Intellicess is happy to announce the release of Sentinel RT Lite, a free version of our plug and play A.I. drilling advisory software. Sentinel RT Lite includes a state of the art real-time rig state back-end engine, that you can integrate into your system and workflows, free of charge. Get in touch with us if…
Sophisticated drilling-analysis software can help drillers set and modify weight on bit (WOB), rev/min, and other drilling parameters, but achieving acceptance of these software-based recommendations by a driller is complicated. Additionally, acceptance of changes to drilling techniques and modified work flows by a driller on one test rig is insufficient. The challenge is to scale…
Significant progress has been made on physics-based torque-and-drag (T&D) models that can run either offline or in real time. Despite its numerous benefits, real-time T&D analysis is not prevalent because it requires merging real-time and contextual data of dissimilar frequency and quality, along with repeated calibration, the results of which are not easily accessible to…
In recent years, detection and alerting systems have been applied to numerous drilling failures, including stuck pipe, fluid influx/loss, and drilling dysfunctions. But the detection of drillstring washout and mud pump failure has been left primarily to traditional methods that rely solely on standpipe pressure and pump rates or on measurement-while-drilling (MWD) sensor data. Drillers…
Armed with an abundance of surface and downhole sensors, today’s operators have access to unprecedented volumes of real-time drilling data. However, because they haven’t had the tools to quickly and accurately interpret it, the industry has yet to fully capitalize on this flood of information. The Intellicess Sentinel RT solution answers this challenge by cleansing…
This paper proposes a metric for quantifying drilling efficiency and drilling optimization that is computed by use of a Bayesian network. The network combines the identification of drilling dysfunctions (i.e., vibrational modes), autodriller dysfunctions, and mechanical-specific-energy (MSE) tracking into a single, normalized quantity that the driller can use to help decide which control parameters to…
Today, the effectiveness of real-time adjustments to drilling parameters may be hindered by uncertain surface and downhole measurements and the inability of humans to aggregate multiple streams of data in real-time. A recently introduced drilling optimization system addresses these issues by incorporating a Bayesian network into operators’ drilling rig data aggregation systems. This Bayesian network-enhanced…
To optimize the value of surface and downhole drilling data, an operator, a software company, and a service company have combined forces to develop a system to seamlessly integrate all forms of data, file types, and communication protocols. To ensure that personnel on the rig and in the office are able and willing to act…
The human component figures prominently in Apache Corporation’s well-documented drive toward developing an automatic rig-based drilling advisory system. The foundation has been laid with the installation of data aggregation boxes on 21 Apache rigs, which integrate seamlessly with the rig’s electronic drilling recorder to run physics-based models built around a basic Bayesian probabilistic network. The…