At the beginning of the 21st century, it was predicted that Japanese petroleum refiners would have to shift their operations in the direction indicated by the key concept FTC (Fuel To Chemicals/Fraction To Components). To maximize the value of petroleum products, a project was implemented and demonstrated to establish chemical analysis and informatics technologies, particularly related to heavy oil. The project included establishment of methods for detailed composition-structure analysis, modelling of molecular reaction pathway networks, prediction of properties and phase equilibria, and flow reaction coupled analysis. This activity established petroleomics as suitable for the current situation of the Japanese petroleum industry. Attempts have also been made by several research groups to develop new chemical processes based on reaction pathway analysis. This review introduces the overall concept and history of this research.

For methanol/dimethyl ether (DME) synthesis in temperature gradient reactor (TGR) at low pressure, according to step (1) searching for additives to the copper-based catalyst (Cu/Zn/Al), step (2) creating an appropriate temperature gradient in the catalyst layer, and step (3) adjusting the catalyst components at each temperature, high one-pass conversion was achieved. Each step was accelerated by means of machine learning. Principal component analysis and support vector machine (svm) were used in step (1), orthogonal array, svm and genetic algorithm (GA) were used in steps (2) and (3). In addition, in an internal condensation reactor (ICR) where the products methanol and water are condensed in situ to remove them from the catalyst bed and the reaction equilibrium is shifted, GA was applied to determine the reaction network in order to estimate the condensation rate in ICR. Both the experimental results and all codes for machine learning are unvailed.

The Cuu Long Basin (CLB) in offshore Vietnam is a key hydrocarbon-producing region, known for its complex geological structures, particularly in the basement granite. However, traditional seismic methods often struggle to accurately map faults and fractures within the basement granite, largely due to the lack of distinct geological layering. To overcome this challenge, this study proposes the application of the gray level co-occurrence matrix (GLCM) technique to analyze the texture of geological features, such as faults and fractures, within the basement granite of the CLB. By applying the GLCM method, the study aims to detect basement faults, identify lineaments, and examine the compartmentalization of basement reservoirs. The results demonstrate that the GLCM analysis reveals zones with shallow-deep fault interactions have lower prospectivity compared to areas where older faults do not extend upwards. Additionally, the GLCM attributes show a correlation with the FMI (Formation Micro Imager) data, assisting in the identification of additional oil reserves. GLCM analysis reveals that zones with interactions between shallow and deep faults show lower prospectivity compared to areas where older faults remain confined to deeper levels in the basement granite of the CLB. These findings underscore the potential of GLCM as a valuable tool for enhancing fault detection and reservoir characterization in complex geological settings like the CLB.

The liquid-phase oxidation of benzene using Cu(II)-2,2’-bipyridine complexes as catalysts and molecular oxygen as oxidants has been investigated. The reaction activity of three types of catalysts with one, two, and three bipyridine molecules coordinated to Cu(II) ions was compared in a batch reactor, and [Cu(bipy)Cl₂] with coordination of one bipyridine molecule obtained the highest yield of hydroquinone. The coordination structure of the complexes and ease of ligand desorption are speculated to have influenced the reaction activity. The reactor was changed from a batch reactor to a slug flow reactor to investigate the effect of different reactors on the reaction. The results indicate that the reaction in the slug flow reactor obtained a hydroquinone yield that was 5.7 times higher than that in the batch reactor. The formation of the slug flow is assumed to have continuously supplied oxygen to the liquid phase efficiently, which improved the hydroquinone yield.