Scraping PTEN's US Land Rig Fleet

Scraping PTEN's US Land Rig Fleet

Posted by Paul Choi

Updated: Feb 9, 2020

worksite-ltd-l6zhclq9eyy-unsplash-978746-sEAmTv09-scaledLinks: Github | Scraped Site

Introduction

I decided to scrape and analyze rig data from Patterson-UTI Energy’s (NASDAQ: PTEN) website. PTEN is the second largest contract land driller in the US and one of the largest pressure pumping (e.g. fracking) service providers to Oil & Gas companies. The company is publicly traded with a current market cap of roughly $1.4 bil as of Feb 7, 2020. All of this means that there are a number of Oil & Gas investors who would be interested in seeing data about this company.

Why scrape this site?

PTEN provides daily status updates on all of the rigs in their fleet for customers and investors. Scraping this data is very helpful because it allows us to understand what’s going on in real-time with their core drilling business (63% of 4Q19 revenues, per 2/6/2020 8-K).  Additionally, seeing daily changes to PTEN's rig fleet allows investors to (1) better understand if management can hit their rig activity guidance in the near-term, and (2) gain a sense of any deviation from market expectations for land drilling fundamentals industry-wide. I was able to scrape nine days of the company's rig data and visualized some takeaways below.

(Industry rig count from Enverus)

Data Takeaways

  • PTEN's rig utilization rate remained at 56% during the week ended Feb 8, 2020 (120 operating vs. 96 available), below levels needed to drive an increase overall rig dayrates

  • The company had 39% of its active rig fleet (47 rigs) working in West Texas over the same period, which is expected given the E&P's focus on oily basins such as the Permian

  • The APEX-XK and APEX-PK rig class combine to represent 75% of its entire fleet (48% and 26%, respectively)

  • Lastly, the vast majority of PTEN's active fleet (95% or 115 rigs) has 1,500 horsepower capability, reflecting the management's focus on higher-spec rigs 

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Paul Choi

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Topics from this blog: Web Scraping

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