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Composable DataOps - Oil & Gas Industry

How Composable DataOps is Modernizing the Oil & Gas Industry​

New technologies helped make the U.S. a net exporter of oil in just a few short years, but the oil & gas industry still faces a challenging future. Renewable energy generation methods are becoming cheaper, while political and cultural considerations are forcing oil & gas companies to innovate and eliminate inefficiencies from their production capabilities.

These forces make need for quicker digitalization urgent. But new technologies are creating datasets that overwhelm traditional data management techniques. According to industry research, petroleum engineers and geoscientists spend over half their time searching and assembling data.

Composable DataOps is a set of tools and processes that helps companies efficiently manage their large and dynamic data assets at scale, while also improving the accuracy and efficiency of data science tasks.

Here’s how oil and gas companies can leverage Composable DataOps tools to optimize upstream, midstream, and downstream data science activities.

A poll of over 400 IT decision makers in the oil & gas industry found that nearly all felt a failure to embrace data technologies could endanger their future success.


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Composable Workflows Maximize Interoperability

Despite consistent technology investment, the oil & gas industry is still replete with legacy IT systems, including enterprise resources planning (ERP), accounting systems, and file servers. These siloed systems require enormous investments of time and energy to integrate into a modern data infrastructure.

Composable DataOps platforms give oil & gas companies the tools and workflows they need to modernize legacy systems and maximize their interoperability. Some of the key characteristics include:

Cloud-native data operations
The Composable DataOps model is built for native operation on Microsoft Azure or Amazon AWS, giving your data engineers a central, easily accessible management console for ingesting and processing data from and heterogenous on-premise and cloud systems. Access to a unified set of resources from any location has other important benefit too, like enabling strong collaboration among disparate teams.

Flexible microservices
The composable software architecture replaces monolithic, software architecture with flexible modules that your data engineers can assemble however they need for each individual workflows. Accessing data and services as need, through APIs means that data in any format, from any system, without any over the bloat or inflexibility that comes with monolithic software platforms.

Improve Ingestion and Data Lake Management

Many companies in the oil and gas industry struggle with unstructured data. According to the Journal of Petroleum Technology, employees at oil & gas companies are spending 3 times the amount of time looking through unstructured datasets than the average across industries. Compliance documents, imaging information, presentations, and reports all contain valuable information, but without the right tools extracting the information from those data assets takes tedious, manual effort.

Automation is an important part making sure that the data in your like is cleaned, easily located, and free from error. The composable architecture allows you to integrate enterprise AI and advanced optical character recognition capabilities into your ETL workflows, automating some of the most tedious data management tasks.

  • Upstream data
    Streamline the management of seismic data so that data consumers can quickly find and access the datasets they need to evaluate locations and optimize the drilling process.
  • Midstream data
    Better managing data about logistics and supply chain procedures enables operators to plan future use better, assess risk, and predict outcomes.
  • Downstream data
    Gathering and utilizing data from the oil refining process in analytics and machine learning workflows can create incremental, data-driven improvement.

Integrate Field Worker Data
Field workers are on the front line of the oil & gas industry, gathering field measurements, wellhead measurements, and testing drilling activity. Oil & gas companies that lack a unified system for ensuring ingesting, cleansing, and cataloging that data encounter unnecessary complexity.

Composable DataOps platforms provide automated data pipelines that ensure data from frontline workers is properly loaded into your data lake and catalog, regardless of its format, helping your firm manage errors & omissions insurance claims and corpus management processes.

Expand SCADA System Investments
SCADA systems are critical to overseeing automated processes, but you can deepen the investments you’ve already made in your SCADA systems by automating the extract, transform, and load process of newly generated data, allowing seamless interaction with ERP systems, cloud data lakes, and analytics systems.

Embrace Next-Generation Analytics and Machine Learning

With the advent of data recording sensors in exploration, drilling, and production, analytics workflows have become an important part of the oil and gas industry’s efforts to optimize the performance and safety of pumps, streamline asset management processes, and strengthening logistics efficiency.

The speed at which important data gets processed involved in these processes is critical. With full-stack automation and easily configurable pipelines, data engineers will have the tools to ensure analytics application like rock and sediment classification, production monitoring, and hydraulic fracturing processes receive the input data they need.  

Modeling and Simulation
3D modeling is an important tool for oil & gas companies, helping them manage oil and gas reservoirs, optimize pipelines maintenance schedules, discover production bottlenecks, and more. Effectively managing first party, third party, and even fourth party datasets with automated data management tools reduces data engineering tasks and allows data scientists to focus on producing high quality models. Furthermore, data governance tools deep integrated into your DataOps workflows allows you to build functional data applications with confidence that compliance controls aren’t being violated.

A survey conducted by the International Data Corporation found that in 2021, 70% of US oil executives were unaware of how data science could help improve their operations, while a recent survey by General Electric and Accenture found 81% of decision makers now consider big data a top priority. – Big Data Analytics in Oil and Gas Industry: An Emerging Trend

Maximize the Return on Your Digital Transformation Investment

The Composable DataOps model is a comprehensive set of platforms, processes, and tools for managing data science and analytics initiatives at oil & gas companies. If you’re interested in streamlining your data management workflows and making the most of your digital transformation, we’d be happy to help.

The Composable Analytics team is eager to help more businesses embark on the Composable DataOps journey with confidence, helping them meet all the technical and operational challenges they may encounter.

About Composable Analytics, Inc.

Composable Analytics, Inc. builds software that enables enterprises to rapidly adopt a modern data strategy and robustly manage unlimited amounts of data. Composable DataOps Platform, a full-stack analytics platform with built-in services for data orchestration, automation and analytics, accelerates data engineering, preparation and analysis. Built with a composable architecture that enables abstraction and integration of any software or analytical approach, Composable serves as a coherent analytics ecosystem for business users that want to architect data intelligence solutions that leverage disparate data sources, live feeds, and event data regardless of the amount, format or structure of the data. Composable Analytics, Inc. is a rapidly growing data intelligence start-up founded by a team of MIT technologists and entrepreneurs. For more information, visit composable.ai.