In recent years, E&P companies including national oil companies are accelerating its move towards digital transformation for their business that utilize digital technologies such as AI and IoT. E&P companies are under pressures for development and operation cost reductions, and are working on an innovative approach in collaboration with rapidly developing IT companies. In this symposium, we will introduce the current status of digital transformation efforts in the domestic and overseas E&P companies.

Digital technology has a strong potential to transform our business process and enhance the operational efficiencies in oil and gas industries. INPEX has been exploring the applicability of various digital technologies, such as machine learning, deep learning, big data analytics, internet of things （IoT） and robotics etc. since early 2018 as part of 2018-2022 Technology roadmap strategy. This paper describes the one of current domestic projects, which aim is the visualization & optimization of the production well performance. This project has been executed to the oldest oil field in Japan, located in the Akita prefecture. The passion of the project is not only to increase hydrocarbon productivities, but also to reduce the operating expense （OPEX）/bbl. In addition, the paper includes INPEX digital transformation（DX） strategy & lessons learnt from various proof of concept （PoC） projects, which we have also conducted since the beginning of 2018.

Over the past few years, there have been many application references related to the utilization of Arti?cial Intelligence （AI） Technology in various industries. However, oil & gas industries have been left behind in this movement because of various reasons including the lack of opportunity to share the best practices within the industry.

This paper covers a few of the examples of the AI technology use cases in the oil & gas industry including the model developed by the authorʼs group in aim to increase the productivity of the LNG plant.

Cross-cutting digital transformation driven by domain expertise and experience is re-shaping the future of the industry, giving birth to high-stake digital opportunities for all stakeholders: the creation of new workflows and collaboration at every stage of E&P operations, impacting operational efficiency, increasing asset reliability, boosting throughput, recovery and raising safety levels across the value chain. The 4th industrial revolution is underway, fed by breakthroughs in automation, robotics, artificial intelligence and the internet of things. Like in many other industries, this 4th industrial revolution creates fundamental shifts in oil & gas. Of all stages of the E&P lifecycle, production operations stand to make the largest gains from this digital disruption, with an estimated 6% to 35% value at stake, where business value refers to savings or gains, such as time and cost savings through efficient processes or replacement of people by machines through creative destruction also known as the act of old jobs being replaced by newer ones. Driven by the promise of ubiquitous digital transformation, Schlumberger envisioned a few years back, and refocused its R&D effort since, on the delivery of such breakthrough capabilities. We strongly believe that this new approach is set to unlock the enormous potential of a digitally enabled, integrated and automated operating environment that benefits from the convergence of digital enablers, high-end E&P science and domain expertise. Cross-cutting digital transformation driven by domain expertise and experience is re-shaping the future of the industry, giving birth to high-stake digital opportunities for all stakeholders: the creation of new workflows and collaboration at every stage of E&P operations, impacting operational efficiency, increasing asset reliability, boosting throughput, recovery and raising safety levels across the value chain.

The 4th industrial revolution is underway, fed by breakthroughs in automation, robotics, artificial intelligence and the internet of things. Like in many other industries, this 4th industrial revolution creates fundamental shifts in oil & gas. Of all stages of the E&P lifecycle, production operations stand to make the largest gains from this digital disruption, with an estimated 6% to 35% value at stake, where business value refers to savings or gains, such as time and cost savings through efficient processes or replacement of people by machines through creative destruction also known as the act of old jobs being replaced by newer ones.

Driven by the promise of ubiquitous digital transformation, Schlumberger envisioned a few years back, and refocused its R&D effort since, on the delivery of such breakthrough capabilities. We strongly believe that this new approach is set to unlock the enormous potential of a digitally enabled, integrated and automated operating environment that benefits from the convergence of digital enablers, high-end E&P science and domain expertise.

