首页|Reports on Machine Learning Findings from China University of Petroleum East Chi na Provide New Insights (Sparry Calcite Identification in Shale Reservoirs By Da ta Augmentation And Attentionbased Machine Learning Algorithms)
Reports on Machine Learning Findings from China University of Petroleum East Chi na Provide New Insights (Sparry Calcite Identification in Shale Reservoirs By Da ta Augmentation And Attentionbased Machine Learning Algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New study results on artificial intelligence have been published. According to news originatingfrom Qingdao, People’s Republic o f China, by NewsRx editors, the research stated, “Sparry calcite is anindicator of favorable production lithology and it also exerts a positive influence on pr oduction capacity.”The news editors obtained a quote from the research from China University of Pet roleum East China:“Therefore, sparry calcite identification is an important par t of shale reservoir exploration. However, the logging response to sparry calcit e is weak and sample sizes are limited, making accurate identificationchallengi ng using conventional methods. To address this challenge, we propose data augmen tation andattention-based machine learning algorithms, specify logging curves a s experimental data. Initially, thedataset is optimized using Synthetic Minorit y Over-sampling Technique (SMOTE) and wavelet transforms.Subsequently, an atten tion-based Convolutional Neural Network (CNN) is trained to extract nonlinear features from the input logging curves. These nonlinear features are then fed into the Bi-directional LongShort-Term Memory (BiLSTM) to extract potential informa tion regarding the depth domain sequence andachieve accurate identification of sparry calcite.”
China University of Petroleum East ChinaQingdaoPeople’s Republic of ChinaAsiaAlgorithmsCyborgsEmerging Techn ologiesMachine Learning
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