Intelevate™ real-time machine learning optimizes GeoESP® performance

Overview

European geothermal operators typically rely on static, historical data and lessons learned from neighboring wells to mitigate potential operational issues that can lead to premature failure. Unfortunately, this ineffective approach introduces significant uncertainty when making operational decisions. Consequently, there is an elevated risk of losing thermal energy generation and revenue when equipment malfunctions. The financial impact on operators can be substantial, involving production delays and the considerable cost of replacing equipment, which may amount to hundreds of thousands of Euros.

Challenge

Prior to Intelevate innovations, the operator lacked a real-time methodology based on the GeoESP operating parameters for identifying operational challenges in geothermal systems. Additionally, there was no intelligent alarm monitoring system to help help maintain production rates for heat requirements in Germany when downhole and surface problems arose due to scale development.

Solution

The Halliburton Intelevate digital platform offers:

• A cloud-based software system with 24/7/365 remote support from subject matter experts
• Machine learning (ML) models to calculate virtual parameters such as pressure, temperature, flow rate, and total dynamic head
• Optimization playbook for field operations and remote troubleshooting techniques
• Real-time scale and vibration resonance detection
• Real-time power consumption tracking and enhancement

Result

Intelevate digital platform and innovative technologies, deployed in 12 European applications, enable operators to meet production goals across climate seasons while ensuring geothermal energy compliance. The project was completed without additional capital expense, using existing SCADA information. For one operator, runtime increased from an average of 39 days to 105 days and is still running.