Digital rock physics combines modern microscopic imaging with numerical simulation for analysis of the physical and hydrological properties. Recent technology developments of X-ray microcomputed tomography

（micro-CT） as well as computational capacity for numerical simulation enable us to apply digital rock physics to natural

rock samples. Using digital rock models, we study porous flow, fluid-solid interaction, interfacial phenomena, elastic and inelastic deformation, and mineral precipitation within real pore space. This approach allows us to estimate both hydraulic and elastic properties in various reservoir conditions. Here we mainly show the application of digital rock physics for carbon capture and storage （CCS）. The behavior of CO₂ inside pore space can be characterized as two-phase or three-phase flow in a porous media system, which is usually influenced by interfacial tension, pore structure, pressure, wettability, etc. Therefore, we believe that digital rock physics contributes to reveal multi-phenomena in porous medium occurred in the CCS project. To characterize hydraulic properties of reservoirs using geophysical data, we can use digital rock physics to obtain the relationship between hydraulic and geophysical properties. We usually use analytical models or empirical relations to estimate physical/hydraulic properties from geophysical properties（ e.g., seismic velocity）.

However, the analytical models（ e.g., differential effective medium theory） can be applied only for the simplified pore geometry （e.g., crack）. The digital rock physics can construct the relationship between elastic properties and hydraulic properties by considering realistic pore geometry and in various reservoir conditions. The relation contributes to monitoring and modeling of the reservoirs.

Asset integrity management system （AIMS） outlines the ability of an asset to perform its required functions effectively and ef?ciently whilst protecting safety under the integrated system. AIMS is drawing attentions more than ever since the maximum valuation of existing assets is the main stream in E&P industry currently under the volatile oil market and AIMS plays an important role on this.

On the other hand deteriorations of aging facilities or deviation from the basis of design are common challenges in brown field. Such late stage challenges were eminent issues in the production Asset A and in addition to the rigorous inspection and maintenance program a facility life extension work （FLEW） had launched for the extension of the facility life. At the same time an asset integrity & operation assurance （AI&OA） initiative had been built from the corporate standpoint to propagate the AIMS concept to the production assets.

In2017 an AI&OA survey under AI&OA initiative was conducted focusing on FLEW to observe the status and ensure FLEW was in progress under systematic and competent manners in line with the AIMS. AI&OA framework is a cyclic process stating from the risk identification. As the result of the survey it was acknowledged FLEW needed to reinforce some items such as the risk assessment, organization structure, project execution plan, monitoring and key performance indicator （KPI）, technical authorization, document control and project review process.

Another AI&OA Survey was conducted in 2018 focusing how FLEW program was conveyed adhering to AI&OA framework and addressing the items pointed out during 2017 survey. 2018 survey result had indicated FLEW program was executed in line with AI&OA framework fulfilling all of requirements.

What is important in artificial lift installations to the mature oil filed is flexible operations and the appropriate installation schedule considering uncertainty of production forecasts. The reason is that it is expected to minimize the installation and operation costs, in addition to accelerate oil recovery. This paper introduces challenges and approaches for optimization of jet pump installations for the Ayukawa field in Japan.

Engineering science largely relies on a fundamental understanding on the structure-property relationships at various spatial and time scales. Digital oil is a molecular model of crude oil that is represented by multiple representative molecules created based on analytical data. This concept was proposed by our group in 2014 inspired by the concepts of digital field and digital rock, which emerged, historically, in the oil industry as critical technical revolutions. For five years, my colleagues and I have been working on digital oil and constructed two types of light crude oil as well as two types of heavy crude oil models with one being oil sand bitumen. So far, the applications include: （1） predicting asphaltene precipitation,（ 2） better solutions to asphaltene problems, and（ 3） heavy oil development. For heavy oil, we developed the method for constructing molecular models of saturates and aromatics. To predict phase behavior, we are working on a coarse-grained digital oil model. Digital oil builds a bridge between basic petroleum chemistry and engineering via molecular simulation techniques. We believe that this technique will be widely used for solving problems in both upstream and downstream in oil industry.

Asphaltene inhibitor （AI） is widely used to mitigate and/or prevent asphaltene deposition problems in reservoir, tubing and surface facilities. Many types of commercial AIs are available. To select suitable AI is a key to success of asphaltene mitigation. Currently, asphaltene dispersancy test （ADT） under ambient condition has been widely applied as a standard procedure of AI screening. However, more practical screening tests at the operating conditions are required. In this paper, a new workflow of selecting proper AI is introduced, consisting of “compatibility testing”, “dynamic asphaltene inhibitor tests （DAIT）”, core flooding test, evaluation for squeeze lifetimes on the basis of core flooding test and so on. Those series of tests consider with actual operation condition.