China Block Research Articles

Application of OVT Domain Processing Technology in 3D Seismic Exploration of Coalbed Methane in Heshun Hengling Block

This study introduces the OVT (Offset Vector Tile) domain processing technology to improve the accuracy of small structure detection in 3D seismic exploration of coalbed methane in the Heshun-Hengling block in China. The OVT technology optimizes wide azimuth seismic data processing through steps such as facet division, five-dimensional regularization, pre-stack time migration, and azimuthal anisotropy correction. The results show that OVT processing retains azimuth information, enhancing the ability to reflect stratum changes with azimuth; azimuthal anisotropy correction improves the resolution of the profile. The profile after OVT processing has a natural waveform, good continuity of the phase axis, and a wide frequency band, meeting the requirements of the “Coalbed Methane Seismic Exploration Specification”. It demonstrates the advantages of OVT technology in imaging complex geological structures, providing a new perspective for seismic exploration.

Utilization law of shale gas in hydraulic fracturing with the Changning–Weyuan block in China as an example

The process of extracting shale gas, particularly the study of the utilization law of shale reservoirs modified by hydraulic fracturing technology, is crucial for understanding the effective development of shale gas. This understanding can significantly influence the estimated ultimate recovery of reserves. Our study focused on Longmaxi Formation shale in the Changning–Weiyuan block. To investigate the hydraulic fracturing expansion mechanism and utilization law, we employed shale reservoir physical and mechanical characterization, indoor triaxial hydraulic fracturing experiments, and numerical simulations. The findings are as follows. The rupture pressure of hydraulic fractures increases with the peripheral pressure, and high stress is conducive to the formation of internal microfractures. Additionally, a high rate of water injection enhances fracture extensions along the direction of fluid injection. Under varying injection pressures, the length of crack extensions and number of bond damages in shale are positively correlated with the injection pressure. Conversely, under different differential ground stresses, the length of crack extensions and number of bond damages are negatively correlated with the injection pressure. The six main factors affecting the effective utilization of shale gas are as follows: the stimulated reservoir volume, number of hydraulic fracture clusters, fracture length, fracture height, number of fracture stages, and cluster spacing, accounting for 27.13%, 14.74%, 10.31%, 9.58%, 9.53%, and 9.29%, respectively, with a cumulative contribution rate of 80.58%. This study clarifies the hydraulic fracturing mechanisms of shale reservoirs and the laws governing shale gas production, providing technical support for the development of shale gas reservoirs.

Interdependence of heterogeneous blockholders: Evidence from China

The co-holding of interdependent pairs of heterogeneous blocks can provide firms with stable financial support. The interdependence of heterogeneous blockholders’ investment decision has become an important frontier in the financial literature on large shareholders. In this paper, we study the interdependence of heterogeneous blocks in China. We find significant positive interdependence among blockholders of the same type. In heterogeneous block pairs, the financial–private pair shows positive interdependence. The findings are in contrast to those observed in the US. Under the mixed-ownership reform in China, our findings suggest the potential for cooperation among multiple blocks of the same type rather than between heterogeneous strategic partners.

CH4 and CO2 Emissions From Different Tectonic Settings Along the Western Margin of the Ordos Block in China: Output and Correlation With the Regional Tectonics

