Categories
Drilling & Completions Transfer

Gun Barrel Diagram: Calculate and Visualize Well Spacing Part 2

Part two of this blog series builds on my last post and provides step by step procedures for dynamically calculating well spacing and building gun barrel diagrams with Petro.ai. The short video above from Kyle LaMotta highlights the key steps but keep reading for a detailed procedure of how this is done.

Required Data

The gun barrel calculation requires two sets of data; wellbore directional surveys and formation structure grids. It is also possible to run the gun barrel calculation without structure grids, but an additional data function is required.

The surveys must have X, Y, Z, MD, and a well identifier, and the X & Y should be shifted to the correct geo positions, not the X & Y offset values provided by the survey company. Check out this template if you need to convert a drilling survey with azimuth, inclination, measured depth to XYZ. The formation grids must have an X, Y, Z, and formation name. It’s also important to note that the two data sources must be projected in the same coordinate reference system with Z values referencing the same datum (e.g. TVDSS). Another useful template can be found here to convert a CRS in Spotfire.  With this information the Gun Barrel function will calculate the 3D distance between the midpoints of horizontal wellbores.

After loading these data sources into Spotfire (either via Petro.ai or by directly adding the tables), click Tools > Subsurface > Classify subsurface intervals. Clicking this will bring up your “Classify Subsurface Intervals” window. Here you be prompted to fill in the dropdown menus with the relevant information.


Figure 4: Classify Subsurface Intervals (and Gun Barrel) Menu

XYZ Input: Map to wellbore surveys

The top left section, shown below, is used to map columns to your wellbore surveys table. Select your wellbore surveys data table, then fill in the X, Y, and Z dropdowns. Be sure to select “use active filtering”. This will allow the user to filter and mark select groupings of wells and determine the Gun Barrel distances for that select grouping.


Figure 5: Classify Subsurface Intervals (and Gun Barrel) Menu: XYZ input box Horizons

Horizons: Map to surface grids

The top middle section, shown below, is used to map columns to your wellbore surface grids. Select your horizons data table. This will be a table that has your horizon grid data points. This table should contain X, Y and Z data points for each individual horizon. See below for reference. Be sure to select “use active filtering”. This will allow the user to filter the surface grids around the wells of interest, which will significantly improve computation time.


Figure 6: Classify Subsurface Intervals (and Gun Barrel) Menu: Horizons Input Box


Figure 7: Formation Grids data table requirement (example)

Output: Table names and columns

The top right section, shown below, is used to configure the output table and column names. Transfer Columns are simply the additional columns that will be displayed in the output data table, check the column name boxes to include any metadata columns that will help you identify your wells.


Figure 8: Classify Subsurface Intervals (and Gun Barrel) Menu: Output options

Gun Barrel Settings

The bottom half of the window shown below enables the Gun Barrel calculations to run and allows the user to configure settings for the gun barrel.

To enable the gun barrel, check the “Enable Gun Barrel” checkbox. In the Wellbores section, select the Well identifier and MD from your Wellbore Survey data table. Next, use the input boxes to define buffer dimensions around the lateral. This allows the user to update the dimensions around the laterals, creating a rectangular prism for the calculations. In general, the preset values are sufficient.

The right side, Gun Barrel – Output, is used to name the spacing result table generated by the calculation. Use the input box to update the table name. At this point, you are ready to run the calculations: click the OK button.


Figure 9: Classify Subsurface Intervals (and Gun Barrel) Menu: Gun Barrel Input Box

Gun Barrel Spotfire Template

With all the proper data imported and mapped, it is now possible use the Gun Barrel workflow. It’s possible to run the interval classifier and gun barrel calculator in any Spotfire DXP using Ruths.ai software, but we recommend starting with the Gun Barrel Spotfire template, as it’s preconfigured to automate this workflow. This template will be published soon, stay tuned for updates!

Select the Gun Barrel, mark a group of wells on the Map Chart, then click the “Update Gun Barrel” button on the left side menu. And that’s it! You have kicked off the calculation for the 3D distance between the horizontal midpoints of each selected wellbore. Just monitor the Spotfire notifications area to see when the function execution completes.

