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Finding gems in your historical frac data

Finding gems in your historical frac data

by Well Data Labs | Mar 27, 2020 | Completions, Data Analytics

Using frac data to spot trends and improve outcomes Though the booms and busts of the industry are often tied to economic and geopolitical forces beyond our control, we at Well Data Labs are firm believers in taking advantage of these slowdowns to innovate and improve...
Time for a frac review? 3 tools to gain deeper insights

Time for a frac review? 3 tools to gain deeper insights

by Well Data Labs | Dec 16, 2019 | Completions

The end of the year is coming – you can’t avoid it!  Dissecting your 2019 business data, regardless of what industry you’re in, is crucial for a strong start in 2020. By now, you’ve most likely evaluated the past year’s performance and are finalizing budgets and...
Capturing the value of APIs in today’s oilfield

Capturing the value of APIs in today’s oilfield

by Well Data Labs | Nov 13, 2019 | Completions, Data Science, Real-Time Frac

The Intelligent Oilfield. It’s a term we commonly hear discussed in boardrooms, at conferences, in industry journals, on blog posts, and in other media. While the oilfield is becoming increasingly intelligent, that intelligence is hindered by a lack of something...
Garbage in, garbage out – how bad data can fuel bad decisions

Garbage in, garbage out – how bad data can fuel bad decisions

by Well Data Labs | Oct 1, 2019 | Completions, Data Science

Garbage in, garbage out. The quality of information coming out of a system can never be better than the quality of information that was put in. It may sound sort of like one of Newton’s laws of physics, it’s not. But at the very least, it’s an always relevant guiding...
The Digital Oilfield – Then and Now

The Digital Oilfield – Then and Now

by Well Data Labs | Apr 8, 2019 | Data Science, Industry Insights

Much has been written about the digital oilfield, just Google it and you’ll get pages of results. The term has been around for nearly 20 years, and we thought it would be fun to provide a high-level overview of what it means and assess where we are in terms of...

Predict Trouble Stages Using Rock and Frac Data

by Well Data Labs | Jan 24, 2019 | Completions, Data Integration

Integrating Rock Properties and Fracture Treatment Data to Help Optimize Completions Design In case you missed this paper on the Society of Petroleum Engineers (SPE) OnePetro website, a team of experts from Hawkwood Energy, FractureID, and Well Data Labs describe how...

Data Frequency: Every Second Matters

by Well Data Labs | Mar 1, 2018 | Data Integration, Data Science

Data Resolution – Why is it important? New software is allowing companies to capture and store more granular data than ever. In O&G, specially in completions operations, some of the most detailed data is acquired off  field equipment at a one-second level....
Visualizing the Big (data) Picture

Visualizing the Big (data) Picture

by Well Data Labs | Nov 29, 2017 | Data Science, Industry Insights

For many operators, it seems like the well is a baton handed off from the drilling team to the completions team to the production team. Each group has their own tools, their own questions, and their own ideas about what makes for a quality well. But at the end of the...

What Computers Can do for Your Oil & Gas Data that Humans Cannot

by Well Data Labs | Sep 7, 2017 | Completions, Data Science

Guest Post by Ky Kiefer We often design hydraulic fracturing treatments around historical success. We look to the successes (and failures) of “wildcatters” of the past and attempt to replicate treatment designs. Once we have a baseline treatment that tends...

Diverter Effectiveness – Analyzing One Piece of the Puzzle

by Well Data Labs | May 4, 2017 | Completions, Industry Insights

  In today’s industry climate, operators are relying on large data sets more than ever to make intelligent design decisions when it comes to drilling and completing wells. The first step in making those decisions is establishing a detailed understanding of what...
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