Tackle your productivity challenges

Here are some of the ways we can enhance production uptime and boost operational safety.

Real-time production back allocation

Improve in real-time how your oil and gas wells are producing, using machine learning and first principles.

ALS predictive production issues

Get advance notice about potential production or maintenance issues that could lead to production disruption and downtime.

Hydrocarbon emissions or leak detection

Receive notice just in time of potential hydrocarbon emissions and leaks before they impact your operations.

Gathering network flow assurance

Achieve real-time visibility into how oil and gas gathering networks are performing.

We do the digital part. You enjoy the transformation.

We help companies embrace digital transformation and come out ahead against costly downtime and maintenance, safety concerns, and strict compliance How? By making your production and physical assets more efficient and effective through the use of technology-based solutions—carefully chosen to solve your specific business challenges.

Why Oil & Gas companies choose our IIoT-powered solutions

Leveraging IIoT, our customers in the Oil and Gas industry are able to streamline production and remotely monitor their operations to reduce costs while increasing profits.

1
Reduce Operation Cost (OPEX)

Reduce OPEX through real-time monitoring of expensive products and services, reducing manual and operator-based tasks, and reduced trips to remote production locations.

Early Detection of Production Issues

Discover production issues in time through solutions such as abnormal production pattern detection, machine learning-based virtual flow metering, and operator support using generative AI.

2
Predictive and Prescriptive Maintenance

Use data analysis and machine learning to monitor critical equipment and processes in order to detect anomalies that will lead to process shutdown or equipment's critical failure.

Improved Decision-Making

Improve your decision-making by leveraging clear and actionable data using advanced analytics and machine learning.

3
System Integration

Our software integration connects on-site sensors with an advanced dashboard to identify issues before they become liabilities.

Regulatory Compliance

Avoid heavy fines and penalties for non-compliance with regulatory standards through solutions such as H2S monitoring and detection, hydrocarbon emissions detection, and carbon footprint tracking.

With the IoT, we’re headed to a world where things aren’t liable to break catastrophically – or at least we’ll have a hell of a heads’ up.

Scott Weiss

How our oil & gas solutions work to increase safety and production uptime

Real-time production back allocation

We perform a dynamic modeling of the production system that enables us to perform a real-time mass, energy, and momentum balance to obtain production per well, as well as the pseudo-dynamic production behavior, capturing events and perturbations in the process. Once this model is built, we can use it to optimize artificial lift systems in real-time, find flow assurance problems in real-time, and generate predictive recommendations for well intervention.

ALS predictive production issues

We automate systems to monitor artificial lift systems for lower-producing wells to predict operational problems in real time by applying machine learning and real-time simulation techniques to data already in SCADA systems. Alerts can be programmed to send to operators automatically, proactively servicing the most critical wells first, while optimizing resources. As low as a 12% improvement in these wells would mean almost a 10% improvement in asset production.

Hydrocarbon emissions or leak detection

We use technologies such as industrial IoT and sensors to provide real-time monitoring of operations and program alerts about unwanted emissions like unsafe atmospheres, or methane emissions that exceed limits under current regulations. Connecting H2S or CO2 sensors directly to the cloud is highly effective, has no impact on the operator's control infrastructure, and involves low operational costs, while boosting operational safety and compliance with regulations.

Gathering network flow assurance

We combine SCADA data with machine learning models and physical models with automatic parametric tuning to generate real-time virtual three-phase flow and pressure measurements at any point in the production networks. This allows us to predict undesirable flow assurance events and trigger automatic alerts for the operator to proactively mitigate or eliminate production loss.

Case Study

Predictive Operations & Real-Time Alert System for Drilling Sites | Petrolink

See how we developed the backend engine for Petrolink's cloud based Saas drilling operations alerting system, providing their clients with instant insights and decision-making capabilities from drilling data.

Read Case Study

Let's talk.

It's time to slash production downtime and boost efficiency

Schedule a consultation