Processing the RRC Data in the Cloud with Azure Functions

As we wrote about earlier this month, the Texas Railroad Commission (RRC) released a treasure trove of data freely available to the public on their site. It was like Christmas in the Mi4 office. After we sang some carols and drank some hot chocolate, we realized that there was so much data. We didn’t know where to start.

Christmas in September

As my colleague @Talal wrote last week, we decided to get Lat/Long coordinates for every Texas well. In his post, he explained, there are many use cases for this data, so it seemed like an excellent place to start.

In this post I will go over my contribution to the exercise: creating a serverless function to process data in blob storage. Continue reading “Processing the RRC Data in the Cloud with Azure Functions”

TX RRC OData Feed – Intro

In this series of articles we will take the RRC data from the SQL database and serve it via an OData REST API and show how we did it.

The series will consist of 3 parts:

  • Part 1: Creating the OData REST API in Visual Studio using Entity Framework Core and C#
  • Part 2: Setup Continuous Integration and Delivery for automated build and release pipelines to publish to Azure using Azure DevOps
  • Part 3: Offering the API to the public via a secured Azure API Management gateway and developer portal

Sounds like a lot…I know, so if you want to fast forward to the end and start testing the API and the data just continue reading…you should be up and running in under 5 minutes.

Continue reading “TX RRC OData Feed – Intro”

Visualizing the RRC Data in the Cloud

Part 1: Well Locations

Last week I wrote a blog post talking about the TX RRC publishing data to the public that previously was only available via a paid subscription.

After downloading the different data sets and examining the various types of data and formats, I decided to take a closer look at the data that might prove to be useful to us and to our Productioneer clients.

It is not uncommon for location and depth data, as well as other well-header and meta data to be incomplete or non-existent during a software migration, after all this data might not be considered crucial for the daily gauge sheets. Especially in the case of Excel gauge sheets, where additional columns are a waste of “prime real estate” and might be considered as cluttering that particular production report.

It would be nice if we have a quick way to pull the Lat Long data in bulk to speed up the on-boarding process.

Continue reading “Visualizing the RRC Data in the Cloud”

Cutting month-end closing times in half

The accounting team at TPIC was spending too much time doing manual and repetitive tasks to close out the month and generate regular reporting packets for management. Having worked with us in the past, they asked us to streamline the process.

We promised them we’d make the process as fast and as simple as possible, joking that it would be as easy as pressing a button, and now it is!

A process that used to take days now only takes a few minutes, and all the manual labor has been reduced to a single button press, literally.

Continue reading “Cutting month-end closing times in half”

Is Your Oilfield Management Software Doing These 6 Things?

Is Your Oilfield Management Platform Doing These 6 Things?

“Digitization is the new lubricant for the future of the oil and gas industry’s upstream sector.” –Strategy& report by PwC

In order to keep a competitive advantage in a cutthroat marketplace, world-class oil and gas operations are tapping into the latest technologies. Augmented reality (AR), machine learning, automation, and robotics are all part of ‘what’s next’ in oil and gas exploration, but the greatest investments in transformative technologies are taking shape around software designed to make exploration more agile and data more accessible than ever before. Continue reading “Is Your Oilfield Management Software Doing These 6 Things?”

Power BI Switching between Logarithmic and Linear Scales

Welcome to the second post in our miniseries: “Are You Developing Power BI Reports the Right Way?” In the two-part series we are designing a sample Power BI report visualizing the weather on Mars and using some real world techniques.

The highlights of our first post were:

    • Getting data from Mars
    • Using a JSON file as a data source
    • Performing operations in the “Get Data” phase using M
    • Implementing a Dynamic Slicer
    • Using Chiclet Slicer and Dummyimage to create a Legend Slicer
    • Making design decisions

This post will focus on:

    • Switching an Axis Between Logarithmic and Linear Scales via a Slicer
    • Adding a Date Slicer
    • Using a Dark Theme

Continue reading “Power BI Switching between Logarithmic and Linear Scales”

Productioneer Report Portal General Release

Mi4 is excited to announce the public release of the Productioneer Report Portal to all of our Productioneer customers. The Productioneer Report Portal allows Productioneer users to see their Productioneer reports directly in a web browser. To use the portal, users do not need to have Productioneer installed on their computers and can now view their reports on tablet or mobile devices.

Access to the Productioneer Report Portal is included with a Productioneer subscription and is available to all Productioneer customers at no additional cost. Since Productioneer is not priced by user, Productioneer customers can give any member of their organization or partners access to the portal at no additional fee. Continue reading “Productioneer Report Portal General Release”

Power BI Legend Slicer from a JSON File with M and DAX

Data is king, or queen depending on your household dynamics. How you communicate that data and its impact to your clients can help or hurt your business. Both your short and long term relationships can hang in the balance, which is why the quality and delivery of your Power BI reports are everything.

Case Study: Power BI Report Development

In this blog post mini-series, we will be taking you through the process of creating a Power BI report. The demo report draws from one we created for a client as part of a larger dashboard project. It implements a line chart to visualize the weather on Mars.

The actual report we developed had nothing to do with Mars, space, or weather, but you should find it useful to understand how real-life issues can be resolved and optimizations can be employed. The first post in the series focuses on data-prep and implementation of a legend slicer.

Continue reading “Power BI Legend Slicer from a JSON File with M and DAX”