Currently, the rapid development of digitalization and intelligence, the accelerating pace of green and low-carbon transformation in energy, the interweaving and integration of digital technology and energy transformation, bring new opportunities for the energy industry to achieve zero carbon goals and green, safe and high-quality development.
At the recently held inaugural meeting and first academic seminar of the Oil and Gas Digitalization and Intelligence Professional Committee of the China Petroleum Society, attending experts conducted in-depth discussions on topics such as exploring and practicing the digital transformation and intelligent development of petroleum and petrochemical enterprises, promoting technological innovation through digital technology, implementing and applying achievements in intelligent oil and gas fields, intelligent refining, and intelligent pipeline networks, and continuously building and expanding the digital technology ecosystem.
Reporter Qin Zihan
Digital transformation is a systematic project
With the flourishing of technologies such as big data, cloud computing, artificial intelligence, and digital twins, major oil companies around the world are actively integrating advanced digital information technology with traditional industries, continuously promoting the multi-level rapid development of digitization and intelligence in the oil and gas industry from point to line, from line to surface, and from surface to body.
China vigorously promotes the construction of energy Internet, integrates and optimizes energy production, storage and transportation, consumption and management by using digital technology, improves energy conversion and allocation efficiency, and gradually forms a smart energy ecosystem.
Faced with challenges such as fluctuations in oil and gas prices, regional supply-demand imbalances, and the growth of renewable energy, global oil and gas companies are utilizing new information and digital technologies such as "Cloud, Big Data, IoT, Smart Chain Twin" to promote digital transformation, explore and create new business models, and enhance their core competitiveness. For example, the rise of ChatGPT has made artificial intelligence technology a new engine for social and economic development, and new technologies will become the key to industry development in the future, as well as the main driving force for the development of the digital economy.
The report of the 20th National Congress of the Communist Party of China proposed to accelerate the development of the digital economy, promote the deep integration of the digital economy and the real economy, and create a digital industry cluster with international competitiveness. This provides a clear direction for the digital transformation of enterprises, which will give rise to a number of digital application achievements in the future.
Digital transformation is a systematic project, a long-term transformation process that requires the continuous development of new capabilities, rather than a one-time task. It should focus on improving efficiency and effectiveness, continuously improving factor productivity and resource allocation efficiency, and enhancing enterprise operational efficiency. In the process of transformation, productivity and production relations will undergo changes, shifting from adapting to material economy and scale economy to adapting to digital economy and scope economy. In order to adapt to this change, it is necessary for enterprises to undergo comprehensive transformation in various fields, achieve interactive innovation and collaborative optimization of business, organization, and technology.
Digital transformation should focus on cultivating and strengthening digital productivity, constructing organizational and operational mechanisms that are compatible with digital productivity from the perspectives of industrial chain, supply chain, and value chain, and achieving model reengineering. In the process of promoting transformation, the content and scope continue to expand, gradually shifting from local optimization to global optimization and comprehensive transformation. The ultimate goal is to redefine customer value, explore new business areas, and disrupt traditional ways of working.
Over the years, enterprises such as Sinopec, PetroChina, CNOOC, and National Pipeline Network, as well as many universities and research institutions, have deeply implemented the strategy of building a strong network and a digital China. They have actively applied new generation information technologies such as 5G, big data, artificial intelligence, and cloud computing, vigorously built advanced and applicable digital intelligent platforms, continuously strengthened data governance, and promoted the modernization of management innovation, governance systems, and governance capabilities driven by data and knowledge. They have achieved significant results in fields such as intelligent oil and gas fields, intelligent refining, intelligent pipeline networks, intelligent sales, intelligent engineering, and intelligent finance.
Hu Bingjun, Director of the Oil and Gas Digitalization and Intelligence Professional Committee of the China Petroleum Society, stated that years of development practice have proven that the digital transformation of petroleum and petrochemical enterprises is a systematic project of reform and innovation. Currently, there are still a series of problems that need to be addressed through collaboration in development strategy, top-level design, business transformation, digital technology, and other aspects to form a joint force for common promotion. It is urgent to build an innovative and collaborative organization with industry characteristics for digital and intelligent technology to solve the common problems encountered by various enterprises in the process of digital transformation.
