Oil and Gas
Oil and Gas
Technology Led Solutions for Faster Time to Discovery
The oil and gas industry has been known for its complexity and challenging operating environments, with installations all over the world, in complicated and remote locations. According to a recent Ernst & Young survey, 92% of oil and gas companies around the world are investing in AI or plan to do so in the next five years.
Certara.AI technology can assist you to
- Increase production
- Reduce lost time incidents
- Do more with less people
- Decrease well intervention index
- Decrease field visits
- Decrease CO2 emissions
- Reduce down time
- Reduce failures with preventative maintenance
- Develop effective molecules and formulations quicker
- 提高运营效率
Accelerate Discovery with Private AI Platform
73% of c-suite leaders are prioritizing AI over all other digital investments. As investments in AI continue to rise, the need to streamline data collection and AI deployment will be critical to future success. Today’s GPTs are trained on broad sets of data making them great at answering general questions effectively but lacking the expertise and access to data needed for internal use.
The result, users can review, validate, and fine-tune generated responses while providing the reference required for trusted AI use. This enables a powerful platform for applying GPTs across various industrial use cases such as molecular research, report generation, market intelligence and more
小分子药物发现
要了解一种分子进一步开发的可行性，需要对复杂的化学、生物、逻辑和计算数据进行分析。Certara.AI 具备理解复杂数据类型的能力；发现科学家只需花费更少的时间进行琐碎的计算分析和研究任务。
Exploration Research and Discovery
There is a huge amount of data to model, 3D seismic data, data from drilling and logging, production data, etc. from hundreds of wells in large areas over a thousand kilometers, all that data is critical to the success of exploration. AI can reduce the number of failed wells. There is especially high exposure in oil and gas exploration where annual investment levels can be upwards of a billion dollars, and where typical drilling success rates are in the low range 10-50%.
The exploration wells fail more often than they succeed. AI technologies can optimize field development from exploration to production, enabling effective and efficient interpretation of seismic data to identify hydrocarbon deposits, as well as identify optimal locations for drilling operations.
Wellbore Integrity – Preventing Unintended Losses and Accidents
Well integrity refers to always maintaining full control of fluids within a well, to prevent unintended fluid movement or loss of containment to the environment/ Well integrity policy defines commitments and obligations to safeguard health, safety, environment, assets, and reputation. The use of AI would be a great advantage because the growing demand to assess the integrity of downhole casings and proactively predict their failures is of a prime importance. Being able to analyze downhole metal loss data from logged wells is a challenge by itself. Predicting the metal loss profile for non-logged wells is yet more challenging. In huge oil fields, where the number of wells can exceed two thousand, practicality is given a significant weight during the corrosion logging candidate selection process. Downhole corrosion is the main threat to the integrity and upkeep of wellbore completion tubulars. Poor cement bond behind casings promotes and accelerates external corrosion growth.
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Upstream, Midstream and Downstream Solutions
Understanding and controlling subsurface microbiomes
There is interest in studying the native microorganisms in reservoirs, how they are affected by drilling and fracking operations, and how their numbers and activity could potentially be controlled through biocides or other means. This could help optimize production.
Controlling geochemistry
Understanding and manipulating geochemical reactions during fracking and production at the nanoscale was seen as an opportunity, as geochemistry impacts scaling, precipitation, clay swelling, and more.
Coating materials for pipelines and equipment
Anti-corrosion, anti-scaling, and other coating technologies could be advanced from a materials science perspective. Maintaining heat during initial hydrocarbon transport from subsea wells to offshore platforms is critical to prevent cooling, separation, and blocking. Advancing syntactic polypropylene and other insulation coatings could benefit this application.
Strengthening proppants
Tailoring chemicals or materials to modify the strength of proppants could enable fracking of less brittle rock formations. Formulations must also consider safety and environmental effects.
Carbon tracking
Data based carbon tracking, sequestration and tracing of carbon as part of environmental and economic re-usage of carbon in various drill and extraction projects.
Performance and failure detection of BOP
Perform data based analysis for determination of elastomer performance in BOP; determine optimum inspection frequency and assess material performance under intense environmental conditions to optimize maintenance, recertification and downtime.
Hydrophobic, low-friction coatings
Coatings that prevent buildup and blockage from waxes, hydrates, etc. and promote smooth fluid/gas flow could realize significant efficiencies for production and transmission. Improving existing technologies like liquid repellent coatings are discussed as use cases.
Optimization through energy consumption
AI models to improve the refining operations and reduce energy consumption. AI-led technology can predict the performance of refineries and identify areas where energy efficiency can be improved. What additives and equipment to use to manufacture a clean and efficient fuel is one of the biggest challenges for any company that is dedicated to refining.
Fuel formulations
AI models are effectively used for predicting complex phenomenon of efficiently burning fuel formulations and offers ways to achieve more effective combustion stability control. Producing efficient as well as clean fuel is one of the challenges that supermajors like ARAMCO are currently working on.
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