AbstractThe investigation of tectonic controls on CH4 and CO2 emissions was conducted by measuring the fluxes of the gases in the different tectonic units along the northwestern margin of the Ordos Block in China, a region renowned for its intricate tectonic configuration. The mean fluxes of CH4 ranged from −1.5 to 1.1 mg m−2 d−1, while CO2 fluxes spanned from 2.0 to 29.2 g m−2 d−1. Notably, the Minqin, Ordos, and Haiyuan blocks primarily exhibited absorption characteristics for CH4. In contrast, within the Hetao and Yinchuan grabens, both degassing and absorption processes coexist. A striking observation was that blocks with high internal deformation exhibited significantly higher CH4 and CO2 fluxes compared to those in the stable blocks. Additionally, regions experiencing extensional deformation demonstrated greater gas emission than those undergoing compressional deformation. The spatial distribution of CH4 and CO2 fluxes at the study points exhibited a similar trend to faults in the Yinchuan Graben. Our findings revealed that CH4 and CO2 are mainly of biogenic origin, accompanied by abiotic emissions from underground. And the gas source, migration pathway, and tectonic stress were the primary factors influencing gas emission, with tectonic stress playing a pivotal role. This stress controlled the formation of tectonic structures, changed the degassing pathway, and served as the driving force for gas migration. The results of this study offer valuable insights into the mechanisms governing CH4 and CO2 emission in faulted regions. Furthermore, our results may contribute to future assessments aimed at quantifying the contribution of geological sources to greenhouse gas emissions.

A novel domain adaptation method with physical constraints for shale gas production forecasting

Effective forecasting of shale gas production is essential for optimizing exploration strategies and guiding subsequent fracturing. However, in the new development of shale gas blocks, two main challenges are encountered: (1) data is insufficient, and (2) the dynamic production characteristics of shale gas wells, influenced by factors such as reservoirs and engineering, exhibit complex non-linear and non-stationary features. The inherent black-box nature of deep learning models raises concerns among decision-makers about the reliability of results. The current artificial intelligence model overlooks these factors, resulting in limitations in the accuracy and interpretability of the model. To address these problems, a novel domain adaptation methodology is proposed using physical constraints. First, production data from the source domain is segmented into multiple subdomains to enhance sample diversity. Subsequently, the positive transfer learning subdomains are identified by comparing maximum mean discrepancy (MMD) and global average distance metrics. Then, we integrate all transferable knowledge to create a more comprehensive target model. Finally, by incorporating drilling, completion, and geological data as physical constraints, we develop a hybrid model consisting of a multi-layer perceptron (MLP) and a Transformer, aiming to maximize interpretability, which is proved through comparison of symbolic transfer entropy (STE). The performance of the proposed method is experimentally validated on shale gas production data from two blocks in China. The average RMSE, MAE, and R2 on the target domain are 0.2454 (104 m3/d), 0.1552 (104 m3/d), and 0.88, respectively. These values are significantly superior to the traditional methods. Additionally, we demonstrate the superiority of our method in terms of causality through a comparison with Granger causality. The interpretability of static and dynamic data in the prediction process was studied using zero-value masking and attention mechanisms, respectively. Experimental results demonstrate the effectiveness and superiority of the proposed method for forecasting shale gas production under data insufficiency.

Empirical Analysis on Influence of Authenticity Perception on Tourist Loyalty in Historical Blocks in China

Tourist loyalty is the key to the sustainable development of tourism in urban historical blocks. This article focuses on exploring the relationship between authenticity perception and tourist loyalty in this context. With this aim, we introduce the mediating variable of tourist engagement and construct a theoretical model of authenticity perception, tourist engagement, and tourist loyalty. Hierarchical regression analysis and bootstrapping were performed on questionnaire data of 287 West Street tourists in Dujiangyan, China. The results of this study demonstrate that both object-related authenticity perception and existential authenticity perception have a significant positive impact on tourist loyalty behavior, with similar degrees of influence. Additionally, the study reveals that tourist engagement plays a mediating role in the relationship among object-related authenticity, existential authenticity, and tourist loyalty. From the perspective of tourist engagement, this article reveals the impact mechanism of authenticity perception on tourist loyalty in the context of historical block tourism, enriches the research on tourism authenticity, and deepens the understanding of tourist loyalty behavior. Furthermore, the results of this study also provide reference for the formulation of sustainable development policies related to tourism in historical blocks.

