Intelligent modeling with physics-informed machine learning for petroleum engineering problems

The advancement in big data and artificial intelligence has enabled a novel exploration mode for the study of petroleum engineering. Unlike theory-based solution methods, the data-driven intelligent approaches demonstrate superior flexibility, computational efficiency and accuracy for dealing with complex multi-scale, and multi-physics problems. However, these intelligent models often disregard physical laws in pursuit of error minimization, which leads to certain uncertainties. Therefore, physics-informed machine learning approaches have been developed based on data, guided by physics, and supported by machine learning models. This study summarizes four embedding mechanisms for introducing physical information into machine learning models, including input databased embedding, model architecture-based embedding, loss function-based embedding, and model optimization-based embedding mechanism. These “data + physics” dualdriven intelligent models not only exhibit higher prediction accuracy while adhering to physic laws, but also accelerate the convergence to improve computational efficiency. This paradigm will facilitate the guide developments in solving petroleum engineering problems toward a more comprehensive and efficient direction.Cited as: Xie, C., Du, S., Wang, J., Lao, J., Song, H. Intelligent modeling with physics-informed machine learning for petroleum engineering problems. Advances in Geo-Energy Research, 2023, 8(2): 71-75. https://doi.org/10.46690/ager.2023.05.0

Diagenesis and reservoir quality of Neoproterozoic dolomitized microbialites following multi-stage diagenetic fluid activity: a case study of the Sinian Dengying Formation, China

Neoproterozoic marine microbialites have been targets for exploration and hydrocarbon reservoir development. The original depositional fabric and diagenesis control the pore systems of microbialites, leading to the complicated origin of microbialite reservoirs. This study aimed to reveal the origin of microbialite reservoirs following multi-stage diagenetic fluid activity in the fourth Member of the Dengying Formation in the central Sichuan Basin in southwestern China. The fourth Member of the Sinian Dengying Formation developed dolomitized microbialites, mainly including stromatolites, laminates, and thrombolites. Based on the background of tectonic movement, petrology and geochemistry examinations were executed to analyze the origin of the microbialite reservoir. Based on the cathodoluminescence and the homogenization temperature of the brine inclusions, it is credible that there were four stages of diagenetic fluid activities in the burial diagenesis. In the first stage, the microbialite reservoir was charged by oil in the Silurian period, with evidence from residual asphalt around the pores. In the second stage, dolomite precipitated to incompletely fill the pore spaces. In the third stage, the silica-rich diagenetic fluid with high temperature resulted in the precipitation of authigenic quartz. In the last stage, the oil charged again during the Triassic period, followed by siliceous filling, with residual asphalt filling the pore spaces. There were two stages of subaerial emergence, which occurred in two episodes of the Sinian-Early Cambrian Tongwan movement. The evidence for the two tectonic events includes two phases of dolomites with meteoric water origin, two cycles of V, Sr, and Na element profiles, two instances of negative excursion δ18O isotope, and two cavity layers. By comparison, the karstification of reservoirs in the Tongwan III episode could generate a higher quality of reservoir than that in the Tongwan II episode. As a result, the quality of the microbialite reservoir from the fourth Member of the Dengying Formation was mainly improved by the subaerial exposure in the Tongwan III episode and then was partly destroyed by the siliceous filling. The identification of multi-staged diagenetic fluid charging can illustrate the evolution of the reservoir quality of Neoproterozoic microbialites

Exploring Shape Embedding for Cloth-Changing Person Re-Identification via 2D-3D Correspondences

Cloth-Changing Person Re-Identification (CC-ReID) is a common and realistic problem since fashion constantly changes over time and people's aesthetic preferences are not set in stone. While most existing cloth-changing ReID methods focus on learning cloth-agnostic identity representations from coarse semantic cues (e.g. silhouettes and part segmentation maps), they neglect the continuous shape distributions at the pixel level. In this paper, we propose Continuous Surface Correspondence Learning (CSCL), a new shape embedding paradigm for cloth-changing ReID. CSCL establishes continuous correspondences between a 2D image plane and a canonical 3D body surface via pixel-to-vertex classification, which naturally aligns a person image to the surface of a 3D human model and simultaneously obtains pixel-wise surface embeddings. We further extract fine-grained shape features from the learned surface embeddings and then integrate them with global RGB features via a carefully designed cross-modality fusion module. The shape embedding paradigm based on 2D-3D correspondences remarkably enhances the model's global understanding of human body shape. To promote the study of ReID under clothing change, we construct 3D Dense Persons (DP3D), which is the first large-scale cloth-changing ReID dataset that provides densely annotated 2D-3D correspondences and a precise 3D mesh for each person image, while containing diverse cloth-changing cases over all four seasons. Experiments on both cloth-changing and cloth-consistent ReID benchmarks validate the effectiveness of our method.Comment: Accepted by ACM MM 202

