As far as innovations go in the oil and gas industry, new technologies take center stage, transforming how we explore, drill, and produce energy. With the power of digital transformation, we're boosting safety measures, supercharging productivity, and finding more innovative ways to save costs.

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According to research conducted by Accenture, adopting digital technologies in the upstream and downstream of the oil and gas sector can cut capital expenditures by up to 20% and improve cash flow.

For example, this McKinsey report shows the digital transformation of an Asian oil and gas company that generated $150 million in value within three years.

Based on these predictions, companies in the oil and gas industry should start exploring ways to use technology to solve the significant problems of the oil and gas industry right away.

This article will review the most common challenges in the oil and gas industry and the five best use cases for digital transformation. These insights will help you make digital investments, optimize processes, improve efficiency, and drive innovation for your business strategy.

The most common challenges in the oil and gas industry

Operational efficiency and cost reduction

Oil and gas companies strive to enhance operational efficiency and reduce costs in their gas sector operations. It allows them to stay competitive, increase profitability, and adapt to the evolving energy market demands.

Operational efficiency involves optimizing exploration, drilling, production, refining, and distribution. The ultimate goal is to increase productivity, maximize efficiency, and minimize expenses throughout the value chain.

Due to the industry's capital-intensive nature, companies aim to reduce costs by utilizing internal resources and implementing efficient strategies. These business strategies may include:

• Optimizing supply chain management
• Negotiating favorable contracts with suppliers
• Embracing digital technologies for automation and efficiency gains
• Improving energy efficiency
• Reducing operational and maintenance expenses

Implementing these business strategies can increase the production volume by 1-4%, thus improving profitability.

Safety and risk management

Activities in the oil and gas sector include hazardous processes such as drilling, refining, and transportation of volatile substances.

Effective safety risk and management in the oil and gas sector require a comprehensive approach encompassing stringent safety protocols, state-of-the-art technology, and a proactive safety culture. Companies invest significantly in advanced monitoring systems, data analytics, and predictive maintenance to anticipate and mitigate potential risks before they escalate.

Risk management in oil and gas companies entails identifying, assessing, and mitigating various associated risks. These risks encompass a range of factors, such as

• Equipment failures
• Natural disasters
• Geopolitical uncertainties
• Regulatory compliance
• Market volatility

Despite the safety improvement, these incidents still occur. For example, a gas leak incident at Hammerfest LNG plant at Melkøya on 31st May 2023 due to a valve connection problem in the cooling circuit stopped the plant operation with no surety of resuming production.

By actively recognizing, evaluating, and addressing these risks, companies can effectively navigate the challenges posed by operational hazards and external uncertainties, ensuring their operations' safety, compliance, and stability.

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Workforce collaboration

The challenges oil and gas companies face extend beyond technological advancements – they also encompass gaps in effective communication and collaboration that tend to escalate as organizations grow.

The oil and gas sector needs the collaboration and specialized expertise of various teams, comprising engineers, geologists, technicians, field operators, project managers, and other professionals, who operate across diverse locations such as exploration sites, drilling rigs, production facilities, and corporate offices.

The cooperation between engineering and data science is the most critical challenge because these groups have differing expertise and perspectives on the same problems. This time-consuming and challenging task can be solved with the help of AI technology for process optimization - Basetwo.

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Data management and analytics

One of the primary challenges that oil and gas companies encounter is efficiently managing the substantial amount of data gathered throughout the entire process, from crude oil acquisition to downstream processing. As an example, the composition of the crude oil depends on the extraction location and conditions.

After the data acquisition, the oil and gas companies faced another big challenge in analyzing the results. Therefore, the required analysis should be made timely and accurate, and without the help of digital tools, it can be time-consuming and full of errors.

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GHG scope 1/2 emissions reduction

The oil and gas sector is at the top of the list whenever the industrial sector's role in climate change is discussed. It is primarily driven by the substantial investment of energy companies in utilizing fossil fuels, which are the main contributors to carbon emissions.

According to the Climate trace, the greenhouse gas potential of fossil fuel operations over a time horizon of 100 years in 2021 accounts for 56.46% contributions by oil and gas production and transportation and 11.04% by oil and gas refining. Oil and gas companies must significantly reduce their emissions to fulfill their role.

Decarbonization

Oil and gas companies face much pressure due to social and environmental concerns. The main drivers are as follows:

• Society demand
• Investor pressure
• Policies and targets
• Cost and technology reduction

The world is moving towards an energy transition; however, with the growing demand, relying solely on alternative resources to produce energy is impossible.

Therefore, the decarbonization of this sector by using alternative energy sources, replacing old technologies, and optimizing processes is part of the solution. The decarbonization of oil and gas companies seems more realistic and cost-effective, considering the present dilemma of energy demand.

The decarbonization of this sector is a manageable scenario for the energy sector, as some claim. However, to follow the decarbonization goal, the remaining fossil fuels must be used as efficiently as possible with low carbon emissions.

