Artificial intelligence

Mud gas and cuttings analysis remains at today the only direct measurement of, respectively, the reservoir fluid and rock, until a PVT sample and a core are available for laboratory analysis. Surface logging data is an attractive solution for the client to take real-time decisions as they are available while drilling, on a continuous basis and at relatively low cost. Nowadays the accuracy and quality of the surface logging data has reached a level comparable to more sophisticated downhole tools thanks to the technological evolution, processes automation and innovative digital workflows. In this presentation we will describe how Artificial Intelligence and Machine Learning models and ground-breaking algorithms permit a more quantitative and objective approach to determine lithology classification, enhance the accuracy of the mud gas data even in extreme drilling conditions and enable predicting fluid properties while drilling.

Efficiency of existing operations and investments in upstream oil and gas requires a new approach. Cleaner, safer, more efficient energy production is needed to meet increasing demand while reducing emissions. Artificial intelligence (AI) and machine learning will play a pivotal role in unifying siloed upstream data and better optimizing field operations to meet these needs. In this webinar, World Oil editor Craig Fleming hosts a discussion about the state of digital adoption in upstream oil and gas, the complexity of adopting and scaling AI, and examples of how AI is being applied today for improved outcomes.

Advances in drilling technology increasingly require collaboration by traditional drilling players with partners outside the core of the oil & gas industry. Identifying who can provide the missing innovation pieces – whether it is a technology company to develop software for an advanced exploration system, or an academic researcher with expertise in an obscure chemical discipline – is a critical step for innovation in drilling. Join PatSnap to learn how connected innovation intelligence tools and techniques can be used to empower the drilling industry to discover and collaborate with the best possible partners.

Come and discover how our ready to run service enables seamless connection to AI and domain applications for faster and improved decisions. Learn how all the tools needed to automate data loading, quality control, governance, discovery, sharing and consumption are built into a single environment that can be deployed globally through strategic partnerships.

Oil and Gas companies are investing in applications to analyze data in real-time and improve the business performance. That investment involves computing platforms that are reliable in harsh environments where oil and gas assets exist. Streamline Innovations will share their application of advanced technology and how they are enabling clients to meet environmental objectives. Hear from Peter Photos, Streamline Innovations and Corie Allemand, Stratus Technologies on digital initiatives that increase efficiency, safety, and profitability. Join us for a discussion on: -Streamline Innovations use of advanced applications -ROI of Edge Computing for Streamline -Redundancy and virtualization in Edge Computing

A thousand alarms but only one important event. This is the reality facing many operators of electric submersible pumps (ESPs). With so much reliance on people rather than digital tools to prioritize events, it is difficult for field engineers to respond to the most important. The disparate, hit-and-miss analytics of slow-loop systems makes it difficult for operators to identify ESP issues and respond to them in a timely manner. Sensia AiRP captures, prioritizes, resolves, and reclassifies ESP events in an integrated environment, creating a single-view workflow that brings together the latest advances in AI and powerful data visualization to automate the prioritization process. By automatically and intelligently analyzing ESP events in real time, AiRP empowers you to boost operational efficiency, optimize lift, and minimize downtime by significantly cutting the response time to potentially harmful events. This solution harnessing Sensia’s full capabilities represents the first step towards lift autonomy.