pSeven solutions
for
water_drop Oil and Gas

Get a demoContact us

Renewable energy technologies breakthrough in recent years and climate-friendly commitments to the decarbonisation present a significant challenge to the activities of oil & gas companies. These companies are progressively repositioning themselves in the energy industry, transforming into energy companies with such strategies as investments in renewable energy solutions, energy efficiency and emission reduction commitments. Many innovative solutions are being developed to make the power system and grids more flexible, allowing for higher and more cost-effective use and penetration of renewables.

Artificial Intelligence and machine learning-based pSeven software solutions help oil & gas implement their energy transition strategies: reduce energy waste, lower energy costs, and facilitate and accelerate the use of clean renewable energy sources in power grids worldwide. pSeven Enterprise low-code web-based software platform for predictive modeling and optimization allows to:

  • Build more reliable and accurate Digital Twins of assets and equipment faster thanks to advanced predictive modeling algorithms and SmartSelection.
  • Automatically explore and optimize equipment and process parameters better thanks to advanced Optimization algorithms and SmartSelection.
  • Rapidly develop customized Exploration & Production (E&P) microservices, applications, and solutions empowered by simulation and data processing workflows, and easily deploy them at a lower cost and faster thanks to powerful low-code process automation and orchestration platform, and easy to use deployment tools (AppsHub).
  • Easily scale your E&P microservices, applications, and solutions using the industry-proven cloud-native solution.

"Customized E&P applications, which you can build faster and at a lower cost with pSeven Enterprise, will allow you and/or your customers to reduce design time, infrastructure and maintenance costs, detect, analyze, and resolve production problems and generate predictive insights at enterprise scale. This addresses critical issues such as improving operational reliability, optimizing production, improving safety, and generating value".
Digital Petroleum, a leading provider of AI-powered solutions for the oil & gas industry

You can benefit from pSeven at each stage whether on land or offshore – from Exploration and Reservoir Development, to Well Construction, Production, Transportation, and even Refining.

stages

Use cases

ARENA. The future of engineering for flowline studies

Recording of the presentation "ARENA. The Future of Engineering for Flowline Studies" by Sylvain Truche, Project and R&D engineer | SEAL Engineering, part of the Centre of Expertise of TechnipFMC

Recording of the presentation "Reliable forecasts of gas properties without explicit physical modelling – an underground gas storage application case"

Presentation by Thomas Schaaf, Reservoir Engineer, Storengy – Engie group

Machine learning for subsea pipeline reeling mechanics

This study describes the benefits of using approximation models as surrogates of heavy FEA models in the design of pipelines to capitalize on the data and alleviate the design cost.

All use cases navigate_next

Publications

P7UC2024 - Halliburton & pSeven: A four-year journey of innovation and success

Sergio Sousa, Solution Owner - Digital Field Solver Suite, Halliburton
pSeven User Conference 2024

P7UC2023 - Hybrid Digital Twin for monitoring and tuning gas treatment unit

Laurent Chec, Vice-president of Global Sales, DATADVANCE SAS
pSeven User Conference 2023

DUC2021 - Reliable Forecasts of Gas Properties Without Explicit Physical Modelling – An Underground Gas Storage Application Case

Thomas Schaaf, Reservoir Engineer, Storengy – Engie group
DATADVANCE User Conference 2021

DUC2021 - Integrating Simulation Systems with pSeven to Solve Pumping Outfit Optimization Problems

Sergey Sumarokov, General Director, CALS-center
DATADVANCE User Conference 2021

Data-driven Model for Hydraulic Fracturing Design Optimization. Part II: Inverse Problem

Viktor Duplyakov, Anton Morozov, Dmitriy Popkov, Egor Shel, Albert Vainshtein, Evgeny Burnaev, Andrei Osiptsov, Grigory Paderin
Cornell University

DUC2020 - Keynote presentation Halliburton's Experience Building its Cloud-native Digital Oilfield Offering by Embedding pSeven

Sergio Sousa, Solution Owner for Workflow Automation, Halliburton
DATADVANCE User Conference 2020

All related publications navigate_next

Interested in the solution?

Click to request a free trial version or demo access.

Get a free trial