GeoComputing Launches Sixth-Generation RiVA Platform with AI Integration for Oil & Gas Applications
GeoComputing Group, a recognized leader in delivering advanced petro-technical IT infrastructure solutions, has officially announced the launch of the sixth generation of its RiVA geotechnical computing platform—GEN 6. This major upgrade introduces enhanced support for artificial intelligence (AI) tools and compatibility with industry-leading oil and gas software applications such as PaleoScan, Petrel, and Kingdom. The new generation of RiVA is engineered to empower exploration and production (E&P) operators with an advanced computing environment that seamlessly integrates AI-driven capabilities into traditional geoscience workflows.
Meeting the Demands of a Data-Intensive Industry
GeoComputing’s RiVA platform has long been acknowledged as the most robust and capable private cloud system tailored specifically for the energy sector. Designed to meet the needs of exploration and production professionals, the platform directly addresses widespread industry challenges such as sluggish system performance, complex work environments, massive geoscience data volumes, geographically dispersed teams, insufficient technical support, and prohibitive deployment costs and timelines.
With GEN 6, GeoComputing takes another leap forward by delivering a high-efficiency, high-performance solution that enables significant improvements in both productivity and accuracy. Complex modeling and seismic interpretation processes that once required several days to complete on legacy systems can now be executed in a matter of hours, thanks to RiVA’s enhanced computational power and optimized resource management.
AI-Ready Infrastructure Built for the Future
The sixth-generation RiVA platform is specifically built to support the next wave of digital transformation in the oil and gas industry by incorporating cutting-edge AI-ready GPUs and configurable workstation profiles. These advancements enable seamless deployment of AI toolkits from major geoscience software vendors, allowing users to harness advanced machine learning and deep learning algorithms without leaving the familiar environments of their preferred applications.
Among the standout capabilities of GEN 6 is its integration with AI-enhanced tools within widely-used platforms such as Petrel by Schlumberger, PaleoScan by Eliis, and Kingdom by IHS Markit. This strategic alignment allows geoscientists and engineers to continue working within their established toolsets while benefitting from the increased analytical power and predictive insight delivered by AI technologies.
Furthermore, the GEN 6 platform now includes support for containerized deployments—a critical architectural feature for modern AI applications that rely on microservices. This functionality not only enhances portability and scalability but also streamlines integration with external AI solutions that require isolated or modular runtime environments.
Hardware Optimization with NVIDIA AI GPUs
To deliver the high levels of performance required by modern AI workloads, the GEN 6 platform integrates the latest AI-supported GPUs from NVIDIA. These graphics processing units are optimized for machine learning, data science, and deep learning tasks, offering the computational horsepower needed to process massive volumes of unstructured geoscientific data in real time.
The platform also introduces customizable workstation profiles that can be fine-tuned based on the specific memory and performance requirements of different AI applications. Whether running advanced seismic imaging algorithms, well log analysis, or reservoir simulation models, users can tailor their computing environment to achieve optimal speed and responsiveness.
Collaboration with Eliis to Enhance Subsurface Intelligence
As part of its GEN 6 launch, GeoComputing is collaborating with Eliis SAS, the developer of the PaleoScan platform, to jointly accelerate subsurface workflow automation through AI. This partnership represents a significant milestone in merging cloud-based infrastructure with geoscience intelligence tools.
“We are very happy to be collaborating with GeoComputing to continue our mission to accelerate and automate subsurface workflows,” said Alex Wilson, Principal Geoscience Advisor at Eliis SAS. “By coupling the PaleoScan™ geoscience and RiVA private cloud platforms, we will develop and deliver AI solutions that unlock new geoscience insights with unprecedented performance.”
The collaboration is aimed at building tools that not only enhance interpretation speed but also improve decision-making accuracy through machine learning-powered pattern recognition, anomaly detection, and stratigraphic classification—all within the familiar PaleoScan environment.
Practical AI Adoption Without Sacrificing Stability
A major theme underlying the GEN 6 release is GeoComputing’s commitment to facilitating AI adoption without undermining operational stability or cost efficiency. AI in upstream operations is still an evolving field, and operators moving prematurely to public cloud platforms without a clear implementation roadmap often encounter significant setbacks—ranging from degraded performance to skyrocketing IT expenses.
GeoComputing’s RiVA platform offers a well-calibrated alternative by allowing users to adopt AI tools within a trusted and performance-optimized private cloud environment. This approach mitigates the risk of data latency, network congestion, and unpredictable cost fluctuations often associated with public cloud services.
Unlike generalized cloud platforms, RiVA is purpose-built for E&P workloads, providing tailored services and infrastructure that cater to the specific needs of geologists, geophysicists, reservoir engineers, and IT administrators in the oil and gas sector.
Enabling a Smooth AI Journey
The GEN 6 RiVA platform is designed not just to enable AI functionality but to support operators throughout their digital transformation journey in a thoughtful and scalable manner. With an emphasis on operational integrity, data security, and performance optimization, the platform provides the tools necessary to modernize exploration strategies and reservoir management practices while keeping costs under control.
Jay Kirby, Vice President of Strategic Solutions at GeoComputing, emphasized this balanced approach:
“GeoComputing differentiates itself by maintaining an unwavering commitment to delivering peak performance for end users while simultaneously reducing operating costs. Unlike other platforms, we achieve this balance by enabling AI from application vendors without compromising the foundational capabilities that users rely on. Our approach ensures that operators can embrace AI-enhanced workflows without the trade-offs of inflated expenses or degraded performance, providing a harmonious integration of cutting-edge technology with practical efficiency.”