Furthermore, the CO₂ produced during the operations of oil and gas companies should be minimized with new-generation technologies and carbon storage systems.

New technologies can bring improvements, although it is a very costly solution. Compared to that, optimizing the industry to use the lowest possible amount of fossil fuels is the more economical solution that can be implemented worldwide.

Top 5  use cases for a digital transformation in the oil and gas industry:

According to a survey conducted by TRUE global intelligence in June 2020, about 80% of enterprises in this sector are investing a moderate amount of internal resources in the digital transformation of their industries.

Artificial intelligence for predictive maintenance

The digital transformation in energy companies can make predictive maintenance easier by quickly inspecting volumes of data about the equipment used. The benefits due to the implementation of artificial intelligence for the predictive maintenance of oil and gas include:

• Reduced unplanned downtime
• Effective inspections
• An improved lifetime of equipment and catalysts
• Safer Operations
• Enhanced Productivity
• Decreased Labor
• Advanced analytics for risk management

Digital transformation significantly reduces risk probability by leveraging digital technology and advanced algorithms. With the ability to swiftly analyze vast datasets and decipher valuable patterns, digital solutions enhance risk assessment and mitigation strategies.

By harnessing the power of data, companies can proactively identify potential risks, make informed decisions, and enhance overall safety and operational resilience.

Afterward, they can deduce the best possible outcome based on previous experience and the nature of the information.

AI can harness the true strength of advanced analytics to improve oil and industry operations throughout the entire value chain. It can create and suggest scheduled and professional training based on prior experience in the industry.

Advanced analytics for risk management based on AI is not restricted to any one model. It can relate various business models and deduce the value chain with the best possible information based on evaluating multiple models such as fault tree analysis and HAZOP.

AI models for real-time monitoring and simulations

The vast number of datasets, with significant volumes of raw material exhibiting variance and non-linearities, poses challenges for midstream and upstream oil and gas players and downstream companies in effectively managing and keeping track of all the information.

Furthermore, the data obtained after upstream, midstream, and downstream processing significantly increase the amount of data.

AI models with real-time monitoring assist in data observation and manipulation by arranging the data sequentially and presenting it in user-friendly forms such as graphs.

Moreover, AI enhances the simulation's value by providing accurate models for vast datasets and a wide range of operations, thus, reducing the extensive engineering hours required for these problems.

Cloud computing and data integration

Cloud computing is a transformative technology that empowers organizations to access and utilize a wide range of computing services through the internet, such as storage, databases, servers, software, and networking. It eliminates the need for substantial on-premises infrastructure and enables on-demand access to computing resources.

By leveraging cloud computing, businesses can benefit from scalable and flexible solutions that are cost-effective. Moreover, cloud computing facilitates effortless collaboration and seamless data sharing across multiple locations.

According to an article published by GlobalSpec, the big industries in this sector, such as ExxonMobil, Chevron, BP, Total, and Shell, are moving towards cloud computation to remain competitive and participate in the ever-changing global industry.

A data integration tool simplifies merging data from various sources and formats to create a cohesive and consistent view. It enables organizations to extract, transform, and load (ETL) data, ensuring reliability, uniformity, and compatibility.

Data integration tools are essential for the following:

• consolidating and using data scientists
• harmonizing data from disparate systems and sources
• empowering businesses to obtain comprehensive insights
• making well-informed decision
• creating new business models,
• accelerating digital transformation
• increasing operational efficiency

Combining cloud computing and data integration tools presents a potent cooperation for organizations amid digital transformation.

It furnishes the necessary infrastructure and computing resources for storing, processing, and analyzing substantial data. It additionally offers scalability and flexibility, enabling businesses to adapt their computing resources according to their specific requirements.

Emissions management software for tracking and managing energy consumption

Emissions management software encompasses essential functionalities like collecting and consolidating data from diverse sources, including energy usage, fuel consumption, transportation, waste management, and the oil and gas company's operational activities.

This software allows organizations to centralize and integrate emissions data, enabling a holistic understanding of their environmental performance.

Moreover, emissions management software often provides capabilities for scenario modeling and forecasting. It empowers organizations to simulate the potential outcomes of various emission reduction strategies, assess the effectiveness of different initiatives, and actively make well-informed decisions to diminish their environmental impact.

According to the report of BCG published in September 2021, optimizing production processes in the context of energy efficiency can reduce energy consumption by up to 15% while maintaining the production targets.

In some cases, it is considered one of the cheapest and fastest ways to reduce emissions from this sector.

How to simplify process optimization for oil and gas

Basetwo is a giant leap in the digital transformation of the global oil and gas industry with an innovative and up-to-date platform. It provides optimized operation strategies incorporating various digital technologies and schemes to quickly understand and communicate the process’s upstream, midstream, and downstream operations.

