Energy

how it works

SQLstream wrangles, analyzes, and acts upon Smart Energy data in real time

Smart Energy operators must process, analyze, and react in real time to massive volumes of sensor data every day in order to improve safety, compliance, and profit. For example, real-time analysis of streaming data from drilling rig sensors, intelligent wells, and digital oilfield installations enables early detection of drilling hazards and pending equipment failures, thereby reducing rig time, intervention, and shut-ins.

Data problems include the need for real-time integration of operational systems and an inability to maintain accurate and current information across all systems and data warehouses in real time. Poor integration leads to duplication of data and systems, and a lack of visibility across all monitored assets, resulting in the delayed identification of the root cause of problems.

SQLstream’s real-time operational intelligence platform is built on a streaming data management architecture. The platform is capable of processing and analyzing rig data and smart oilfield data in real time, and supports the integration of any and all of an organization’s sensor data, operational platforms, and data warehouses without the need to store the data first.

Data challenges and the SQLstream approach

Field production optimization

High volumes of data streaming from DOF&DFS: Guavus SQLstream ingests and analyzes high-volume, high-velocity data from multiple, disparate sources and formats, at rates of millions of records per second.
Manually updating reservoir models and predict performance: Guavus SQLstream streams field data to model; compares newly arriving data against model continuously and in real time; adjusts production automatically to meet objectives.
Delayed detection of onset of leak & shut down: Guavus SQLstream incrementally adjusts analytics results and pushes automatic updates in production parameters, from adjusting vacuum pressures to shut downs.
New data: Real-time geology interpretation and adaptive new well delivery processed can reduce trial&error and optimize the number of wells

Equipment failure detection

Rig equipment: Reduce non-rotating time, wellbore instability,blowout.
Oil field facilities: Reduce NPT, do repairs during normal maintenance.
Electric submersible pumps: Avoid unscheduled WO & NPT.
FPSO: Avoid expensive interruption to offloading oil to FPSO.
Refineries & petrochemical plants: Avoid unscheduled repair & fire/explosion, environmental hazards, and personnel safety risks.
Pipelines/compressors: Avoid unscheduled repair & fire/explosion.

Fleet monitoring and management

Monitor position & performance of drilling vessels, oil tankers, FLNG, work boats, FSPO from onshore: Stream sensor data to on-board s-Server, deliver rolled up KPIs to data center in real time, generate real-time alarms & alerts for immediate control & response.
Oil tanker demurrage: Manage marine, land, and rail traffic data continuously and in real time to reduce and calculate demurrage for payment and legal defense.
Real-time land fleet performance monitoring: Monitor tanker truck, field vehicle, & heavy equipment performance data continuously and in real time, e.g. tire pressure of tar sand mining trucks, local temperatures, pressures, flow levels, etc.

Data management applications development

Slow development, high costs: Use existing apps, databases, data warehouses, and skill sets. Business analysts, SQL, and Java developers can build streaming apps in minutes that deliver streaming ingest, analytics, and actions to operationalize insight.

Streaming analytics impacts all business areas

operations

Streaming ingestion and analytics enable automatic actions that can adjust entire production systems to eliminate production challenges, reduce operational costs, and recognize opportunities in real time.

Safety

Real-time data processing predicts and eliminates well integrity and cargo safety risks, personnel health & safety risks, and system security threats before they occur.

COmpliance

Operational requirements are automatically updated and deployed when changes in physical work conditions negatively affect the environmental impact, or when changes in policies demand a readjustment of product, processes, or price strategies.