Digital Transformation

Number of drilling advancements at both the rig and down-hole levels have helped producers reach targets previously impossible to consider. However, the key to unlocking full digital transformation across the oil and gas sector will involve both soft and hard automation technologies as well as require more nimble work practices. Along with challenges of implementing digital change, there are also enormous opportunities for substantial cost reductions(especially for oil and gas companies that have already undertaken significant cost reductions in recent years), better safety, and sustained productivity improvement.

Well construction and intervention accounts for typically 40 percent—and often as much as 70 percent—of an oil or gas company’s capital spending. For this and other reasons, that area is widely recognized as the most critical and complex operation to “get right” in the entire oil and gas value chain. Furthermore, drilling and well activities are highly complex, happening in an environment with significant health and safety risks and often involving an intricate web of interfaces in which ten or more suppliers are working together to deliver a single well (reference :
A new operating model for well organizations – McKinsey).

The good news is that emerging technologies will bring significant opportunities to improve all aspects of the operating model for wells, from streamlining core processes to strengthening front line capabilities to improving the overall organizational model(significant operational changes), including the all-important supplier interface.Companies can use occupational safety databases and/or offset well data during planning pointers to predict HSE events for planned and ongoing activities. Advances in robotics will also improve safety through the replacement of human operators in hazardous environments, putting people out of harm’s way to improve health, safety, and environmental (HSE) performance.

Drilling Automation – Enabler’s

In my previous posts we looked at what is Abstraction, and what it mean in E&P. some components already discussed in my previous posts which is about

Advanced analytics supported by new capabilities—like more connected data platforms—can improve subsurface activities like well placement, well design, and full-field development planning. In many ways, this approach lays a foundation for significantly lower costs and better well productivity.Using advanced analytics and digital ways of working can reduce the numerous interfaces and handovers among functions and individuals. Digitally enabled logistics planning and procurement execution can help ensure that trucks and vessels show up on time and with the right equipment. Furthermore, clients are already digitally monitoring suppliers to ensure that the right materials are delivered on time and the price charged matches that in the contract documents.

Digital transformation is not only about technology. It requires a holistic approach to transform operations – such as changes to existing workflow, operations and business models.

Lets take a look at what are the main enabler’s

• Smart Rig – Improving drilling system performance & efficiency by mechanization,automation and bringing main subsystems like The fluid system, bits, BHA together along with smart sensors ( surface and sub-surface measurements especially with closed-loop along with MPD )
• Cost efficient well construction process – optimizing work flows by removing non critical events(which are not contributing to ultimate goal) from critical path so that we can reduce NPT, flat time and improve operational productivity
• Software – Plan a WELL in the current digital cognitive environment, will give an opportunity to allow the past data and inputs that provided, and then execute that plan(digital drilling program) through orchestration and automation(cost efficient well construction optimized work flows), while constantly recording all the data.Then evaluate each operational task by making sure it adherence to plan (ensure any deviations are highlighted and managed) while considering risk and contingencies, also re-plan as needed(for managing UN-planned events). This data then becomes integrated into the learning process When the next well is being designed, which becomes continuous improvement cycle (plan-execute-evaluate-learn).
• Improve the crew competency (more digital and multi skilling) – Optimized well construction process with smart rig requires different skill set(some of the current competency is not needed anymore because of smart rig with automation) especially opportunities like lot of operational tasks can be executed from a remote location(real-time enabling, support multiple rigs).

The elements of drilling automation

• Extensive and diverse offset well data sources for different domains (fluids, cementing, casing…) for planning a well. Real time sensor data, manual measurements, logs, process/tasks, events while drilling.
• Real time processing of data while drilling at the rig, also transmitting data to a remote location
• Rule application and Pattern recognition that enforce leverage and/or discover context while uncovering regularities and normalities in the data. These can be but need not be specific to the domain. Apply rules and patterns does change the state of the world.
• Domain Algorithms that leverage Oil and gas domain expertise to intelligently interpret and apply the rules and patterns, as dictated by an organization’s data ( models – follow the physics behind it first) and its desired outcomes. These algorithms enable to achieve specific goals like Optimization of drill path, ECDs, Drill string vibrations..etc. in both while planning a well and during execution.
• Machine learning that can automatically alter or create new algorithms based on the output of algorithmic analysis and new data introduced into the system. Keep it in mind to stick to a hybrid model such that to follow the physics behind it first, then use the data to adjust
• Artificial Intelligence that can adapt to the new and unknown in an environment
• Automation, which uses the outcomes generated by the machine learning and/or AI to automatically create and apply a response or an action

Digital transformation technologies can leverage to increase the operational productivity, to reduce NPT (non productive time) and have a meaningful impact on well costs. Also in-order to have successful abstract tasks/actions in E&P, we have to find a way to in-co-operate human interference in the above paradigm,