Figure 10: Map Chart: select wells

The map chart above is displaying the horizontal midpoint X Y points. Depending on your preference, you can change these to the heel or toe if you have those points available to you in your data set.

After running the gun barrel calculation, the results are displayed in four different visualizations to help the user interpret these findings. Each will be explained below.

Figure 11: Gun Barrel Spotfire Template: (Side menu Update Gun Barrel Button)

The “Spacing Report” cross table shows a tabular view of the data. This takes each combination of wells and displays the 3D distance between each of the combination pairs (e.g. A to B, A to C, and B to C. This view also provides the distances dx, dy and dz of each of the midpoints between the well pairs, and a flag indicating whether the combination crosses a horizon interval.

Figure 12: Spacing Report: Tabular View

A table is great for looking up specific values; now let’s look at the visual representation of the same data. The Gun Barrel diagram helps to do this. The Gun Barrel diagram displays the data in a 2D vertical cross-sectional view through, and perpendicular to, all wellbore lateral section midpoints, allowing the user to view the horizontal midpoint wellbore paths head on, (as if staring down the barrel of a gun).

Figure 13: Gun Barrel Visualization

Important note: This is a 2D vertical cross section showing the midpoint along the lateral of the selected wells, regardless of whether they are in a direct line or are spatially staggered from a bird’s-eye view.

Figure 14: Using the spacing report and Gun Barrel together to interpret the data.

With these two views it is possible to quickly interpret the gun barrel calculations and visualize the spacing results.

Lastly, viewing this data in map view and a 3D subsurface view help to further orient the user to the well’s spatial position in the field (shown below).

Figure 15: 3D Subsurface view and Map Chart view.

Note that the Map chart shows the horizontal portion of each selected well, with the heel and toe points colored by their respective formation intervals. In the above example, the black dots represent the lateral section midpoints of each well.

Let me know if you have any issues with the above procedure. Good luck making your gun barrel plots and spacing reports!

Categories
Data Science & Analytics Transfer

What Do Cancer Models Have to do with Oil and Gas?

Dr. Luay Nakhleh, J. S. Abercrombie Professor of Computer Science at Rice University, spoke at the second Petro Community event on the importance of accounting for uncertainty when modeling complex systems like cancer growth or well performance.

Insights gained from one domain, like computational biology, can often be leveraged in other domains, like petroleum analytics, because they uncover better ways of modeling complex data to discover patterns and make more informed observations.

“Computer scientists get training in modeling and formulating problems,” states Dr. Nakhleh. “A model is an abstract representation of a system to explain some of its features, and how detailed a model is depends on the questions being asked.”

Watch more of Dr. Nakhleh’s talk to discover how he deals with modeling uncertainty in his research. Do you think this resonates with your work in oil and gas? Why or why not?

Categories
Drilling & Completions Reservoir Engineering Transfer

Gun Barrel Diagram: Calculate and Visualize Well Spacing Part 1

Introduction

The Petro.ai Gun Barrel workflow allows the user to quickly find the 3D distances between the midpoints of the lateral section of selected nearby horizontal wells. This critically important information was once only possible to calculate using specialized geoscience software or through painstaking and time-consuming manual work. With the Petro.ai integrations, we can now calculate this information directly from Spotfire:


Figure 1: Petro.ai Gun Barrel View

Categories
Drilling & Completions Transfer

From Science Pads to Every Pad: Diagnostic Measurements Cross the Chasm

My energy finance career began in late 2014. As commodity prices fell from $100 to $35, I had a front row seat to the devastation. To quote Berkshire Hathaway’s 2001 letter, “you only find out who is swimming naked when the tide goes out.” It turned out that many unconventional operators and service businesses didn’t own bathing suits. My job was to identify fundamentally strong businesses that needed additional capital … not to survive, but to thrive in the new “low tide” environment. To follow Buffett’s analogy, I was buying flippers and goggles for the modest swimmers.


