Metrics-based methodology can be applied to create a ‘scorecard’ system to quantify progress throughout well planning, engineering and drilling
By Stephen Whitfield, Associate Editor
While the digital transformation has led to major advancements in the oil and gas industry, so far technologies such as cloud computing and digital twins have not been heavily leveraged to progress ESG goals. One opportunity, according to Robello Samuel, Chief Technical Advisor and Technology Fellow at Halliburton, is to apply digital technologies to quantify the sustainability of a well, in real time, starting from when it is designed through to its drilling and completion.
Speaking at the 2021 IADC Sustainability Conference on 9 February, Dr Samuel presented the concept for an artificial intelligence (AI)-based methodology – what he called a “sustainability index” – to estimate and display sustainability in well design and operation. The index is a weighted multidimensional model grounded in engineering principles that enables optimal decision making with regards to sustainability. Dr Samuel described the methodology as a collection of well-level “report cards” that can be used to measure key performance indicators (KPIs).
“We’re implementing environmental protections, but we need a scorecard, or some kind of indicator that we can use as an intrinsic reference, so that we can actually quantify the progress that we’re making and bring ourselves into the next level of good corporate citizenship,” Dr Samuel said.
The concept of a sustainability index is not new; many companies in different industries, including oil and gas, use them as a way to measure overall progress toward environmental sustainability. It is meant to simplify the complex decision-making processes that make a company more sustainable, aggregating relative information about the sustainability aspects of various decisions, strategies and approaches, and then distilling that information into an easy-to-understand scoring system that quickly determines the most sustainable options.
The proposed sustainability index, Dr Samuel said, would introduce a three-way coupling system incorporating physics and data science with an uncertainty model to provide comprehensive analysis of the sustainability of various activities during the life cycle of a well. He described the model as an expandable system that users can customize to suit their needs.
The index uses modules, which Dr Samuel referred to as the “seven pillars,” to measure the impact of an activity on sustainability:
• Environmental impact, primarily involving carbon emissions;
• Societal impact;
• Health and safety impact;
• Well design and engineering;
• Functionalities and optimization;
• Well cost and maintenance; and
• Miscellaneous impacts on sustainability.
Dr Samuel said these pillars are all interconnected. A reduction in the carbon footprint has a societal impact; likewise, the health and safety impact of an activity, well design and engineering affects functionality and well costs. This interconnectivity must be reflected in the comprehensive sustainability index. In the model that Dr Samuel described, real-time data, static data and sustainability actions are entered as inputs into physics-based and data-driven models, each of which shares data with a third model incorporating numerical uncertainty.
The use of physics- and data-based models provides a more comprehensive insight into a physical system; the mathematical framework used to describe the system in a physics-based model can be used to teach the data-driven model how to use real-time data to predict the system’s behavior. Uncertainty in each model has been extensively studied and can be taken into account during the design and operation of the system.
Traditionally, sustainability indices have utilized a variety of methods to calculate the values of an indicator, such as a simple scoring method, where people assign numerical values to specific actions, or the fuzzy logic approach, which allows for multiple values to be processed through the same variable. But for a process with as much complexity and uncertainty as the design and drilling of a well, Dr Samuel believes a simple scoring method is insufficient.
“If you look at a simple system where you assign values and weights, that may be easy to do with a model that has 10 variables or less, but we are dealing with a lot of variables when it comes to the well. If you take surveys, downhole tools and other things, you see a lot of components going into the operation of a well. We need to go into another option.”
The proposed model uses a neuro-fuzzy system – a combination of fuzzy logic and an artificial neural network – to estimate sustainability values. Such a system effectively emulates the operation of the human brain, with the neural network concentrating on basic functions and the fuzzy logic system emulating symbolic reasoning. This system analyzes the data outputs generated from the coupled models to provide scores for any given activity over the lifetime of a well, with the seven pillars serving as the basic criteria for users to determine what they may need to change.
Dr Samuel said the neuro-fuzzy system gives the model a degree of flexibility, as it can adapt to the data provided over the lifecycle of a well and adjust the importance it gives to various pillars and their subsets in calculating a score.
“With the neural network, you can find out which indicators are dominant and which are weak. The weak ones can get dropped down in importance as we get more and more data. It takes time, but there is no penalty in making all of these computations,” he said.
An activity with a score between 8.50 and 10.00 is considered sustainable and requires no additional change. A score between 7.00 and 8.49 points indicates an activity that approaches sustainability and requires little to no change. Weak sustainability falls between 3.50 and 6.99 points, and any activity less than 3.50 points is considered unsustainable and requires significant change.
Sustainability scores can help companies modify their activities to limit the emissions impact from their operations, Dr Samuel noted. “When we’re planning a well, this index provides all of these indicators, which is essential information. It can affect how we design things, how we optimize things. It provides an opportunity to infuse new ideas. Because we can couple all of this data, all of this new information coming in, the index will give us an overall picture on how we’re doing things.” DC