, permeability but lower yield strength and more severe stress sensitivity in both permeability and fracture conductivity. For laumontite-rich glutenite rocks, there are commonly three types of rock deformation during the loading process: elastic compression, shear dilation and shear enhanced compaction. Both elastic compression and shear enhanced compaction will cause the reduction on rock porosity and permeability. A fully coupled finite element model (FEM) considering stress-induced permeability evolution was introduced to simulate the production process. Permeability evolution models of three different deformation stages were presented, respectively. Simulation results showed that our model is in good agreements with the well testing data. The simulated oil production characteristics for permeability evolution coupled and uncoupled models were discussed. Results showed the strong stress-induced permeability reduction is the major factor that laumontite causing the low and quickly declining oil rates. Initial permeability has a positive effect on productivity and stress-induced fracture conductivity reduction has slight influence on productivity. The results of this paper indicate that the stress-induced permeability evolution in the oil production process must be considered to accurately evaluating reservoirs in the studied area. [ABSTRACT FROM AUTHOR]

In the future, there will be more and more abandoned oil-gas wells with the exploitation of onshore oilfield resources. However, the large height difference in abandoned oil-gas wells can be used as building blocks for gravity power generation, thus maximizing the economic value of abandoned oil-gas wells. In this study, a scheme of gravity power generation by virtue of the spud-in casing depth of oil-gas wells is proposed, and a gravity power generation model based on abandoned oil-gas wells is established. The parameters and economic benefits of gravity energy storage are calculated for oil-gas wells in the Huabei oilfield, the Daqing oilfield, and the Xinjiang oilfield. It is shown that the power density and discharge time of the gravity energy storage system in abandoned oil-gas wells are suitable for distributed power generation. In addition, the fast response characteristics of energy storage in abandoned oil-gas wells are verified, which makes the system suitable for correcting continuous and sudden frequency and voltage changes in the power grid but not suitable for energy arbitrage under a high number of annual cycles. Furthermore, the leveling cost of storage of the gravity system in abandoned oil-gas wells is more economical with the high number of annual cycles. The analysis of this work provides a significant investigation of the feasibility of gravity power generation by using abandoned oil-gas wells. [ABSTRACT FROM AUTHOR]

The aim of this study was to propose the workflow for integrated analysis of the 3D geostress and 1D geomechanics of an exploration in a new gas field. This integrated analysis will allow for problems associated with the inaccuracy of 1D geomechanical analysis to be overcome in a region with obvious anticline/syncline structures. The 1D geomechanical analysis of the well in the exploration of a new gas field mainly included the prediction of pore pressure and calculation of the mud weight window for safe drilling. In general, this integrated workflow included both a method for pore pressure prediction and a method for the calculation of the mud weight window, with the numerical solution of 3D geostress plus the interval velocity of formations. The procedure for the calculation of the 3D geostress of a target block was also introduced. Numerical solution of the 3D geostress of the target gas field, as well as solutions of 1D geomechanical analysis, have demonstrated the efficiency and practical use of the proposed theory in the successful drilling of the LT-1 well in the Junggar Basin, Xinjiang, China. For this LT-1 well in the target TS block, there was no logging data to refer to when predicting the pore pressure of undrilled formations. Only 3D geostress could be used to calculate the mud weight window. Influences of anticline structures were considered in the calculation of 3D geostress. Since the accuracy of the numerical solution of 3D geostress is higher than the accuracy of the 1D geostress solution for a single well analysis, the results of pore pressure and the mud weight window are more accurate than those obtained with conventional 1D geostress analysis. Details of the finite element modeling of the 3D geostress field of the TS block is presented along with the solution of the 3D geostress field. With the data of the interval velocity of formations and 3D geostress solution of the TS block, pore pressure prediction was carried out for the 7000 m-deep pilot LT-1 well. Finally, calculations were performed for the values of the mud weight window of the LT-1 well. [ABSTRACT FROM AUTHOR]

In the past, reservoir engineers used numerical simulation or reservoir engineering methods to predict oil production, and the accuracy of prediction depended more on the engineers' own experience. With the development of data science, a new trend has arisen to use deep learning to predict oil production from the perspective of data. In this study, a hybrid forecasting model (CNN-LSTM) based on a convolutional neural network (CNN) and a Long Short-Term Memory (LSTM) neural network is proposed and used to predict the production of fractured horizontal wells in volcanic reservoirs. The model solves the limitation of traditional methods that rely on personal experience. First, the production constraints and production data are used to form a feature space, and the abstract semantics of the feature time series are extracted through convolutional neural network, then the LSTM neural network is used to predict the time series. The certain hyperparameters of the whole model are optimized by Particle Swarm Optimization algorithm (PSO). In order to estimate the model, some production dynamics from the Xinjiang oilfield of China are used for comparative analysis. The experimental results show that the CNN-LSTM model is superior to traditional neural networks and conventional decline curves. [ABSTRACT FROM AUTHOR]

