Pre-Event Workshop:

Understanding large language learning models (ChatGPT),
the applications, and benefits across oil & gas operations

Wednesday, September 13 – Hilton Americas (Houston, TX)

Cost: $700

The Facilitator

Alec Walker

About the Workshop

Over the last several months, Large Language Models (LLMs) like OpenAI's ChatGPT have taken the news by storm, creating a variety of solid responses across the industry ranging from concerns over data privacy and job security to excitement over impending boosts to productivity and innovation. The strength of these reactions correlates with the universally recognized capabilities of the LLMs: they can answer questions with uncanny accuracy and with a profound appeal to context. While uncertainty looms, some organizations in the industry are already using the models, building, and deploying tools to optimize processes, enhance decision-making, and make predictions.

This workshop is designed to catch participants up with these trends and tools. While some of the material covered will relate to very technical concepts, the workshop is intended to be suitable for non-technical audiences. They will be given intuitive and non-mathematical derivation and interactive examples whenever technical topics are being covered. This approach ensures that participants come away with a unique and valuable understanding without having to become experts in the subject matter.

The workshop begins with an overview of the relevancy of LLMs to the oil and gas industry, including who needs to know how they work and how they are used. Whether you're a geologist analyzing seismic data, an engineer optimizing drilling operations, a manager overseeing complex logistics, or a C-suite executive guiding strategy, understanding LLMs and how to effectively utilize them can be a game-changer. This workshop will demystify the inner workings of these tools, enabling you to make informed decisions about their implementation in your day-to-day operations.

Next, the workshop will offer an intuition into the inner workings of large language models suitable for audiences without a technical background. Predominantly, this section will explore a particular type of deep learning methodology called a transformer, which is a vital element in the architecture of LLMs. Transformers have revolutionized the field of natural language processing. They evolved from convolutional neural networks (CNNs) initially designed for image recognition tasks. The limitations of CNNs in processing sequential data led to the advent of transformers. These new models have allowed for parallel processing of sequence data and efficient handling of long-term dependencies, making them well-suited for tasks involving large amounts of text.

The immense power of LLMs can also present challenging trade-offs between deriving insights and ensuring data security. We'll delve into this complex landscape, discussing strategies for protecting sensitive information while harnessing the computational power of LLMs. This includes applying differential privacy techniques, federated learning, and data anonymization approaches to ensure robust data privacy. It also has an overview of assessing potential business partners in the space.

Finally, we'll explore various applications of LLMs across everyday use cases in the oil and gas industry. We encourage you to bring your ideas for use cases. LLMs can be used for various tasks, including document summarization, predicting operation needs, or enhancing safety protocols. Throughout this section, the workshop will offer an overview of best practices on key techniques used in the successful application of LLMs: fine-tuning and prompt engineering.

  • Fine-tuning allows us to adapt pre-trained LLMs to specific tasks or datasets within your organization. This can save significant computational resources compared to training a model from scratch while still delivering highly accurate results.
  • Prompt engineering involves carefully designing inputs to elicit the desired response from a pre-trained model, a crucial skill for effectively harnessing the capabilities of LLMs.

By the end of this workshop, you should have a comprehensive understanding of how large language models function and how they can be applied within your organization. We're excited to help you unlock the potential of these powerful AI tools, enhancing efficiency, accuracy, and productivity within the oil and gas sector.


Why Attend:

  1. Demystify LLMs: Gain an in-depth understanding of large language models, breaking down the complexities of these AI tools into practical, understandable concepts.
  2. Industry Relevance: Discover LLMs' specific relevance and potential within the oil and gas sector, illuminating pathways to improved operational efficiency and strategic decision-making.
  3. Transformers Explained: Understand the evolution and functionality of transformers, which lie at the heart of modern large language models.
  4. Data Security: Learn strategies for leveraging the power of LLMs while maintaining data privacy and security, ensuring your organization's sensitive information is protected.
  5. Fine-Tuning Techniques: Acquire practical skills for fine-tuning LLMs to adapt them to specific organizational tasks or data sets, saving time and computational resources.
  6. Prompt Engineering: Learn the art of prompt engineering, a key technique for designing effective inputs that elicit desired responses from pre-trained models.
  7. Application Scenarios: Explore real-world use cases of LLMs within the oil and gas industry, gaining insights into how these models can be effectively deployed.
  8. Networking Opportunity: Network with industry professionals, AI experts, and peers, fostering valuable connections and collaborative opportunities for the future.


Who Should Attend:

  1. Geologists: Professionals in the oil and gas industry who want to understand how AI and LLMs can help in data analysis and interpretation tasks
  2. Engineers: Petroleum and drilling engineers looking to optimize operations, increase efficiency, and reduce risks with the help of AI and LLMs
  3. Field Workers: Individuals involved in on-site operations which can leverage AI for better decision-making, safety, and maintenance planning
  4. Operation Managers: Professionals overseeing logistics, operations, and project execution, who want to explore how LLMs can streamline processes and improve forecasting
  5. C-Suite Executives: CEOs, CIOs, CTOs, and other executives in the oil and gas sector interested in leveraging AI for strategic advantages and organizational growth
  6. Data Scientists and Analysts: Professionals in data-centric roles within the oil and gas industry looking to upskill in AI and LLMs for industry-specific applications
  7. IT Professionals: Those implementing, managing, or supporting AI initiatives within their oil and gas organizations
  8. Research and Development Professionals: Individuals involved in R&D within the oil and gas industry, particularly those exploring AI and machine learning solutions
  9. Consultants: Individuals or entities providing strategic or technical advice to oil and gas companies who would benefit from a deeper understanding of the capabilities of AI tools like LLMs


Workshop Agenda:

9:00-9:40 Section 1: LLM Relevance in the Oil & Gas Industry

  • How LLMs came about
  • Who are the major players are
  • What is going to change
  • How should we prepare for a new mainstream
  • How can we be ahead of the curve


9:40-11:20 Section 2: The Inner Workings of LLMs

  • A brief overview of machine learning
  • History and intuitive explanation of convolutional neural networks
  • Background of natural language processing and text analytics
  • Intuitive description of transformers and large language models

11:20-11:40 Networking Break

11:40-12:30 Section 3: Organizational Navigation of LLMs

  • What the data privacy and data security risks are
  • What are the methods to overcome or circumnavigate these risks
  • Different strategies for deployment and their comparative advantages


12:30-1:30 Lunch

1:30-3:00 Section 4: Applications of LLMs

  • How to set up and use LLM personal accounts
  • How to deploy LLM models in personal applications
  • Best practices for fine-tuning
  • Best practices for prompt engineering

3:00 End Workshop