Basetwo can be essential in optimizing energy consumption and cost reduction by predicting power load. It can connect multiple data sources and leverage machine learning (ML) algorithms that inform the energy production and storage system requirements in advance. It reduces power, time, cost consumption, and greenhouse gas emissions.

Furthermore, it provides a real-life understanding of the complex conversion processes (such as reforming and gasification), which constitute a significant concern in the overall operation due to the variation and non-linearities in the raw materials and conditions.

Contact us today for a live demo of our tool.

Role of Basetwo in the Optimization of Complex O&G Processes

Due to versatility and multi-objective optimization functions, Basetwo can assist in complex processes such as LNG liquefaction, gas sweetening, and distillation.

LNG Liquefication

LNG  liquefication is energy-consuming and cost-intensive due to its refrigeration and compression sections. Moreover, the maintenance of final product quality is also a huge concern due to the varying quality of the raw materials.

The multi-objective optimization of Basetwo makes it very easy to deal with this complex process. For instance, it can simultaneously adjust the inlet/outlet pressures of the compressor, adaptive adjustment of the refrigeration loop, and heat exchanger flow rates to maintain the temperatures for better product quality.

LNG liquefication processes can reap substantial benefits from digital transformation. By utilizing advanced process modeling, optimization algorithms, and real-time data analytics, operators can optimize the operation of liquefaction units.

The optimization encompasses precise control, automated monitoring of refrigeration cycles, robotic process automation, energy efficiency improvements, automatic tracking, and enhanced data analytics for process efficiency. Implementing digital tools enables increased production capacity, decreased operational costs, and improved profitability in LNG liquefication operations.

Gas sweetening

Gas sweetening is a critical process for using natural gas as impurities like H₂S and CO₂ can damage the catalyst in downstream processing, costing a great fortune.

Nevertheless, optimizing the process requires a deep understanding of the process and immediate response upon disturbances to ensure the desired quality of gas while maintaining the catalyst beds of absorbers for the longest time possible.

Basetwo connects multiple real-time sources for collecting feed gas composition and conditions (such as pressure and temperature) and develops ML models to ensure the quality of product gas and the long lifetime of catalysts in a real-time experience.

Through digital transformation and smart sensors, gas sweetening operations in the oil and gas industry can leverage real-time monitoring and control using sensors and advanced analytics data.

It enables precise adjustments to operating conditions, optimized chemical usage and equipment utilization, and minimizes energy consumption, reducing carbon emissions and enhancing efficiency and cost savings.

Gas sweetening involves the removal of acid gases, such as hydrogen sulfide (H₂S) and carbon dioxide (CO₂), from natural gas.

Distillation

Distillation is one of the most energy-intensive processes known in this sector. In addition, the non-linearity and uncertainties in the upstream processes make acquiring the desired process efficiency more challenging.

The modeling and optimization capabilities of Basetwo can help in the non-linearities faced in the upstream process. It can predict and generate operating process conditions immediately and accurately according to the upstream disturbances, enabling engineers to react accordingly.

Utilizing digital tools, such as continuous process data analysis, enables the prediction of optimal operating conditions and dynamic adjustment of critical parameters. This optimization process maximizes separation efficiency, lowers energy consumption, and enhances the plant's overall performance.

Digital tools applied to distillation processes ensure a more precise and efficient separation of hydrocarbon components based on their respective boiling points.

Basetwo Features:

Basetwo is a low code AI platform that enables engineers to optimize their production processes in real-time. With Basetwo engineers can connect to their production, quality and maintenance databases, and use that data to build robust simulation models and receive recommendations for how to operate their equipment and processes.

• User-Friendly Interface: Easily clean data and create simulations with a simple drag-and-drop interface, no programming experience required.
• Enhanced Collaboration: Foster seamless collaboration by building and managing a library of process models in the cloud, breaking down team silos through iterative development.
• Versatile Model Building: Empower users to construct mechanistic, machine learning, or hybrid models for various systems, ranging from assets and processes to entire plants.
• Real-Time Connectivity: Connect to data lakes and leverage near-real-time data from multiple assets to perform accurate and up-to-date process simulations.

To date, we've helped Fortune 500 manufacturers reduce cycle time and operational costs by over 40% while reducing energy consumption and scope 1/2 emissions by 25%.

Conclusion

The oil and gas industry is undergoing a notable transition towards digital transformation, primarily motivated by the pursuit of enhanced efficiency, safety, and decision-making capabilities.

Although the industry confronts various hurdles to accelerating digital transformation vision, like aging infrastructure and intricate operations, there is a progressively increasing recognition of the advantages of leveraging digital transformation technologies.

We have examined several prevalent challenges encountered by the oil and gas sector during the digital transformation and digital maturity move,

These obstacles remain competitive but can be effectively tackled by implementing various digital maturity and transformation strategies that harness the potential of emerging technologies.

Choose Basetwo and traverse the modern era of the oil and gas industry. Contact us today for a demo and start reliably optimizing your drilling operations.