Accurate information about the distribution of natural fractures is a key factor for the success of the exploration and development of oil and gas in carbonate rock formations. Forward modeling of natural fractures generated by tectonic movement within carbonate rock formations was investigated by jointly using the continuum damage model and finite element numerical technology. Geological analysis of natural fractures was used as the basis of the geomechanical finite element calculation. A workflow of numerical calculations for natural fractures was proposed. These achievements were applied to investigate natural fractures' distribution within Ordovician carbonate rock formations of the Fuman Oilfield, Xinjiang, in the west of China. Finite element sub-modeling technology was used to further investigate natural fractures within key target reservoir formations with a finer mesh. The contour of natural fractures represented by the localization band of continuum damage variables was obtained. A comparison of the numerical results of the natural fractures' distribution represented by continuum damage variables with those of natural fractures interpreted from seismic data shows that: (1) the numerical solution of natural fractures matches the measured data, and their orientations are in good accordance; (2) their distribution and locations are basically the same, with some small differences in local details; (3) the numerical results indicate that the maximum value of the damage variable SDEG within the zones of natural fractures is 0.2686, and the widths of the bands of natural fractures/faults are in the range of 500 m to 1000 m. Validation of the results of the distribution of natural fractures was performed indirectly via the distribution of the minimum horizontal stress gradient ShG. [ABSTRACT FROM AUTHOR]

China faces a difficult choice of maintaining socioeconomic development and carbon emissions mitigation. Analyzing the decoupling relationship between economic development and carbon emissions and its driving factors from a regional perspective is the key for the Chinese government to achieve the 2030 emission reduction target. This study adopted the logarithmic mean Divisia index (LMDI) method and Tapio index, decomposed the driving forces of the decoupling, and measured the sector's decoupling states from carbon emissions in Xinjiang province, China. The results found that: (1) Xinjiang's carbon emissions increased from 93.34 Mt in 2000 to 468.12 Mt in 2017. Energy-intensive industries were the key body of carbon emissions in Xinjiang. (2) The economic activity effect played the decisive factor to carbon emissions increase, which account for 93.58%, 81.51%, and 58.62% in Xinjiang during 2000–2005, 2005–2010, and 2010–2017, respectively. The energy intensity effect proved the dominant influence for carbon emissions mitigation, which accounted for −22.39% of carbon emissions increase during 2000–2010. (3) Weak decoupling (WD), expansive coupling (EC), expansive negative decoupling (END) and strong negative decoupling (SND) were identified in Xinjiang during 2001 to 2017. Gross domestic product (GDP) per capita elasticity has a major inhibitory effect on the carbon emissions decoupling. Energy intensity elasticity played a major driver to the decoupling in Xinjiang. Most industries have not reached the decoupling state in Xinjiang. Fuel processing, power generation, chemicals, non-ferrous, iron and steel industries mainly shown states of END and EC. On this basis, it is suggested that local governments should adjust the industrial structure, optimize energy consumption structure, and promote energy conservation and emission reduction to tap the potential of carbon emissions mitigation in key sectors. [ABSTRACT FROM AUTHOR]

Low-rank coal samples from the Xishanyao Formation in the southern Junggar basin of Xinjiang were processed under different negative pressures in order to examine the microstructural characteristics of low-rank coal reservoirs. The pore structures of low-rank coal under different negative pressures were tested using scanning electron microscopy, low-temperature nitrogen adsorption–desorption, and water saturation and centrifugal low-field NMR experiments. The results showed that for the low-rank coal samples from the study area, a high portion of the porosity and surface area came from micropores and small pores; the fractal dimension of the adsorption pores of the low-rank coal samples was divided into surface fractal dimension D1 and structural fractal dimension D2, which showed that the microstructure of the low-rank coal from the study area was complex. The transverse relaxation times T2 of the low-rank coal samples in the test were approximately 0.1~2.5, approximately 10, and greater than 100 ms; the T2 spectrum had basically three peak types. By combining scanning electron microscopy and nuclear magnetic resonance tests, it was concluded that the pore connectivity of the low-rank coal reservoirs in the study area was poor and the effective porosity was relatively low, which may be unfavorable for the exploration and development of coalbed methane. [ABSTRACT FROM AUTHOR]

Single well productivity is an important index of oilfield production planning and economic evaluation. Due to fracture-vuggy reservoirs being characteristically strongly heterogeneous and having complex fluid distribution, the commonly used single well productivity prediction methods for fracture-vuggy reservoirs have many problems, such as difficulty in obtaining reservoir parameters and producing large errors in the forecast values of single well productivity. In this paper, based on the triple medium model, the Laplace transform and Duhamel principle are used to obtain the productivity equation of a single well in a fracture-vuggy reservoir. Secondly, the seismic attributes affecting the productivity of a single well are selected using the Spearman and Pearson correlation index calculation method. Finally, the selected seismic attributes are introduced into the productivity equation of the triple medium model through the interporosity flow coefficient and the elastic storativity ratio, and the undetermined coefficients under different karst backgrounds are determined using multiple nonlinear regression. From these, a new method for predicting single well productivity of fracture-vuggy reservoir is established. In order to verify the feasibility of the new method, based on the actual production data of a fracture-vuggy reservoir in Xinjiang, the new single well productivity prediction method is used to predict the productivity of 134 oil wells. The results show that the new productivity prediction method not only reduces calculation workload, but also improves the accuracy of productivity prediction, which contributes to a good foundation for future oilfield development. [ABSTRACT FROM AUTHOR]