Bibliometric Analysis of Historical Block Renewal Research at Home and Abroad based on the Scientific Knowledge Map

The renewal of historical blocks plays an extremely important role in the process of urbanization. However, there are few studies focus on the time distribution of the relevant literature corresponding to the renewal of historical blocks and cannot provide a more cutting-edge opinion conclusion. Therefore, this study aims to explore the law of time distribution in the literature study the renewal of historical blocks. This paper uses the scientific knowledge mapping software CiteSpace to systematically visualize the scientific literature in the field of historical block renewal and its many related fields. To start with, the bibliometric analysis of historical block renewal is carried out. This paper makes a bibliometric analysis of the time distribution, keyword distribution, literature release time, mutation keywords, author density, author network, and other data. This paper finds that the literature in the field of historical district renewal in CSSCI and Peking University core journals has been studied more rapidly in the past decade than in previous years. The increase in the number of papers has increased sharply, and the research hotspots have focused on organic renewal and functional replacement. Among them, micro-renewal, place spirit, and industrial sites are the most concerned frontiers. Based on the above results, this paper summarizes the development trend of the main cutting-edge technologies of the renewal of historical blocks and puts forward relevant suggestions for the development of the renewal field of historical blocks in China.

Research and Application of Carbon Capture, Utilization, and Storage–Enhanced Oil Recovery Reservoir Screening Criteria and Method for Continental Reservoirs in China

CCUS-EOR is a crucial technology for reducing carbon emissions and enhancing reservoir recovery. It enables the achievement of dual objectives: improving economic efficiency and protecting the environment. To explore a set of CCUS-EOR reservoir screening criteria suitable for continental reservoirs in China, this study investigated and compared the CCUS-EOR reservoir screening criteria outside and in China, sorted out the main reservoir parameters that affect CO2 flooding, and optimized the indices and scope of CCUS-EOR reservoir screening criteria in China. The weights of parameters with respect to their influences on CCUS-EOR were determined through principal component analysis. The results show that there are 14 key parameters affecting CO2 flooding, which can be categorized into four levels. For the first level, the crude oil-CO2 miscibility index holds the greatest weight of 0.479. It encompasses seven parameters: initial formation pressure, current formation pressure, temperature, depth, C2–C15 molar content, residual oil saturation, and minimum miscibility pressure. The second level consists of the crude oil mobility index, which has a weight of 0.249. This index includes four parameters: porosity, permeability, density, and viscosity. The third level pertains to the index of reservoir tectonic characteristics, with a weight of 0.141. It comprises two parameters: permeability variation coefficient and average effective thickness. Lastly, the fourth level focuses on the index of reservoir property change, with a weight of 0.131, which solely considers the pressure maintenance level. Based on the CCUS-EOR reservoir screening criteria and index weights established in this study, comprehensive scores for CCUS-EOR were calculated for six blocks in China. Among these, five blocks are deemed suitable for CCUS-EOR. Based on the comprehensive scoring results, a planning for field application of CCUS-EOR is proposed. The study provides a rational method to evaluate the CCUS-EOR reservoir screening and field application in continental reservoirs in China.

A shale gas production prediction model based on masked convolutional neural network

Shale gas production prediction is of great significance for shale gas exploration and development, as it can optimize exploration strategies and guide adjustments to production parameters for both new and existing wells. However, the dynamic production characteristics of shale gas wells under the influence of multiple factors such as reservoirs, engineering, and production, exhibit complex nonlinear and non-stationary features, leading to low accuracy in predicting shale gas production. To address this issue, a novel masked convolutional neural network (M-CNN) based on masked autoencoders (MAE) is proposed for shale gas production prediction. First, high-dimensional shale gas production data are transformed into images with unknown information using an encoding structure, thereby converting the regression task into images generation task. Then, convolutional neural network is used for image restoration prediction, and the corresponding numerical values at the image positions are extracted as shale gas production prediction results. Specifically, dilated convolution and multi-scale residual structure (MSRS) are developed to improve the feature representation capability of the network. Meanwhile, convolutional block attention module (CBAM) is adopted to enhance the feature extraction ability of the M-CNN. The performance of our method is validated experimentally on shale gas production data of Changning (CN) block in China. The average RMSE, MRE, and R2 on the test sets are 0.211 (104m3/d), 10.9%, and 0.906, respectively, which is much lower than the traditional time series models. Experimental results demonstrate the effectiveness and superiority of the proposed M-CNN method for shale gas production prediction.

