Tạp chí Dầu khí

This paper summarises experiences on industrial scale reforming of CO2-rich natural gas. Methane can react in a direct route with CO2 to form a synthesis gas consisting of CO and H2, so called dry reforming (DMR). This reaction is closely related to steam methane reforming (SMR). DMR has received much attention as it in theory off ers a way of using CO2, which is considered in many industries as a waste product and environmentally as a polluting greenhouse gas. In an industrial scale with realistic feedstock, water cannot be completely omitted from the reaction, as this specifi cally will be needed for removal of higher hydrocarbons. Instead, high severity CO2-reforming can be done, which have been proven in several industrial plants. Sulfur passivated reforming (SPARG) has demonstrated that CO2-reforming can be achieved without use of expensive noble metals. In addition to thermodynamic consideration, mass balance constrains must be considered. Mass balance dictates that high severity CO2-rich gas will result in a synthesis gas with low H2/CO ratio. Thus, the commercial feasibility of CO2-reforming is highly dependent on the desired product. CO2 reforming may be an attractive solution for product requiring lower H2/CO ratio, such as higher alcohols, reducing gas, and acetic acid, etc.

The purpose of this work was to develop a method for predicting temperature/pressure dependent density of biodiesel based on fatty acid ester composition. The PC-SAFT equation of state combined with a modified group contribution method was used to calculate density of mixtures of fatty acid esters. Prediction errors at atmospheric pressure were less than 0.5% for 10 multi-component mixtures of fatty acid ethyl esters. Compared with experimentally measured density at 0.1 - 45MPa, the predicted densities of soybean, rapeseed, palm, mixture of soybean and rapeseed, mixture of palm and rapeseed, mixture of soybean and palm, mixture of soybean and rapeseed and palm,sunflower biodiesel were all within 1%.

The paper presents an in-depth analysis and evaluation of the role of the oil and gas industry, which is represented by the Vietnam National Oil and Gas Group (Petrovietnam), in the national economy, and analyses the changes and development of the oil and gas sector in recent years. The analysis covers most of the activities that contribute to the development of Vietnam’s economy and Petrovietnam’s activities in the oil and gas value chain.

Với sự phát triển của Trí tuệ nhân tạo công nghiệp (Artificial Intelligence - AI), cảm biến thông minh và Internet vạn vật (Internet of Things - IoT), các công ty đang học cách sử dụng dữ liệu trong quá trình vận hành không chỉ để phân tích quá khứ mà còn dự đoán tương lai. Bảo trì tiên đoán (Predictive Maintenance - PdM) là một phương pháp sử dụng các kĩ thuật thu thập, làm sạch, tối ưu và phân tích dữ liệu từ các nguồn dữ liệu và cảm biến khác nhau trong quá trình vận hành như mức sử dụng máy móc, điều kiện hoạt động, thông số và phản hồi của thiết bị. Phương pháp Bảo trì tiên đoán áp dụng các thuật toán phân tích dữ liệu nâng cao, tự động so sánh dữ liệu được cung cấp và thông tin từ lịch sử vận hành trước đó để chuẩn đoán hoặc dự đoán lỗi thiết bị trước khi nó xảy ra, tối ưu hóa việc sử dụng thiết bị, chiến lược bảo trì và cải thiện hiệu suất, năng suất và kéo dài tuổi thọ thiết bị. Việc có các công cụ Bảo trì tiên đoán mạnh mẽ cho phép các tổ chức tận dụng dữ liệu hiện có, thông tin từ lịch sử để tránh các sự cố an toàn, gián đoạn sản xuất và giải quyết chúng một cách chủ động thay vì phản ứng với các vấn đề khi chúng phát sinh. Chính vì vậy, điều này đã tạo ra sức hút rất lớn cho các nhà nghiên cứu trong những năm gần đây. Bài báo này đánh giá toàn diện về những tiến bộ gần đây của kỹ thuật Học máy (Machine Learning - ML) được áp dụng rộng rãi trong PdM, bằng cách phân loại nghiên cứu theo các thuật toán ML; máy móc và thiết bị được sử dụng trong việc thu thập dữ liệu; và nêu bật những đóng góp quan trọng của các nghiên cứu, từ đó đưa ra các hướng đi cụ thể cho các nghiên cứu tiếp theo. Đặc biệt, Biển Đông POC hiện đang tập trung triển khai thử nghiệm dự án PdM cho các thiết bị quan trọng tại giàn xử lý khí condensate Hải Thạch - Mộc Tinh.

The polycondensation of cashew nut shell liquid (CNSL) with formaldehyde was carried out in order to synthesise a pour point depressant (PPD) for paraffinic crude oils. Experimental results showed that the obtained CNSL-formaldehyde novolac resin gave good performance, decreasing the pour point of crude oil by as much as 15oC. In addition, it was also showed that there is an optimum molecular weight value of the synthesised polymer, with which the ability for depression of pour point of crude oil is expected as maximum. Thus, it is believed that with proper molecular weight control, CNSL could be polymerised into a good PPD for local crude oil.

