Oil & Gas

Upstream Drilling & Exploration

CloudPrisma has taken an approach to map digital technology onto a typical Oil & Gas company’s value chain and position an appropriate Digital Technology-based strategy. Each stage of the value chain has its own uniqueness of data sets with their own ecosystem. Also, CloudPrisma strongly feels that employing data analytics to improve operations, relying on siloed applications offer limited visibility within each block of the value chain if the data sets provided by the OEM’s, partners, etc. are not included to provide a holistic picture of the value block and also bring synergies across the various blocks in the value chain of the organization.

Enable Cloud

Modernizing the core IT Infrastructure of the O&G companies to bring in more flexibility in computing, optimize resources and move to an Opex model from a Capex model. Understand client’s current state, business needs, and priorities for a migration to a Digital Infrastructure like a cloud. Create a cloud enablement plan with implementation, transition, and support.

  • A Cloud-based HPC solution can be used to process data on Oil & Gas Reservoirs. This Technology saves time & money by allowing analysis of exploration prospects to be done in weeks instead of months. Given that drilling exploration, wells can cost hundreds of millions of dollars, drilling in the right place can yield sizable savings.

Modernize Applications & Data

  • Data from different sources across the value chain require a different architecture to capture and cleanse before ingestion into various applications. In the O&G Value chain, you have three types of data sources – Batch (acquired sensor data from Exploration & Appraisal stage), Static (data created with models & software in the Concept, Project Definition & Execution stage), and Real-Time (Streaming sensor data in the Drilling & Production stage).
A key to any digital transformation is the availability of quality data, and external data sources continue to refine and define new business models with analytics.
  • Application Modernization - Many of the legacy systems' surrounding applications may also need modernization and port in a Hybrid Cloud environment, for there may be a need to do an initial study and draw a roadmap for creating new Modern Applications.

Gain Insight with Big Data & Analytics

Gain visibility & have a look at how the ever-growing amount of data generated by oil and gas companies can surmount these challenges when crunched into meaningful insights into areas like -

  • Complex operational processes
  • Difficulties of performance improvement
  • Equipment life cycle management
  • Logistics complexity
  • Meeting environmental regulations.
Recommendations –
  • Manage Seismic Data - acquisition of seismic data (collected with sensors) across a potential area of interest in search of petroleum sources.
  • Optimize Drilling Process - customize predictive models that forecast potential equipment failures. As a starting point, the equipment is fitted out with sensors to collect data during drilling operations.
  • Improve Reservoir Engineering - The variety of downhole sensors (temperature sensors, acoustic sensors, pressure sensors, etc.) can gather companies' data to improve reservoir production.

Climb AI & Cognitive Ladder

Identify trends and predict events throughout processes to quickly respond to disruptions and improve efficiencies.

  • Perform complex Analytics to optimize Drilling & Production.
Recommendations –
  • Transform reservoir management and recovery from reactive to predictive with data.
  • Accelerate Well planning and optimizes drilling with real-time AI insights.
  • Capture expert knowledge to analyze rock formations for better drilling.