Spatiotemporal characteristics of upper-crust seasonal velocity changes in North–South Seismic Belt and South China block in China

Investigating mechanisms and characteristics of the non-tectonic deformation has crucial implications for evaluating the subsurface stress evolution. In this study, we continuously tracked the seasonal velocity changes of Rayleigh wave at 2–10 s with the ambient noise interferometry and discrete wavelet decomposition, in different regions along the actively deforming North–South Seismic Belt (NSSB) and the stable Guangdong region in the South China block in China. The seasonal velocity changes exhibit strong lateral variations across different regions, with much larger seasonality (annual periodicity) and amplitude along the NSSB than those in the stable Guangdong region. There are also small-scale lateral variations inside of each region and generally larger amplitudes of the seasonal velocity changes at greater depth, but the phases (peaks, mostly in winter or summer) at different depths are consistent. The mechanism of the seasonal changes is most likely the direct loading effect of the precipitation, as indicated by consistency in their phases. However, the amplitudes of the seasonal velocity changes seem not controlled by the amount of precipitation, but are more dependent on the tectonic deformation at the different scales, from the correlation between the amplitude of the velocity change and the absolute strain rate. We demonstrate that the crustal media in the regions with larger tectonic background stress are more sensitive to the seasonal loadings. The new finding also highlights the role of the external seasonal loadings in the modulation of seismic activities and risk evaluations. Keypoints•Seasonal seismic velocity variations are found in different regions in China, likely from direct hydrological loadings of precipitation.•The spatial pattern of the seasonal velocity changes is consistent with the distribution of tectonic deformation at multi-scales.•The amplitude of the seasonal velocity changes is more dependent on the magnitude of local deformation than the amount of precipitation.

USTC-Pickers: a Unified Set of seismic phase pickers Transfer learned for China

Current popular deep learning seismic phase pickers like PhaseNet and EQTransformer suffer from performance drop in China. To mitigate this problem, we build a unified set of customized seismic phase pickers for different levels of use in China. We first train a base picker with the recently released DiTing dataset using the same U-Net architecture as PhaseNet. This base picker significantly outperforms the original PhaseNet and is generally suitable for entire China. Then, using different subsets of the DiTing data, we fine-tune the base picker to better adapt to different regions. In total, we provide 5 pickers for major tectonic blocks in China, 33 pickers for provincial-level administrative regions, and 2 special pickers for the Capital area and the China Seismic Experimental Site. These pickers show improved performance in respective regions which they are customized for. They can be either directly integrated into national or regional seismic network operation or used as base models for further refinement for specific datasets. We anticipate that this picker set will facilitate earthquake monitoring in China.

The Mechanism of Casing Deformation before Hydraulic Fracturing and Mitigation Measures in Shale Gas Horizontal Wells

During the development of shale gas, one of the major challenges is the casing deformation (CD) in the horizontal section due to the geological activity. Recently, the casing deformation before hydraulic fracturing (CDBF) occurred in multiple shale gas wells in L block in China. In this paper, based on the theory of tubular mechanics, the relationship between casing buckling and CDBF caused by casing running in is analyzed qualitatively and quantitatively. It is found that the buckling deformation caused by running the casing string process is not sufficient to prevent the tool (Φ99 mm bridge plug). On the other hand, the mechanism of CDBF is systematically analyzed based on the actual field data and finite element (FE) method. In order to analyze the CDBF mechanism, the comparison between the actual casing trajectory and the reservoir rock (S#1, S#2, S#3 and M#1) in horizontal section in H2 platform is carried out, and the preliminary CDBF mechanism is proposed. Then, two groups of FE models are established to reduce the CD process to verify the preliminary mechanism. It is found that the numerical simulation results (high stress section length from FE model) are in good agreement with the actual CD logging results. Based on the analytical results, the corresponding mitigation measures are proposed based on the analysis of the CDBF mechanism. Our work could offer a detailed theoretical basis and reference of CDBF for shale gas well application.