The fourth industrial revolution (Industry 4.0) with the breakthrough of internet and artificial intelligence has had a strong impact, changing all aspects of global socio-economic life. Digital transformation in the spread of Industry 4.0 is no longer a choice but has become an inevitable development trend for businesses to truly stand up to the times. Digital transformation is the transformation of business activities, processes, products, and models to fully leverage the opportunities of digital technologies, characterised by development, growth, innovation, and disruption. In particular, "digital disruption" is the situation when new technology competes with the traditional business way that we now often refer to under the concepts of cloud computing, big data, and internet of things (IoT). This competition will help businesses utilise digitised data and processes to create a new model that is more efficient and convenient. Digital technologies in oil and gas companies can have a significant business impact as it contributes to increasing hydrocarbon recovery, ensuring safety across the business ecosystem, and improving operational reliability. This paper addresses the oil and gas industry’s trends in digital transformation and the initiatives at Bien Dong POC.

Liên doanh Việt - Nga “Vietsovpetro” đã phát triển công nghệ thu gom, xử lý và vận chuyển dầu nhiều paraffin, phù hợp với điều kiện thực tế ở các mỏ dầu khí và khác biệt so với các công nghệ truyền thống. Thành công này bắt nguồn từ việc Vietsovpetro đã có những nghiên cứu toàn diện và hệ thống về các đặc tính của dầu nhiều paraffin, cáctính chất lưu biến của dầu trong vận chuyển bằng đường ống, tổng hợp những khó khăn, thách thức trong vận chuyển dầu nhiều paraffin các mỏ Bạch Hổ và mỏ Rồng bằng đường ống ngầm ngoài khơi, trên cơ sở đó đã xây dựng và phát triển công nghệ thu gom, xử lý và vận chuyển dầu nhiều paraffin.

The Phu Khanh Basin is a narrow, elongated basin extending from 11.5 to 14°N off the coast of central Vietnam. It is bounded to the west by the narrow Da Nang shelf and separated from the Quang Ngai Graben to the North by the Da Nang shear zone, and from the Cuu Long Basin to the South by the Tuy Hoa shear zone. The purpose of this paper is to understand, by 2D modeling, the generation, migration and accumulation histories for oil and gas from source rocks in the Phu Khanh Basin. Several regional sections covering shallow to deep-water areas were modeled by SIGMA-2D software. In the sedimentary basin, Oligocene lacustrine source rock has generated oil since the Middle Miocene time and is in gas window in almost the entire area of the basin, with the main part in the deep water area at the present time. The Lower Miocene fluvio-deltaic source rock has generated oil since the Late Miocene time and is in gas window in the central part of the basin at the present time. Oil and gas generated both in the Oligocene and Lower Miocene source rocks in deep water areas migrated along a regional carrier system in Lower Miocene (both sandstone and porous carbonate) after vertical migration of the Oligocene oil and gas by cap rock leakage and through faults. The oil and gas accumulated in structural highs in both deep water and in shallow water areas. Some were already found as oil seeps from onshore outcrops [1] and were encountered in exploration wells such as 124-CMT-1X.

The Phu Khanh Basin is a narrow, elongated basin extending from 11.5 to 14°N off the coast of central Vietnam. It is bounded to the west by the narrow Da Nang shelf and separated from the Quang Ngai Graben to the North by the Da Nang shear zone, and from the Cuu Long Basin to the South by the Tuy Hoa shear zone. The purpose of this paper is to understand, by 2D modeling, the generation, migration and accumulation histories for oil and gas from source rocks in the Phu Khanh Basin. Several regional sections covering shallow to deep-water areas were modeled by SIGMA-2D software. In the sedimentary basin, Oligocene lacustrine source rock has generated oil since the Middle Miocene time and is in gas window in almost the entire area of the basin, with the main part in the deep water area at the present time. The Lower Miocene fluvio-deltaic source rock has generated oil since the Late Miocene time and is in gas window in the central part of the basin at the present time. Oil and gas generated both in the Oligocene and Lower Miocene source rocks in deep water areas migrated along a regional carrier system in Lower Miocene (both sandstone and porous carbonate) after vertical migration of the Oligocene oil and gas by cap rock leakage and through faults. The oil and gas accumulated in structural highs in both deep water and in shallow water areas. Some were already found as oil seeps from onshore outcrops [1] and were encountered in exploration wells such as 124-CMT-1X.

The purpose of this work was to develop an empirical model for predicting temperature dependent dynamic viscosities of biodiesel, based on their fatty acid ester composition. The Vogel equation [1] was used to describe the viscosity-temperature relationship of pure fatty acid esters (FAME-Fatty acid methyl ester/FAEE-Fatty acid ethyl ester) commonly present in biodiesel fuels, and a modified mass fraction based mixing equation was used to predict viscosity of 47 biodiesel mixtures based on their FAME/FAEE composition. The accuracy of this simple method was better than the other mass-based semilog blending equation reported in the literature.