Live & Online Conference 28 & 29 January 2025, Houston Tx.
A significant transformation! For 2025, the core Wellsite Automation Conference has been completely revamped and co-located with the Drilling Automation and Technology Conference. This integration provides a comprehensive view of the entire lifecycle of oil and gas operations and automation—from drilling to production and facilities management—exploring what can be automated and how systems can be seamlessly integrated.
Personalize Your Agenda: Deep Dives into Core Automation and Integration
The 2025 agenda will cover a broader range of topics, diving deeper into core automation over three days. Attendees can customize their experience by selecting sessions that match their interests. Strategy heads may focus on top-line updates and project progress, while technical engineers can explore detailed protocols and integration approaches.
Interactive Roundtables and Case Studies: Driving Innovation in Automation
We are placing a stronger emphasis on integrating roundtable discussions into each session while retaining strategic panels and case study discussions. Additionally, there is a significant focus on reducing methane and carbon emissions, with automation playing a key role. Methane sensors and remote monitoring systems, which are essentially automated technologies, will be highlighted. Day one’s strategy sessions will explore optimal approaches for automating many aspects of emissions monitoring and reporting.
Cybersecurity in Focus: Guarding Against Digital Threat
Cybersecurity workshops are also crucial this year. With the increasing digitalization of operations, cybersecurity has become a top priority. Implementing advanced security protocols is essential to protect against cyber threats and ensure data integrity.
Critical Success Factors: Tackling Technical Integration Challenges
Day two’s technical integration sessions are essential for the success of wellsite automation projects. These sessions will focus on real-time data processing, local analytics within edge systems, and strategies for combining data sources to enhance situational awareness and decision-making. Addressing technical integration issues is critical; otherwise, projects can become difficult and costly to implement.
Standard Protocols for Seamless Automation: Bridging Different System
On these more technical days, we’ll explore the industry’s shift towards standardized protocols for automation, which facilitate better interoperability between different systems and equipment from various manufacturers. Discussions will include the integration of programmable logic controllers, SCADA systems, and various communication networks, such as the Industrial Internet, wireless networks, and the Internet of Things. Additionally, data management and analytics, including data acquisition systems, cloud platforms, and edge computing, will be thoroughly covered, particularly on day three.
Harnessing AI & Machine Learning: Real-Time Analytics for Better Decisions
On day three, we'll explore the integration of AI and machine learning with automation systems, focusing on real-time data analytics and improved decision-making. We'll provide updates on how companies are handling edge computing versus other methods.
Ensuring Data Accuracy: Automated Quality and Management Systems
Automated data quality and management, including data cleansing and validation, are also critical topics. We’ll examine how automated systems can ensure data used for analytics and decision-making is accurate and reliable.
We do look forward to meeting you in person this January to explore these exciting developments and innovations in wellsite automation.
Presenting how real-world examples are demonstrating significant cost reductions and increased profitability through automation, with metrics such as reduced downtime and improved efficiency.
Showcasing scalable automation solutions being implemented in phases, highlighting modular systems that can be easily upgraded or expanded to match operational growth.
Highlighting specific tasks like remote monitoring and predictive maintenance that are being automated to streamline operations, reduce headcount, and maintain output.
Sharing insights into effective change management with training programs for employees to handle automated systems and strategies to re-skill and redeploy workers.
Discussing the regulatory landscape and how automated systems are efficiently meeting compliance requirements, with examples of successful integration.
Presenting challenges faced, solutions employed, and measurable benefits achieved by companies successfully implementing automation.
Offering live demonstrations showcasing the reliability and impact of automation technologies on operational efficiency.
Deploying IoT sensors and edge computing to continuously monitor emissions in real-time, ensuring accurate data collection and regulatory compliance.
Using automated compliance management systems updating regulatory requirements and ensuring operational adherence to changing regulations.
Utilizing advanced analytics and machine learning to identify and quantify emission sources accurately, aiding in compliance and reduction strategies.
Implementing automated reporting systems compiling and formatting data according to regulatory standards, ensuring timely and accurate submissions.
Deploying energy management systems optimizing energy use through automated control and real-time analytics, reducing overall emissions.
Implementing standardized data formats and protocols ensuring compatibility and ease of data exchange across various systems and devices.
Adopting open standards and interoperability frameworks enabling different systems to communicate effectively.
Using middleware solutions and API gateways to bridge the gap between new automation technologies and existing legacy systems.
Utilizing edge computing to process data locally at the wellsite, reducing latency and ensuring timely decision-making.
Implementing robust cybersecurity measures, including firewalls, encryption, and intrusion detection systems, to safeguard data and operations.
Presenting challenges faced, solutions employed, and measurable benefits achieved by companies successfully implementing automation.
Designing systems with modular architecture allowing easy expansion and scalability as needed.
Deploying redundant communication networks and failover mechanisms to ensure continuous operation even in the event of network failures.
Choosing vendors supporting open standards and interoperability, allowing flexibility to switch or integrate different technologies as needed.
Implementing automated update and maintenance processes to keep systems current without disrupting operations.
Using standardized communication protocols and message brokers to facilitate inter-system communication and data exchange.
Conducting comprehensive interoperability testing in controlled environments to identify and resolve potential integration issues.
Utilizing data integration platforms and ETL (extract, transform, load) tools to consolidate data from disparate systems into a unified database.
Using edge computing and real-time analytics platforms to process data locally and quickly.
Utilizing scalable cloud storage solutions and data management frameworks like data lakes and data warehouses.
Implementing AI and ML models to analyze data for predictive maintenance, anomaly detection, and optimization.
Using advanced visualization tools and dashboards (e.g., Power BI, Tableau) to present data insights clearly and interactively.
Establishing data governance frameworks and compliance protocols to manage data integrity, access, and usage.
Designing data architectures with scalability in mind, leveraging cloud services for elastic scaling.
Implementing data lifecycle management practices, including regular archiving and purging of outdated data.
Implement data cataloging tools and metadata management systems to improve data discoverability and context.
Develop change management strategies, including training and communication plans to handle system upgrades and process changes.
Optimize data storage and processing costs through efficient data management practices and leveraging cost-effective cloud services.
Using workflow automation tools to create end-to-end automated data processing pipelines.
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