Research on Urban Historical Block Planning Method Based on Big Data Multimedia Technology

With the application and popularization of big data technology, it is more advantageous than traditional urban planning to use big data multimedia technology to reasonably plan the historical blocks of the city. The protection and renewal of historical and cultural blocks have become the core elements to improve the quality of urban development and promote the development of “people-oriented” new urbanization. We analyze and study the planning methods of urban historical blocks under the big data technology. This paper analyzes the different values of historical blocks. By comparing the division effect and business operation mode of historical blocks under different technological environments, it is concluded that the efficiency of traditional data survey and statistical mode is faster than that of big data multimedia technology, and it is more accurate and efficient in analyzing and studying the commercial market and tourism development planning of historical blocks. Through big data multimedia technology data query, we have mastered the cultural connotation of the historical district, protected the historical environment, excavated the historical culture, activated the vitality of the district, and optimized the district environment. It provides convenient scientific and technological means for the protection and development planning of cultural heritage such as historical blocks in China.

Two-Decade GNSS Observation Processing and Analysis with the New IGS Repro3 Criteria: Implications for the Refinement of Velocity Field and Deformation Field in Continental China

Extensive observation collection, unified and rigorous data processing, and accurate construction of the station motion model are the three essential elements for the accuracy and reliability of the Global Navigation Satellite System (GNSS) velocity field. GNSS data reprocessing not only can weaken the influence of untrue nonlinear site signals caused by imperfect models but also can eliminate the displacement offset caused by frame transformation, solution strategy, and model change. Based on the new repro3 criteria of the International GNSS Service (IGS), we process rigorously GNSS observations of continental China from the period 2000 to 2020 to refine GNSS station secular velocities and analyze the present-day crustal deformation in continental China. The main contributions of this work included the followings. Firstly, the repro3 algorithm and model are used to uniformly and rigorously process the two-decade GNSS historical observations to obtain more reliable GNSS coordinate time series with mm-level precision. Combined with the historical records of major earthquakes in continental China, we build a GNSS time series model considering nonlinear factors (velocity, offset, period, co-seismic/post-seismic deformation) to extract GNSS horizontal velocity field whose root mean square (RMS) mean is 0.1 mm/a. Secondly, the GNSS horizontal grid velocity field in continental China is interpolated using the gpsgridder method (the minimum radius is set to 16, and the Poisson’s ratio is set to 0.5). Estimation and analysis of the crustal strain rate solution lead to the conclusion that the strain degree in West China (the high strain region is mainly located in the Qinghai Tibet Plateau and Tianshan Mountains) is much more intense than that in the east (the main strain rate is less than 5 nstrain/year). In addition, most strong earthquakes in the Chinese mainland occurred on active blocks and their boundary faults with large changes in the GNSS velocity field and strain field. Then, an improved K-means++ clustering analysis method is proposed to divide active blocks using GNSS horizontal velocity field. Furthermore, different relative motion models of different blocks are constructed using the block division results. Among them, the Eurasian block has the lowest accuracy (the RMS of residual velocity in the east and north directions are 5.60 and 9.65 mm/a, respectively), and the China block 7 has the highest accuracy (the RMS mean of relative velocity in the east and north directions are 2.60 and 2.65 mm/a, respectively). More observations (2260+ sites), longer time (20 years), and updated criteria (Repro3) are to finely obtain the GNSS velocity field in continental China, and depict crustal deformation and active block with the gpsgridder and improved K-means++ methods.

