Why relying on static data will see the oil and gas industry stuck in the past

Prad Thiruvenkatanathan, November 02 2020

The oil and gas industry’s approach to data is ready for a revolution.

That is the argument in our white paper ‘Raising recovery rates in real-time using in-well fiber optic sensing’, which we published in October 2020. In this paper, we explain why the industry’s current approach to data is out of date, how this harms oil and gas firms’ returns by millions of dollars each year, and how the sector needs to change.

We have explained in previous post why oil and gas companies base their decisions on how to manage their hydrocarbon wells on data acquired using wireline logging every few years.

These insights are then used to inform operational decisions for several years to come, even though the performance and condition of the well may well change massively over that time.

Why is this a problem?

You would not expect financial traders to make multi-million dollar buy or sell decisions based on stock valuations that are even a week old. Why then are oil companies using data showing how their well was performing years previously to inform decisions on how to optimize it for production today?

It’s baffling, especially when you consider the production impact of common challenges like sanding, well integrity, and accurate flow profiling. All of these challenges have a significant influence on the performance of a well.

Flow profiling, for example, is crucial to an operator’s understanding of inflow and outflow in their wells, both of oil and gas but also unwanted water or sand. Profiling shows which wells are operating flawlessly and those with issues such as sand or water ingress that need attention.

Flow behaviour is dynamic and complex, and an operator relying on a snapshot of data gathered years previously will not see this. A historical snapshot of data simply cannot give an operator an accurate idea of which wells are operating efficiently and those with issues that need attention now.

To properly understand flow dynamics, an operator needs to know the where, why and how much of what is being produced – but, most importantly, they need to know the ‘when’. In our white paper ‘Raising recovery rates in real-time using in-well fiber optic sensing’, we set out a comprehensive plan for operators to discover this “when”.

How can the industry improve?

In this paper, we explain that it is possible to gain real-time insights into how hydrocarbon assets are performing using data gathered from fiber optic networks overlaid with ‘hybrid analytics’ - a new breed of data analytics where we fuse the power of machine learning with decades of physics-based knowledge to inform decisions in real time.

These insights enable companies to identify and prevent sand or water ingress and even spot well integrity anomalies as – or even before - they develop, and thus optimize the performance of their assets in real time. This can generate a major boost to their bottom line.

We outline how the real-time element of LYTT’s analytics, enabled by our physics-infused machine learning and cloud capabilities, allows operators to make better decisions about how to optimize inflow from different parts of the well and detect unwanted breakthroughs of water and gas as and when they happen.

In short, LYTT’s real-time analytics is allowing the industry to finally move away from its reliance on snapshot data, enabling a real-time data revolution in the way wells are managed, boosting returns to the tune of hundreds of millions of dollars while improving safety and efficiency.


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