• Due diligence/contract negotiation
• Contract award (including third-party service contracts) and project initiation
• Well planning/engineering phase
• Mobilize project management team
• Obtain well proposal and information on offset wells
• Define basis of design and conduct peer review
• Develop risk management plan
• Obtain regulatory permits (quality assurance and HSE compliance)
• Prepare AFE and drilling schedule
• Procure tangibles and plan logistics of equipment and personnel
• Conduct "Drill Well on Paper" exercise
• Project execution phase
• Deploy field team
• Monitor and supervise drilling operations
• Maintain risk register
• Issue amendments, when necessary, and progress reports
• Well delivery
• Conduct "After Action Reviews"
• Issue End of Well Report
• Demobilize

Machine Learning and Artificial Intelligence (ML/AI) Models

There are enormous advantages in applying Machine Learning (ML), Artificial Intelligence (AI), Big Data, Industrial Internet of Things (IIoT), cloud and edge computing technologies to oil and gas industry processes. These include geology, drilling, production, and facility engineering. Companies make decisions using unstructured, semi-structured and structured data. For example, when planning to drill a new well, engineers and geoscientists scour through historical information in the form of text: logs, PVT, production, drilling records and laboratory tests; and images from image logs and cores.

Applying these technologies will reduce the huge amount of information operators are required to analyze in making critical business and engineering decisions. But decisions made from image and numerical data can be subjective. Combination of Machine Learning, Artificial Intelligence and Big Data technologies will provide valuable insights and result in more objective decisions.

How does Laurel leverage these technologies to deliver data driven solutions?

Cloud Computing and Big Data: Cloud powered scalable and distributed big data resources to ingest, process (batch or real time), store, search and manage the data.

IIoT and Edge Computing: Record telemetry data, monitoring, controlling and applying algorithmic intelligence on equipment located remotely with limited internet connectivity and critical operations that require very low latency network.

Artificial Intelligence and Machine Learning: Proprietary algorithm ingrained with subject matter domain expert tailored for specific play/field/reservoir/well/facility.

All IT Systems: Generate and integrate secured root certificate, private and public encryption keys for all IT processes and even consider integrating ML/AI algorithms to filter bad actors proactively.

 

Drilling Domain ML/AI Models

1. Custom Machine Learning/Artificial Intelligence (ML/AI) drilling engineering-based data products developed to:
   1. Establish the significant variables that cause ILT and NPT
   2. Ascertain Static and Dynamic ROP to reduce drilling time and cost
   3. Select Cost-effective BHA assembly for the drilling program to reduce NPT
   4. Conduct Batch or Real time model refresh
   5. Generate and attach secured encryption keys to process
2. Distributed Cloud storage to host drilling data:
   1. Allow easy and seamless big data and analytics operations on future drilling or related projects
   2. Allow drilling data distribution and collaboration amongst all stakeholders
   3. Provide easy and seamless backup and archiving of drilling data with retrieval within 1-5 minutes
   4. Easily upload drilling big data acquired from the project or other projects to the cloud in batches using Laurel's industry leading data guzzler, thereby, saving PEASD costs of writing data to the cloud
   5. Establish resilient disaster recovery protocol to ensure no loss of drilling data
   6. Provide on-demand scalability of cloud storage resources: Reduce cost to spin up a new server to incorporate additional data
   7. Provide ease of storage integration with third-party applications (Mobile, web-based, enterprise, drilling contractor vendor-based)
   8. All above and more with 99.99% availability backed by a Service Level Agreement
   9. Generate and attach secured encryption keys to process
3. Distributed Big Data Processing of drilling data:
   1. Provide easy and seamless incorporation of real time or near real time telemetry data from sensors
   2. Reliably persist and merge drilling data from all sensors in real time
   3. Generate and attach secured encryption keys to process
4. Distributed Big Data Search:
   1. Mine significant relationships from big drilling data from a well, field, even fields without an ML/AI model
   2. Easily search all drilling data- numbers, text, images stored in Laurel's custom storage solution in a blink: Quickly identify drilling events without going through traditional drilling reports
   3. Generate and attach secured encryption keys to process
5. IIoT and Edge Computation:
   1. Provide architected and sourced electronic components and device to fulfill project requirements
   2. Configure edge computation on device to effectively utilize local resources, reduce network costs and deploy (refine/refresh) ML/AI models for swift monitoring and control of critical drilling events
   3. Integrate drilling equipment sensors, actuators and valves with Laurel Edge device
   4. Generate and attach secured private and public encryption key pairs to process