Experimental Research of Compound Monitoring on Multiple Temporary Blocking Refracturing for Long-Section Horizontal Wells

As an important energy replacement block in China, the tight conglomerate oilfields in the Mahu area are difficult to develop and are characterized by strong heterogeneity, large horizontal stress differences, and undeveloped natural fractures. However, new development processes including temporary blocking diversion and large section-multiple clusters have been implemented on the oilfields in the past few years. In 2020, two adjacent horizontal wells in the MD well area experienced a poor fracturing development effect compared with the earlier wells in this area. Analysis suggests that the main reasons are water sensitivity of the reservoir, insufficient fracturing scale, and/or interference from the adjacent old wells. To ameliorate the problem, this study presents an experimental study of multiple temporary plugging and refracturing technology in long horizontal well sections, in combination with electromagnetic and microseismic monitoring. Results from the study show a great difference between the two monitoring techniques, which is attributed to their different detection principles. Interestingly, the combination of the two approaches provides a greater performance than either approach alone. As the fracturing fluid flow diversion is based on temporary plugging diversion and electromagnetic monitoring of fracturing fluid is advantageous in temporary plugging diversion monitoring, both approaches require further research and development to address complex situations such as multiple temporary plugging and refracturing in long intervals of adjacent older wells.

Development, Application and Effect Evaluation of the Remote-controlled Automated Needle Valve Intermittent Production System in the L Well Block in China

In order to solve the problem of liquid loading, some water-produced gas wells use intermittent production mode to produce: shut in gas wells to restore energy during the closing phase, and open up to carry the liquid to surface by the high velocity gas during well opening phase, which is cost effective. However, some wells need frequent opening and closing or adjusting gas flow, manual opening and closing is easily influenced by external interference factors (road conditions, weather, public relation issue, etc.), and cannot guarantee production time for intermittent producing well. In order to realize the remote-control and automation for these wells, the remote-control automated needle valve intermittent production system was developed and successfully applied to the L well block. The gas rate, production time and economy before and after the smart needle valve installed was compared to do the performance assessment. The results show that: (1) the stability of the remote-control automated needle valve intermittent production system is good, and it can meet the requirments of the remote automated opening and closing of gas wells. (2) After the installation of the remote-controlled automated needle valve system, 71% of the gas wells have a stable gas increase, 100% of the gas wells have a higher well opening time, and the liquid unloading in the gas wells has been significantly improved. The average gas production increased from 1.75×10⁴ m³/d to 1.87×10⁴ m³/d, which was 6.86% higher than that before installation. The well opening time of 7 wells increased by 5.16% on average. (3) Compared with manual operation, the comprehensive economic performance of the remote-controlled automated needle valve opening system is more excellent. The remote-controlled automated needle valve opening system can remotely intelligently control the intermittent production of gas wells, which has significant economic benefits and high application value and worth further spreading.

Daily production prediction for coalbed methane based on Bayesian temporal matrix factorization

Effective and accurate daily production prediction of coalbed methane (CBM) is significant for enhancing CBM recovery and developing economic evaluations of CBM exploitation. As production time increases, CBM well data gradually show some characteristics of big data and is susceptible to incomplete data and noise data. Traditional geological modeling, however, requires a variety of input factors. In the present study, we apply a time series analysis method based on Bayesian temporal matrix factorization (BTMF) without the deletion of exceptional values to investigate the characteristics of CBM development. In addition, different from the widely used data preprocessing, we innovatively scale the multidimensional data to accomplish the analysis and prediction of different attributive data. By studying the temporal and attributive characteristics of the CBM production curve, the model is applied to a CBM block in China to impute the production data and perform a multi-step rolling prediction of daily gas production.Evaluation metrics, including the mean absolute percentage error (MAPE) and the root mean square error (RMSE), are applied to evaluate the performance. It is found that the imputation by the application of BTMF achieves highly satisfactory estimates (in all tested CBM wells, the maximum MAPE and RMSE are 0.1182 and 245.5882, respectively) and is comparable to the other factorization models. Results also show that BTMF is able to account for the variance in gas production with different multi-step rolling predictions and different predicting scenarios, with the MAPE matrix of five CBM wells of different predicting strategies varies from 0.051 to 0.208, 0.121 to 0.307, 0.099 to 0.221, 0.062 to 0.224 and 0.054 to 0.135, respectively. Because of the similar mechanisms of CBM development, this method can provide a reference for predicting the daily gas production of other CBM wells.

