In the high-stakes world of drilling operations, every second counts, and every decision can have significant implications for cost and safety. The need for smarter, faster, and more efficient solutions has never been greater. DrillOps™ predictive analytics, a next-generation, cloud-deployed solution, is designed to transform the way drilling operations are monitored and managed. By harnessing the power of automation and integration, it lightens the workload for engineers, simplifying many tasks and providing valuable insights to enhance operational efficiency. This approach is setting a new standard for operational excellence, helping operators reduce costs, minimize risks, and scale their operations with greater confidence and efficiency.
At its core, DrillOps predictive analytics focuses on addressing some of the most persistent challenges in the industry. Non-productive time (NPT) and invisible lost time (ILT) have long been the bane of drilling operations, leading to delays, cost overruns, and inefficiencies. DrillOps predictive analytics tackles these issues by automating many traditionally manual workflows and integrating data and insights across multiple domains. The solution enhances engineers’ capabilities by streamlining complex processes and providing them with actionable insights, freeing them from tedious tasks like interpreting raw data. This enables them to put more focus on decision-making ensuring that wells are delivered on time, within budget, and as planned.
Automation: the key to drilling efficiency
One of the most transformative aspects of DrillOps predictive analytics is its ability to automate and accelerate tasks that were once labor-intensive and time-consuming. Historically, drilling operations heavily relied on experts manually verifying data quality, configuring and calibrating models, and interpreting data and model results from various sources. This process was generally slow and prone to human error, leading to missed opportunities for optimization or early intervention.
DrillOps predictive analytics simplifies these workflows by streamlining the QC process for rig data, automatically retrieving context from the drilling plan and geomechanical studies, and running advanced computations to interpret the data, all in real time. With many of the foundational tasks automated, engineers’ focus can remain on higher-value activities such as advanced engineering and strategic decision-making.
Powered by smart engines, combining AI and physics-based models, the solution analyzes real-time drilling conditions to identify potential issues, such as excessive pressure, drill string integrity risks, or mud weight window violations. These smart engines don’t just flag anomalies but provide context-aware insights that help teams assess the severity of a situation and take appropriate action. By reducing the time spent sifting through raw data and analyzing time series data plots to make sense of problems, the system enables reduced response times, and less costly disruptions.
For example, if early signs of a pack-off or stuck pipe event are detected, the system doesn’t just raise an alarm. It integrates data from multiple sources and provides various pieces of context, so the engineer can analyze the situation holistically. By automating the analysis and contextualization of data, DrillOps predictive analytics not only accelerates decision-making, it also reduces response times, and prevents costly disruptions assisting with actionable recommendations, transforming operational outcomes.
