Kun Huang

TL;DR: This is the first academic peer-reviewed paper on the “Oil and Gas 4.0” era, aiming to let more oil and gas industry personnel understand its benefits and application scenarios, so as to better apply it to practical engineering in the future.

TL;DR: This paper first presents the relevant theories and core technologies of the blockchain, and then describes how the blockchain is applied to the oil and gas industry from four aspects: trading, management and decision making, supervision, and cyber security.

TL;DR: Six machine learning models are used to predict the daily carbon price and trading volume of eight carbon markets in China, including Beijing, Shenzhen, Guangdong, Hubei, Shanghai, Fujian, Tianjin, Chongqing, and an advanced data denoising method is used in the models to smooth the raw data.

TL;DR: A hybrid prediction model that integrates an improved whale swarm algorithm (IWOA) and relevance vector machine (RVM) and empirical mode decomposition (EMD), approximate entropy (ApEn), and C-C method are introduced to aid the calculation.

TL;DR: In this article, the development of carbon dioxide transport via pipeline is systematically reviewed from four aspects: pipeline design, process, risk and safety, standard and specification, and the results reveal that there are many similarities between the carbon dioxide pipeline and the natural gas pipeline, but due to different gas compositions and transportation destinations, the transport process, design and construction considerations are quite different.