Investigation of typical residential block typologies and their impact on pedestrian-level microclimate in summers in Nanjing, China

The morphology of urban residential blocks in China, which is strictly affected by regulations, can potentially improve or deteriorate microclimates. This paper first proposes a framework for identifying typical residential block typologies using Nanjing as an example. A thorough investigation, consisting of 114 samples, was conducted, and 18 typical residential block typologies were summarized. Second, 3D non-isothermal numerical simulations were performed on the hottest days of summer using the ENVI-met. The effect of morphological indices on the microclimate at the pedestrian level was explored using statistical methods and a novel graphic method named m-SpaceMate. The results revealed a strong correlation between the urban heat island intensity (UHII), mean radiation temperature, and universal thermal climate index (UTCI) and floor area ratio (FAR), as well as between wind velocity (U) and building coverage ratio (BCR). A significant increase in FAR (by approximately 1.0) can result in a low UTCI that was driven by MRT and shading conditions. Six-floor blocks, with FAR between 1.8 and 2.1, had a better overall thermal environment (except for lower U) than that of 11-floor blocks. When considering a similar BCR, blocks with slab-type buildings tended to have a U that was higher by approximately 30%.

A morphology-based evaluation on block-scale solar potential for residential area in central China

Block-scale application of photovoltaic technology in city is becoming a viable solution for renewable energy utilization. Rapid urbanization process has made urban buildings have huge development potential for solar energy in China, especially in residential areas that occupy large parts of the city. However, the residential blocks in China show differences in the morphological layout and parameters, which means they have diverse potential for solar energy development. This paper studies the effect of quantified morphological parameters on solar potential for residential blocks in Wuhan, China. The distribution characteristics of solar potential in different block environments are discussed. Various strategies are evaluated in terms of the installation position and height of PV modules. The results showed that floor area ratio, building density, average building height and building interval have significant impact on solar potential for residential block, and their correlation can reach 75%, 71%, 78% and 72% respectively. The average PV installation ratio of roof, south facade and west facade can reach 96%, 32% and 39% respectively. The results of this paper not only provide a reference to the block-scale application of PV technology in urban environment, but also stimulate the implementation of photovoltaic policies on various residential blocks in China.

Enrichment of Platinum Group Elements in Lower Cambrian Polymetallic Black Shale, SE Yangtze Block, China

Platinum group elements (PGEs) occur mainly in basic–ultrabasic igneous rocks and are concentrated by the differentiation and crystallization of magma. Thin polymetallic layers including Ni, Mo, V, PGEs, and rare-earth elements are widely developed in lower Cambrian black shales in southern China. The PGE contents in such layers may not be economically significant but are still unusually enriched. PGE enrichment mechanisms have not been widely studied, but here the PGE compositions of polymetallic layers in the Shuidong (Nayong) and Niuchang (Weng’an) sections of the SE Yangtze block in China were determined, and results compared with published data for the region. Results indicate that PGEs are enriched in the polymetallic layers, whereas the surrounding country rocks are barren. The ΣPGE contents in the Shuidong Ni–Mo deposits are generally lower than in the Niuchang V deposits. PGE distribution patterns in the polymetallic layers are similar to those in basic–ultrabasic rocks, indicating that such rocks played a role in the PGE enrichment. Oceanic hypoxia during the Sinian–Cambrian transition resulted in the production of large amounts of organic matter and H2S in the ocean. When high-salinity brine reached the ocean bottom, rapid changes in Eh–pH conditions caused enrichment of metals at the sediment–seawater interface, and this enrichment was later enhanced during diagenesis.