Overview

Production Challenges

The traditional production operating methodology is “visit every well, every day” which requires significant manpower. For the last fifty years, legacy automation solutions have provided the ability to move to a “pump by exception” operating philosophy - the current best practice. The last 10 years have seen revolutionary advancements in digital technologies, but little of that has been adopted within production operations. Ambyint seeks to advance the current state of production operations by merging best-in-class technologies from outside the oil and gas industry with traditional mathematics and operations methodology.

In simplest terms, operators are constantly struggling trying to improve performance while reducing cost.

Ambyint can help operators reduce cost and streamline operations in 3 critical areas:

Challenge
Ambyint Approach
Challenge
Low quality production operations data or limited visibility
Ambyint approach
Ambyint deploys modern High Resolution Adaptive Controllers to collect data and centralize to our SaaS backend of analysis.
Challenge
Decades old control logic
ambyint approach
Ambyint implements the leading techniques familiar to every production engineer while applying modern data science techniques including Artificial Intelligence to automate daily human activities while delivering actionable insights.
Challenge
Too many wells and not enough time
ambyint approach
Ambyint enables production teams to increase the number of wells managed per FTE by automating functions, reducing well site visits and windshield time while increasing the number of wells that are actively managed and optimized through automation and remote control capabilities.

Ambyint leverages modern embedded systems technology to advance the ‘pump-by-exception’ operating model with our end-to-end adaptive control solution. We dramatically simplify the traditional optimization stack that typically requires multiple vendors, significant capital, and a large infrastructure footprint into a single device and software platform (HRAC + POP). This strategy allows us to achieve a cost structure that is an order of magnitude lower than conventional automation, communicate anywhere in the world, and deploy actionable and intelligent data science and machine learning to automate artificial lift optimization.