In the presented approach to deploying tripping automation, a team consisting of operator, drilling contractor, and drilling equipment OEM collaborated to successfully deploy and improve the well construction process. The tripping process was upgraded with new software and through extensive training, offshore support, and continuous improvement, the rig was able to operate in a more automated mode as well as enhancing the safety by improving tripping hierarchy of control.

This presentation examines in detail the mathematical basis for well test interpretation, starting with the concept of an ideal reservoir model and the partial differential equations used to describe single-phase and multi-phase flow in porous media.

The University of Texas at Austin has been working on advanced sensor technologies over the last 6 years in a bid to improve the safety and efficiency of drilling operations, and to reduce uncertainty with regards to data and situational awareness.

This webinar will cover the process of building a Real-Time Big Data Analytics environment and highlights key learning and challenges from this endeavor.

The process by which organic matter decomposes deep underground to form petroleum and its underlying kerogen matrix has so far remained a no man’s land to theoreticians, largely because of the geological (Millions of years) timescale associated with the process. Using reactive molecular dynamics and an accelerated simulation framework, the replica exchange molecular dynamics method, we simulate the full transformation of polymers such as cellulose and lignin into kerogen and its associated fluid phase under prevailing geological conditions. We observe in sequence the fragmentation of the cellulose and lignin molecular crystals and production of water, CO , CO2…, the development of an unsaturated aliphatic macromolecular phase and its aromatization.

A ROP optimization methodology is presented, using offset drilled wells data. Data is used to train a neural network model for different rock properties which is presented in the vertical section of the reservoir. By changing the drilling parameters like Weight on Bit, Rate of Penetration (ROP) for the target well is optimized.

Wellbore tortuosity is a critical element in drilling complex horizontal wells and deep verticals. The current three-dimensional borehole trajectory model, based on the minimum curvature method [MCM], tends to mathematically smoothen the wellpath.

This presentation describes the development of a well-site automation system consisting of an open data aggregator, with networked surface and downhole sensors and real-time applications for process monitoring, advice and control.

AI applied to object recognition and image processing has developed to a level of sophistication whereby the task of drill bit forensics can be fully automated – and a lot of the subjectivity removed from the process. Researchers at The University of Texas at Austin have in recent past developed algorithms to perform drill bit forensics directly from bit images captured on mobile phones. This is a four step process involving the recognition of the cutters on the drill bit, the grading of the cutters, detecting the location of the cutters on the drill bit and finally providing an overall evaluation of the bit. This webinar will go into details of the approach pursued, and will provide guidance on what we can expect in the near future.

When using analytical data in real-time to produce predictive answers and situational awareness, having confidence in the data is paramount. This webinar will discuss a few examples of the impact of low quality of acquired data and how it will errode the confidence needed to make real time decisions. We will further discuss a few examples of how data can be assessed for appropriate use and a few techniques to augment this data when answers are needed. This webinar helps show how a company can use open standards-based solutions like the proposed Energistics Data Assurance process to qualify data for use in the analytical and decision making processes.

This webinar explains how deviated wellbores are drilled automatically with a rotary steerable system. The automation system used is capable of predicting the wellbore trajectory, deriving steering proposals to follow the planned trajectory closely or steer back to plan, and submitting those steering downlinks automatically to the downhole RSS with the directional driller observing the system. During the webinar, we explain the underlying control methodology and the automation system architecture. Furthermore, operational considerations as well as sensor and actuator influencing factors are discussed. The concept of embedding the driller and directional driller in the decision-making workflow is outlined. Finally, the performance of the automated trajectory drilling system is assessed and case studies are presented, where up to 98 % of a single wellbore has been drilled automatically.

With the implementation of new technology on deep-water units, there have been huge strides made towards a safer and more efficient way of drilling wells. However, with the introduction of these advancements different challenges also arise. In fact, as new technologies are introduced, the more important team skills, or Crew Resource Management becomes.

The webinar discusses newly in-house developed and implemented a set of scientific modules for Drilling kick detection and well control. This involves case studies and their business impact on drilling safety and efficiency.

Content for this webinar is provided by Baker Hughes. By registering, your contact information will be shared with the sponsor.

The offshore Wheatstone LNG Project in Western Australia utilizes subsea big-bore gas wells as the preferred method of producing the field.