Data security issues have received widespread attention
Feng Dengguo, an academician of the CAS Member, stressed that data is a basic strategic resource and key production factor in the digital era. Especially with the deepening of the national big data strategy, data elements are showing a trend of accelerating integration and interconnection. In this context, data security issues are particularly prominent.
The 14th Five Year Plan for National Economic and Social Development of the People's Republic of China and the Long Range Objectives Through the Year 2035, released in March 2021, emphasizes promoting the coordinated transformation of the entire industry chain through data empowerment and strengthening the security protection of data resources throughout their lifecycle. In October 2022, the State Council's report on the development of the digital economy pointed out the need to comprehensively strengthen network security and data security protection, and promote the construction of a community with a shared future in cyberspace. The implementation of the Data Security Law and the Personal Information Protection Law in 2021 poses a real challenge in balancing the development of the digital economy with important data security and personal privacy protection.
The Data Security Law defines data and data security separately. Data refers to any electronic or other record of information; Data security refers to taking necessary measures to ensure that data is effectively protected and legally utilized, as well as having the ability to guarantee sustained security. Data has a lifecycle, including generation, collection, transmission, exchange, storage, analysis, use, sharing, destruction, and many other links. Each link faces security threats and requires full chain security protection.
Currently, data security mainly faces six major threats: data leakage, data destruction, privacy breaches, data loss, data abuse, data damage, and loss. Feng Dengguo pointed out that in recent years, with the continuous development of technology, data monopoly or hegemony, data extortion, and extortion threats have become increasingly serious. Important data is controlled by a small number of individuals and organizations, and is unreasonably allocated and used, including super platforms that attract large amounts of traffic and gather massive information through their own network ecosystems, or use advanced technology to form large amounts of data and control it. Data monopoly or hegemony will limit the free flow of data resources in the market. Attackers may use technologies and tools such as ransomware to make data owners unable to use the data, and provide means of recovering the data by demanding ransom. Alternatively, attackers may create a copy of the data and then threaten to make it public, demanding ransom.
The arrival of the big data era has brought great attention to the "ancient" term of "data security". In the era of big data, data security not only includes traditional confidentiality, integrity, and availability, but also privacy and sensitivity, including not only privacy and sensitivity to prevent data leakage, but also privacy and sensitivity in data analysis. The solution to data security issues cannot be achieved without the support of supporting regulations and policies, as well as strict management measures. However, more reliable technical means are needed to support data security technology, including corresponding technologies in all aspects of the digital lifecycle, as well as common supporting technologies such as data classification and grading, compliance checks for data security, and data security supervision.
In addition, to support data security throughout the entire lifecycle of data, it is necessary to establish three major technical systems: data security protection (zero trust network access control, ciphertext and secure multi-party computing, secure and trusted computing environment construction, etc.), data security governance (privacy leakage analysis and anonymization evaluation, personal privacy protection monitoring, etc.), and data security deterrence (secure data tracing and traceability, network space data mapping, intelligent data induction and countermeasures, etc.).
Currently, there are three mainstream development directions for data security: data storage security, data transmission security, and data usage security. Among them, data security has received high attention, and there have been multiple far-reaching attacks based on memory data. With the development of emerging application scenarios such as cloud computing and big data, and the continuous expansion of the number of mobile and IoT devices, there is an urgent need to protect the data in use. In 2017, hackers used a tool called Triton to attack a refinery located in Saudi Arabia, causing it to shut down urgently. Analysts discovered malicious programs that extracted user passwords or other authentication credentials from memory, with the goal of shutting down normal service functions controlled by industrial systems and causing physical damage. Data usage security is currently the weakest link in data security and is a cutting-edge development direction that requires accelerated innovation research and practical application.
Feng Dengguo suggested that we should establish a concept of independent and controllable, secure and trustworthy protection, continuously deepen our understanding of the connotation of data security, keep up with the development trend of international data security technology, strengthen the research and formulation of data security strategies and laws and regulations, closely integrate with industry and application reality, independently control a number of core technologies and products, and promote the development of the data security industry with high quality.
