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Case Study: ENSYTE Provides Real-Time Monitoring for E&P Client

HOUSTON, TX – ENSYTE routinely receives requests to build custom software utilizing its GASTAR/PRISM™ data models as the foundation. By leveraging an extensive data model for upstream, midstream and downstream business practices, ENSYTE is able to minimize software development and implementation costs for clients and achieve optimal deliverable schedule. A recent example is a real-time gas scheduling model, designed for an international exploration and production company, which provides gas supply monitoring and forecasting for one onshore gas plant and two offshore platform gas processing facilities. ENSYTE deployed the GASTAR/PRISM™ data model and core application software as the base for the project and prepared modifications to capture the client’s unique processing requirements.

Processing Objective: Optimize comingled natural gas from multiple supply locations and perform real-time calculations of contract-specified Volume, Gross Heating Value (GHV), C2, C3 and C4 gas quality delivered to an LNG facility. The goal was to set export targets for volume and/or gas quality and trigger the software to allocate these targets to aggregated supply points. The objective function was to achieve optimum supply point component volumes that when comingled would yield the daily or intraday export targets from each gas processing facility.

Real-Time Processing: The solution sampled an OSISoft Real Time Database (RTDB) on a 2 second interval for volume and a 6 minute interval for chromatograph readings from each measured facility meter and sample point location. Two (2) measurement data sets were sampled with the operator selecting the primary for volume and energy accounting and comparison to contract deliverability terms. The OSISoft ProcessBook was integrated to display custom and User-defined data elements on a process diagram.

Allocation Process: The allocation engine, with each data update, performed an allocation of volume (KSM3), GHV, and components C1-C9+. The allocation engine also responded to manual or automatic insertion of facility and stream constraints, as well as alarms. The allocation network operates in a forward or backward processing state. For example, the User can dial in a contract delivery nomination and based on priority and limit criteria, the software will calculate a first pass, optimized flow rate. There is an extension that permits optimization on defined criteria, such as a range in C3+C4 delivered to the plant.

Contract Monitoring: The Contract Node included the contract terms for gas delivered to the inlet pipeline for the LNG plant. In the system, each node is set up with limits and constraints with screen pop-ups notifying the User/Operator of gas volume and energy that exceeds pre-defined limits. An extensive list of real-time, daily, and monthly time step KPIs (Key Performance Indicators) are generated to report on gas flow compared to process performance requriements.

The project scope relied on an extensive component stream management algorithm that could handle converging streams and split streams, which could reallocate if an operator fixed a supply demand or intermediate node with a directed volume. The component volume allocation algorithm (illustrated on the accompanying screen shot) is an ideal method of monitoring key measurement points for gathering systems, gas plants, and processing allocations.

ENSYTE Energy Software International ( provides performance-driven software packages and professional services for the energy and power industries.