Predictive Analysis

Accurate Data Quality = Early Detection

When addressing wells, or cohorts of wells, eventually the question comes to mind. Why does the quality of the data matter? For production, if an organization is consistently using allocated production, actual production may vary by roughly 10%. At OspreyData, we have seen much higher rates when the allocated wells
Single Tool

Data Quality Assessment with OspreyData

We provide organizations with a full set of services to aid in their digital oil field transformation and enable complex AI based solutions. After identifying possible operational challenges or significant field failures, OspreyData provides a Data Quality Assessment for our clients. Here are the steps that a typical Data Quality
Petroleum Expertise, Unified Monitoring

4 Starting Points For Success In A Digital Transformation

Moving to a digital oilfield is a critical enabler for producers in oil and gas. A critical focus is now on reducing operating costs, increasing employee productivity, and improving the ability to make informed and timely data-based decisions. For most oil and gas companies, the goal is clear, but the
Production Optimization

Increase Operational Efficiency with OspreyData

This week we’re sharing some slides that our Customer Engagement Manager, Jon Snyder, presented at a recent Professional Petroleum Data Management (PPDM) Association virtual luncheon. The slides and associated illustrations highlight the incremental and iterative process of how engineers, supervisors and operators collaborate to leverage data into actionable insights, execute
Predictive Analysis

Data Continuity, Granularity, and Latency

Following up from our last post, we will take a close look at Continuity, Granularity, and Latency in this post. What are these aspects of data quality and why are they so important? Continuity – How much source data is available without gaps or lapses? Faulty sensors and communication failures
Predictive Analysis

6 Aspects of Data Quality that Align with Problems

When looking at controlling costs as an oil and gas operators, it is important to look at the data quality for what you are using to solve problems and to measure your ROI. Do you have complete enough data at a sufficient rate for analytical analysis? What makes quality data?
Predictive Analysis

Operator Challenges in Controlling Costs

E&P companies are facing common pressures across the oil and gas industry to reduce lease operating expenses. The days of $100 oil are long over. Oil hovered between $50 to $60 / bbl for several years. Now with demand destruction due to the COVID-19 pandemic coupled with oversupply from OPEC+
Data Science, Petroleum Expertise

6 Common Data Quality Issues and the PPDM Data Model

In Production Operations, more and more devices have data collection and the type and frequency of the data collected is growing exponentially. We often hear from organizations about their struggles with their available data. It may be collection, or retention, or the quality. This is even regardless of the size of
Data Science, Production Analytics, Unified Monitoring

Digital Twins: Ideas On Increased Diagnostics In Oil Fields & Platforms

In the recent April 2020 Journal of Petroleum Technology article, Upstream Digitalization is Proving Itself in the Real World, the author wrote about “Using the Cloud To Turn Big Data Into Smart Data” and how Digital Twins are being used to increase evaluations and diagnostics within oil fields and platforms.