Technology of 3D Seismic Data Acquisition in Ake gas reservoir

Abstract

Implicit Discourse Relation Recognition (IDRR), which infers discourse relations without the help of explicit connectives, is still a crucial and challenging task for discourse parsing. Recent works tend to exploit the hierarchical structure information from the annotated senses, which demonstrate enhanced discourse relation representations can be obtained by integrating sense hierarchy. Nevertheless, the performance and robustness for IDRR are significantly constrained by the availability of annotated data. Fortunately, there is a wealth of unannotated utterances with explicit connectives, that can be utilized to acquire enriched discourse relation features. In light of such motivation, we propose a Promptbased Logical Semantics Enhancement (PLSE) method for IDRR. Essentially, our method seamlessly injects knowledge relevant to discourse relation into pre-trained language models through prompt-based connective prediction. Furthermore, considering the prompt-based connective prediction exhibits local dependencies due to the deficiency of masked language model (MLM) in capturing global semantics, we design a novel self-supervised learning objective based on mutual information maximization to derive enhanced representations of logical semantics for IDRR. Experimental results on PDTB 2.0 and CoNLL16 datasets demonstrate that our method achieves outstanding and consistent performance against the current state-of-the-art models. 1

State of the Art of Oil and Gas Pipeline Vulnerability Assessments

“…In 2004, the American Petroleum Institute introduced vulnerability to risk assessment for the first time [86], and since the 1910s, Chinese researchers have gradually extended the study of vulnerability to oil and gas pipelines [87], exploring the connotations of vulnerability, the construction of indicator systems, and the determination of indicator weights for oil and gas pipelines. The comprehensive indicator method is widely used because of its clear principles and ease of implementation.…”

“…Zhao et al [90] constructed a "detect-deterdelay-respond-recover" vulnerability assessment model from the perspective of accident development history, used the entropy value method to specify the indicator weights, and finally built a vulnerability-based risk assessment process for oil and gas pipelines. Wang Jia [87] carried out an analysis and assessment of the inherent vulnerability of oil and gas pipelines at different key locations through the fuzzy comprehensive assessment method. Wang et al [91] constructed a vulnerability assessment system for urban natural gas pipelines and town gas PE pipeline systems.…”

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“…Therefore, it is crucial to study how safety information distortions can be properly quashed/dispelled and how negative effects can be avoided. Controllability [ 38 ]: Safety information distortions can be managed and suppressed in certain ways, such as suppressing its release time, contact rate, interaction rate, and transmission rate, and controlling the release time, speed, content, transmission mode, and intensity of safety information. …”

“…Certain methods of safety information flow network adjustment can be adopted to execute the delayering management mode based on graph theory [ 4 , 38 ]. By combining delayering management mode and graph theory, it can be seen that the network structure of IDSM has the following three characteristics: (1) Delayering mode requires fewer hierarchies in the transmission structure.…”

Experimental and molecular dynamics study of gas flow characteristics in nanopores

“…The average friction factor of a compressible fluid in a tube can be expressed as by Wang et al [22]:…”