Optimising Flow.
Maximising Every
Single Barrel.

Monitor and predict water cut behaviour using Oil Cut and WOR methods (Chan and others), enhanced with physics-based and data-driven models. Estimate recoverable reserves and recovery factor up to a user-defined maximum economic water cut — supporting production scenario planning and intervention timing decisions.

Identify the highest-value candidates for workovers, recompletions, pump replacements, or other interventions — combining production performance data, reliability metrics, and operating costs. Physics-informed models, machine learning, and big data analytics are complemented by advanced methods including Yang's logic fuzzy model, formation damage index, and cluster analysis with PCA. Evaluate at field or block level, create case studies to store and compare results over time.

A fully integrated nodal analysis environment covering PVT properties, reservoir inflow models, completion configurations, wellbore hydraulics, and surface networks. Supported reservoir models include Darcy, Vogel, Jones, transient flow, back pressure, fractured wells, and horizontal well correlations (Joshi, Giger, Economides). Completion options include open hole, cased perforations, stable perforations, and gravel pack configurations. Wellbore models include MONA, Mukherjee & Brill, Beggs and Brill, and Ansari Mechanistic. Choke performance, hydrate formation, and wax deposition are also integrated into the nodal framework.

Model the complete pipeline network from source nodes to delivery points. Apply hydraulic correlations and operating constraints to estimate pressure losses and flow distribution across segments. Identify bottlenecks and capacity limitations before they constrain production. Output includes estimated flow and pressure by node, pressure drop by segment, critical velocity, severity index, and utilisation percentage.

Assess hydrate formation risk along the pipeline system using seven industry correlations — Makongo, Hammerschmidt, Oestergaard, Tower & Mokhatat, Berg, Mottie, and Bahadori. Evaluate pressure-temperature safety margins at each segment and generate preventive alerts before conditions approach the hydrate formation envelope. Wax deposition analysis is also integrated, estimating deposition thickness over time.

Automatically detect water hammer events, leak signatures, and flow restrictions from real-time SCADA data. Identify the event onset, estimate the most probable origin location in the network, and generate severity-based alerts for rapid operational response — without manual analysis or specialist software outside the Optima environment.

Manage pipeline and facility mechanical integrity using inspection and operating data. Calculate wall thickness, Maximum Allowable Operating Pressure (MAOP), and corrosion trend rates. Estimate remaining life and next inspection dates based on operating conditions. AI models predict corrosion behaviour and risk evolution — integrating inspection records, operating data, and chemical treatment history to generate proactive alerts and support risk-based maintenance planning.