Following 18 months of carnage, commodity prices began to improve in 2016. Surviving operators had been forced to rethink their business models: pivoting from “frac ‘n’ flip” to “hydrocarbon manufacturing”. Over the following two years, I familiarized myself with hundreds of service companies and their operator customers. The entire industry was chasing two seemingly conflating objectives: 1) creating wells that are more productive 2) creating wells that are less expensive. This is the Shale Operator Dual Mandate: make wells better while making them cheaper.

Shale Operator Dual Mandate


As an oil service investor, I was uniquely focused on how each company I met helped their customers accomplish the Shale Operator Dual Mandate. Services that achieved one goal would likely survive, but not thrive. However, those that helped customers meet both goals were sure to be the winners in the “new normal” price environment of $50 oil.

Transformations happened quickly throughout the OFS value chain. Zipper fracs drastically improved surface efficiencies, ultralong laterals were drilled further than ever before, in-basin sand mines appeared overnight, and new measurements came to the fore. These new measurements deliver incredible insights: fracture half length, well productivity by zone, vertical frac growth, optimal perforation placement, and much more.

In Basin Sand

New Measurements

While zipper fracs, long laterals, and local sand have taken over their respective markets, new measurements have struggled to gain traction outside of “science pads”. Frustrated technical service providers bemoan the resistance to change and slow pace of adoption in our industry. These obstacles failed to slow the advance of zipper fracs, long laterals, and local sand … why have disruptive new measurement technologies been on the outside looking in?

Challenge #1: Unclear Economics

The first challenge for new measurements is unclear economics. Despite the recent improvements, unconventional development remains cash flow negative … and has been since its inception.

The above data suggests ~ $400B of cash burn since 2001 … small wonder operators are wary of unproven returns on investment! (Note: to be fair, operators were incentivized by capital markets to outspend cash flow for the great majority of this period. Only recently has Wall Street evolved its thinking to contemplate cash on cash returns, as opposed to NAVs).

For any technology to become mainstream, it must either immediately lower costs (e.g. zipper fracs, local sand) or have obvious paybacks (e.g. long laterals). New measurements, by contrast, do not clearly map to economic returns. Instead, these service providers tend to focus on “interesting” engineering data and operational case studies. Operators will not put a technology into wide use until its economic impact is fully understood. This can mean waiting months for offset wells to come online or years for neighboring operators to release results.

Challenge #2: Changing How Customers Work

The second challenge, which is just as important to end users, is that service providers must deliver insights within a customer’s existing workflow. Operators are busier than ever before. E&P companies have experienced waves of layoffs, leaving those remaining to perform tasks previously done by now-departed colleagues.

In addition, many service providers don’t appreciate the opportunity cost of elongating an existing customer workflow to incorporate new variables. A smaller staff is already being asked to perform more work per person; it should be no surprise that customers are hesitant to allocate budget dollars to perform even more individual work.

Challenge #3: No Silver Bullets

While each new diagnostic data type is an important piece of the subsurface puzzle, no single element can complete the picture on its own. Instead, each measurement should be contextualized alongside others. For example, fiber optic measurements can be viewed alongside tracer data to better determine which stages are contributing the most to production. When each diagnostic data source is delivered in different medium, it becomes nearly impossible to overlay these measurements into a single view.

The Oxbow Theory

The combination of the above factors leads to the “Oxbow Theory” of new measurement abandonment. As you may know, as rivers age, certain sections of the river meander off course. Over time, sediment is redistributed around the meander, further enhancing the river’s bend. Eventually, the force of the river overwhelms the small remaining ‘meander neck’, and an oxbow lake is created. Sediment deposited by the (now straight) river prevents the oxbow lake from ever rejoining the river’s flow. By the same token, new measurement techniques that do not cater to existing workflows may be trialed but will not gain full adoption. Instead, they become oxbow lakes: abandoned to the side of further-entrenched workflows.

Our Solution: Petro.ai

Petro.ai is the only analytics platform designed for oil and gas. If you’re an operator, we can help make sense of the tsunami of data delivered by a fragmented universe of service providers. If you’re a service company, we can help deliver your digital answer product in a format readily useable by your customers. Please reach out to info@petro.ai to learn more.