Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Identification of miR-515-3p and its targets,vimentin and MMP3,as a key regulatory mechanism in esophageal cancer metastasis:functional and clinical significance

Metastasis is the main factor of treatment failure in cancer patients,but the underlying mechanism remains to be elucidated and effective new treatment strategies are urgently needed.This study aims to explore novel key metastasis-related microRNAs(miRNAs)in esophageal squamous cell carcinoma(ESCC).By comparing miRNA profiles of the highly metastatic ESCC cell sublines,we established through serial in vivo selection with the parental cells,we found that the expression level of miR-515-3p was lower in ESCC tumor tissues than adjacent normal tissues,further decreased in metastatic tumors,and moreover,markedly associated with advanced stage,metastasis and patient survival.The in vitro and in vivo assays suggested that miR-515-3p could increase the expression of the epithelial markers as well as decrease the expression of the mesenchymal markers,and more importantly,suppress invasion and metastasis of ESCC cells.Mechanistically,we revealed that miR-515-3p directly regulated vimentin and matrix metalloproteinase-3(MMP3)expression by binding to the coding sequence and 3′untranslated region,respectively.In addition,the data from whole-genome methylation sequencing and methylation-specific PCR indicated that the CpG island within miR-515-3p promoter was markedly hypermethylated in ESCC cell lines and ESCC tumor tissues,which may lead to deregulation of miR-515-3p expression in ESCC.Furthermore,our preclinical experiment provides solid evidence that systemic delivery of miR-515-3p oligonucleotide obviously suppressed the metastasis of ESCC cells in nude mice.Taken together,this study demonstrates that miR-515-3p suppresses tumor metastasis and thus represents a promising prognostic biomarker and therapeutic strategy in ESCC.