Research

SSPA header

The Proceedings of the 43rd Scandinavian Symposium on Physical Acoustics are out!

As of today, the Proceedings of the 43rd Scandinavian Symposium on Physical Acoustics is out! I was the editor for these proceedings, just like I was for the 42nd and 39th symposia. This year’s proceedings consists of 7 submissions: 5 full papers and 2 extended abstracts. Altogether, the submissions represent 82 pages of sciency goodness.

Header for the article "Getting started with acoustic well log data using the dlisio Python library on the Volve Data Village dataset"

Getting started with well log data

Last year, I wrote a post on DLIS files, one of the most common file formats for well log data. In it, I covered a few different approaches to extract data from such files. It seems like many people struggle with this, because that post quickly became my most popular one. Well over a thousand views later, it’s time to follow it up.

I have been working with acoustic well log data since 2018. During that time, I have learned a lot about how to work with such data, and I have been wanting to share my knowledge. To do so, I teamed up with Equinor’s Erlend Hårstad and Jørgen Kvalsvik, developers of the dlisio library. Since January, we have been working on a tutorial on how to use dlisio to work with well log data. As I am an acoustician, the tutorial naturally focuses on acoustic tools. However, much of what we show is general, valid for data from any tool.

We first presented this work at the 43rd Scandinavian Symposium on Physical Acoustics in the end of January. Just last week, we published the article that we wrote for the symposium’s proceedings. Along with it, we published a companion Jupyter Notebook, which contains the code underlying the article and some further details. As of June 2020, you can even run it on Binder, so that you can play with it online without having to download anything.

Well log plot

Extracting data from DLIS files

Update, April 2020: I just published a tutorial on getting started with well log data. It is based on Equinor’s Volve Data Village dataset and their dlisio library, both of which are free and open. You can read more about the tutorial here, or go straight to the tutorial article and its companion Jupyter Notebook.

In my current research project, I am working with two well log datasets from Equinor. The first is a large dataset that they released to CIUS, my research group. The second is a smaller freely available dataset called Volve Data Village. The files in those datasets contain measurements from many of Equinor’s subsea wells on the Norwegian continental shelf. These data files are primarily in the DLIS format, formally known as API RP66.

Even though DLIS is the most common format for well log data today, only a very limited number of programs can read it. In addition, most of these programs are geared towards displaying the data so that log interpreters can analyse it visually. What I need, on the other hand, is full access to the data so that I can run my own computational analyses.

When I started my post-doc around a year ago, I had to figure out how to get the data out of DLIS files so that I could work with it. Since then, I have learned quite a bit about how to read these files. In this post, I want to share some of what I have learned with you.

Well logging example

Well logging blog post: “The health of petroleum wells”

I currently work as a post-doc at the Centre of Innovative Ultrasound Solution (CIUS) at NTNU. Here, all the researchers must occasionally write popularised blog posts about their work. It was recently my turn, and I wrote a post titled “The health of petroleum wells”. In that post, I go into what well logging is and what it’s for, and explain some of the aims of my current research project.

You can read my new blog post on the CIUS blog! You can also read some of my earlier work on ultrasonic well logging on my Publications page.

I have taken the header image from Equinor’s free Volve Data Village data set with explicit permission.