A bibliometrics analysis and visualization of autism spectrum disorder

BackgroundThe prevalence of autism spectrum disorder (ASD) increased rapidly in the last 20 years. Although related research has developed rapidly, little is known about its etiology, diagnostic marker, or drug treatment, which forces researchers to review and summarize its development process and look for the future development direction.MethodsWe used bibliometrics to analyze papers of ASD in the Web of Science from 1998 to 2021, to draw the network of authors, institutions, countries, and keywords in the ASD field, and visualize the results.ResultsA total of 40,597 papers were included with a continually increasing trend. It turns out that the research on ASD is mainly concentrated in universities. The United States has the largest number of ASD studies, followed by England and Canada. The quality of papers related to ASD is generally high, which shows that ASD research has become a hot spot of scientific research. The keywords of ASD etiology and diagnostic markers can be classified into at least 7 aspects. The detection of keywords shows that ASD research is mostly based on its subtypes, takes children as the study population, focuses on neurodevelopmental imaging or genetics, and pays attention to individual differences. And ASD research has changed greatly under the impact of Corona Virus Disease 2019 in the past 2 years.ConclusionWe consider the future development direction should be based on the improvement of case identification, accurate clinical phenotype, large-scale cohort study, the discovery of ASD etiology and diagnostic markers, drug randomized controlled trials, and telehealth

Integrated analysis identifies microRNA-195 as a suppressor of Hippo-YAP pathway in colorectal cancer

Figure S2. KEGG cell signaling pathway was shown for HIPPO pathway. The most significantly enriched by the predicted targets of miR-195 (P = 6.47E-05). Red frame shows the predicted miR-195 targets. (TIF 83 kb

Nutlin-3 overcomes arsenic trioxide resistance and tumor metastasis mediated by mutant p53 in Hepatocellular Carcinoma

Background: Arsenic trioxide has been demonstrated as an effective anti-cancer drug against leukemia and solid tumors both in vitro and in vivo. However, recent phase II trials demonstrated that single agent arsenic trioxide was poorly effective against hepatocellular carcinoma (HCC), which might be due to drug resistance. Methods: Mutation detection of p53 gene in arsenic trioxide resistant HCC cell lines was performed. The therapeutic effects of arsenic trioxide and Nutlin-3 on HCC were evaluated both in vitro and in vivo. A series of experiments including MTT, apoptosis assays, co-Immunoprecipitation, siRNA transfection, lentiviral infection, cell migration, invasion, and epithelial-mesenchy-mal transition (EMT) assays were performed to investigate the underlying mechanisms. Results: The acquisition of p53 mutation contributed to arsenic trioxide resistance and enhanced metastatic potential of HCC cells. Mutant p53 (Mutp53) silence could re-sensitize HCC resistant cells to arsenic trioxide and inhibit the metastatic activities, while mutp53 overexpression showed the opposite effects. Neither arsenic trioxide nor Nutlin-3 could exhibit obvious effects against arsenic trioxide resistant HCC cells, while combination of them showed significant effects. Nutlin-3 can not only increase the intracellular arsenicals through inhibition of p-gp but also promote the p73 activation and mutp53 degradation mediated by arsenic trioxide. In vivo experiments indicated that Nutlin-3 can potentiate the antitumor activities of arsenic trioxide in an orthotopic hepatic tumor model and inhibit the metastasis to lung. Conclusions: Acquisitions of p53 mutations contributed to the resistance of HCC to arsenic trioxide. Nutlin-3 could overcome arsenic trioxide resistance and inhibit tumor metastasis through p73 activation and promoting mutant p53 degradation mediated by arsenic trioxide

Influence of Tip Clearance on Flow Characteristics of Axial Compressor

This paper studies the influence of tip clearance on the flow characteristics related to the performance. Based on full-passage numerical simulation with experimental validation, several clearance models are established and the performance curves are obtained. It is found that there exists an optimum clearance for the stable working range. By analyzing the flow field in tip region, the role of the tip leakage flow is illustrated. In the zero-clearance model, the separation and blockage along the suction side is the main reason for rotating stall. As the tip clearance is increased to the optimum value, the separation is suppressed by the tip leakage flow. However, with the continuing increasing of the tip clearance, the scale and strength of the tip clearance vortex is increased correspondingly. When the tip clearance is larger than the optimum value, the tip clearance vortex gradually dominates the flow field in the tip region, which can increase the unsteadiness in the tip region and trigger forward spillage in stall onset