A simulation-based method to determine the coefficient of hyperbolic decline curve for tight oil production

 Tight oil reservoirs are characterized by the ultra low porosity and permeability, making it a great challenge to enhance oil production. Owing to the fast development in hydraulic fracturing technology of horizontal wells, tight oil has been widely explored in North America. Individual wells have a long term of low production after a rapid production decline. This causes low cumulative production in tight oil reservoirs. A rate decline curve is the most common method to forecast their production rates. The forecast can provide useful information during decision making on future development of production wells. In this paper, a relationship is developed between the parameters of a hyperbolic decline curve and the reservoir/fracture properties when a reservoir simulation model is used based on the data from a real field. Understanding of this relationship improves the application of the hyperbolic decline curve and provides a useful reference to forecast production performance in a more convenient and efficient way.Cited as: Yu, Y., Chen, Z., Xu, J. A simulation-based method to determine the coefficient of hyperbolic decline curve for tight oil production. Advances in Geo-Energy Research, 2019, 3(4): 375-380, doi: 10.26804/ager.2019.04.0

Review of 70 years’ achievements and high-quality development architecture system of surface coal mining in China

As an important component of China’s coal industry, surface coal mines have the advantages of large production capacity, low mining costs, and great safety conditions. In recent years, surface coal mines in China have achieved a leapfrog development in construction scale, total production, mining technology, and technical equipment, which strongly guarantees the status of coal as the “ballast” for the safe and stable supply of national energy. Firstly, the development process of surface coal mines in China over the past 70 years after the founding of the People’s Republic of China was reviewed, which was divided into four stages: the initial recovery stage (1949−1979), the rapid development stage (1980−1999), the comprehensive development stage (2000−2020), and the intelligent primary development (after 2021). A systematic summary was made for the outstanding achievements made in the production and quantity scale, mining theory and technology, mining technology and equipment, and resource development and environmental protection in each stage. Then, four main problems faced by the development of surface coal mines at the current stage were discussed, including uneven development layout, bottlenecks in sustainable development, key technological problems that need to be deeply researched, and the shortage of talents and imperfect cultivation mechanism. Finally, it was proposed to construct a high-quality development architecture system for surface coal mines with the overall goal of “safe, efficient, green, low carbon and intelligent” in the whole chain, whole cycle and whole elements. Its connotative features include theoretical basis: six academic ideas, i.e. time-dependent slope theory, mining disturbance coefficient theory, green mining theory, ecological mining theory, zero carbon and carbon negative mining theory, and intelligent mining theory; core support: five technical systems, i.e. disaster monitoring and prevention and control, collaborative support in complex conditions, ecological source damage reduction mining, energy conservation, pollution reduction and clean utilization, and digital-automatic-intelligent construction; key breakthroughs: 30 key technologies, i.e. dynamic reconstruction of transparent geological models, accurate prediction of slope creep and slide, deep and large-hole low-disturbance control blasting, advanced detection and disposal of goaf, and dust suppression, spontaneous combustion prevention and control, and so on; construction tasks: “ten transformable type” surface mines with the evolution of design concepts, standardization of safety guarantees, large-scale construction, comprehensive production processes, intelligent mining equipment, localization of core manufacturing, ecological greening of mining areas, clean utilization of coal, scientific organization and management, and internationalization of talent teams. At the same time, the realization path of high-quality development of surface coal mines based on planning guidance, driven by scientific and technological innovation, and guaranteed by talent cultivation was provided. Ultimately, it provides guidance to promote the sustainable, healthy, and high-quality development of surface coal mines in China

Cryopreservation in Ophthalmology

Amniotic membranes (AMs) and corneas are critical materials in ocular surface reconstruction. AM has specific structures (e.g., basement and two types of cells with stemness characteristics: amniotic epithelial cells and amniotic mesenchymal cells), which contribute to its attractive physical and biological properties that make it fundamental to clinical application. The corneal endothelial cell is a vital part of the cornea, which can influence postoperative vision directly. However, widespread use of fresh AM and cornea has been limited due to their short use span and safety concerns. To overcome these concerns, different preservation methods have been introduced. Cryopreservation is distinguished from many preservation methods for its attractive advantages of prolonged use span, optimally retained tissue structure, and minimized infection risk. This review will focus on recent advances of cryopreserved AM and cornea, including different cryopreservation methods and their indications in ophthalmology

Learning Inter- and Intra-frame Representations for Non-Lambertian Photometric Stereo

In this paper, we build a two-stage Convolutional Neural Network (CNN) architecture to construct inter- and intra-frame representations based on an arbitrary number of images captured under different light directions, performing accurate normal estimation of non-Lambertian objects. We experimentally investigate numerous network design alternatives for identifying the optimal scheme to deploy inter-frame and intra-frame feature extraction modules for the photometric stereo problem. Moreover, we propose to utilize the easily obtained object mask for eliminating adverse interference from invalid background regions in intra-frame spatial convolutions, thus effectively improve the accuracy of normal estimation for surfaces made of dark materials or with cast shadows. Experimental results demonstrate that proposed masked two-stage photometric stereo CNN model (MT-PS-CNN) performs favorably against state-of-the-art photometric stereo techniques in terms of both accuracy and efficiency. In addition, the proposed method is capable of predicting accurate and rich surface normal details for non-Lambertian objects of complex geometry and performs stably given inputs captured in both sparse and dense lighting distributions.Comment: 9 pages,8 figure

Exceptional point-based ultrasensitive surface acoustic wave gas sensor

Exceptional points (EPs) refer to degeneracies in non-Hermitian systems where two or more eigenvalues and their corresponding eigenvectors coalesce. Recently, there has been growing interest in harnessing EPs to enhance the responsivity of sensors. Significant improvements in the sensitivity of sensors in optics and electronics have been developed. In this work, we present a novel ultrasensitive surface acoustic wave (SAW) gas sensor based on EP. We demonstrate its ability to significantly respond to trace amount of hydrogen sulfide (H2S) gas by tuning additional loss to approach the EP, thereby enhancing the responsivity compared to the conventional delay line gas sensors. In addition to high sensitivity, our sensor is robust to temperature variation and exclusive to H2S gas. We propose an innovative method for designing a new generation of ultrasensitive gas sensor

Efficient and durable uranium extraction from uranium mine tailings seepage water via a photoelectrochemical method

Current photocatalytic uranium (U) extraction methods have intrinsic obstacles, such as the recombination of charge carriers, and the deactivation of catalysts by extracted U. Here we show that, by applying a bias potential on the photocatalyst, the photoelectrochemical (PEC) method can address these limitations. We demonstrate that, owing to efficient spatial charge-carriers separation driven by the applied bias, the PEC method enables efficient and durable U extraction. The effects of multiple operation conditions are investigated. The U extraction proceeds via single-step one-electron reduction, resulting in the formation of pentavalent U, which can facilitate future studies on this often-overlooked U species. In real seepage water the PEC method achieves an extraction capacity of 0.67 gU m(-3).h(-1) without deactivation for 156 h continuous operation, which is 17 times faster than the photocatalytic method. This work provides an alternative tool for U resource recovery and facilitates future studies on U(V) chemistry