With JMP data analysis software, oil and gas leaders can create intelligence from new data sources and manage everything from optimizing exploration in unconventional wells to improving downhole process efficiencies – all without needing to learn to code.
Oil and Gas Industry Production – So What?
Industry production by Oil and Gas includes a vast array of activities like exploration, drilling, well completion, production, separation and treatment, storage and transportation, processing, sales, and usage.
Oil and Gas contributes to more than 57% of energy of the whole world. Our modern civilization including our energy infrastructure and transportation systems, are largely based on the Oil and Gas Industry.
Image source: https://www.bilibili.com/read/cv10075430
Chemical production is a critical piece of Oil and Gas. About 70,000 kinds of chemical products come from oil. These products are vital, serving industries like agriculture, transportation, machinery, electronics, textiles, lighting, construction, geology, and building materials.
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石化产品生产流程图_文档下载 (docsou.com)JMP in action
How does the pivotal Oil and Gas Industry tackle their most difficult scientific and engineering problems in JMP?
Geophysicists and reservoir engineers must perform necessary quantitative analyses before oil production can begin in earnest, so they use JMP to understand the nature of your reservoirs’ properties, to optimize hydrocarbon recovery, and leverage well logs and seismic data to interpret information and make better production decisions.
Drilling and Completions Engineers are under rising pressure to mitigate costs while also maximizing well performance. They use JMP to build an analytical drilling strategy to improve efficiency and drive out unnecessary costs, detect equipment malfunctions to reduce drilling downtime and to improve completions efficiency.
Chemists routinely investigate manufacturing steps in downstream processes to understand the complex factors affecting quality, yield, and production costs associated with chemical production. Using JMP they can more effectively monitor crude oil and gas processes to ensure consistent product quality and identify possible batch failures faster and automate analysis workflows to save time in preparing status and summary reports for project stakeholders.
As Stephen Brammer from Brazca attests, they have obtained great value from JMP in the face of the challenge of evaluating complex geospatial information to determine opportunities for mineral extraction in Africa. Stephen and his team used JMP Scripting Language (JSL) to construct a new method for geostatistical cluster analysis. Their novel approach, implemented exclusively with JMP scripts, saved them time and money and led to more rapid and actionable business decisions in response to change geological conditions. An extended application for their solution might include myriad disciplines in the natural sciences and other fields where the spatial position of data matters, for example, in image processing, logistics, marketing and pattern recognition.
JMP Customer Success Stories and Sales Wins in “The OG” Industry
ExxonMobil has grown from a small regional outfit to one of the world’s largest publicly traded companies and pioneering early advocate of digital transformation. Recently, ExxonMobil Operations in Asia Pacific outlined a multivariate process monitoring and analysi
s system in JMP that would enable engineering teams to execute on their vision of moving to more predictive or even prescriptive approaches to process monitoring.
This deal achieved a combined value proposition of more than $5 million per year and 30% reduction in process monitoring analysis time.
There are many examples of companies today in OG that use JMP including, but not limited to:
ExxonMobil is perhaps the best example of a company in the industry to utilize JMP for tremendous organizational savings and continuous process improvement:
- Customizations in JMP created a user-friendly, scalable tool for extreme value analysis that helped optimize inspection processes and eliminated human error. This initiative generated $200,000 in annual savings with strong scale-up potential for any application involving extreme value analysis.
- When a step-change quality improvement was needed, the Global Surface Spot Team used the Functional Data Explorer (FDE) platform in JMP along with principal components (PCA) and outlier analysis (Explore Outliers) to realize $200,000 in annual savings.
- A customized take-or-pay contract optimization tool developed in JMP provided ExxonMobil contract negotiators with cost savings potential of as much as $10 million, yielding a major competitive advantage during contract negotiations.
Industry Showcase with the Well-Trace Add-In
This example demonstrates how a powerful yet relatively simple application – empowering users to visualize the trajectory of drilling quickly and easily form their own 3D coordinate data – enhances product “stickiness” by making use of JMP’s dynamic and fast visualization capabilities.
Using the Well-Trace Add-In, developed by Systems Engineer Peter Polito at JMP, only three inputs are needed to reconstruct the entire three-dimensional drilling path taken by a drill bit to efficiently access and drill for well oil extraction.
The three inputs needed are those gathered via a directional survey, and they are Depth, Inclination and Azimuth. Depth is essentially the total distance drilled into the well. Inclination is the wellbore between survey points which basically follows incremental stairsteps (0 to 90 deg increments). Azimuth is the compass direction, that is, the relative to true north. Given just these three inputs, the Add-In can be used to reconstruct the drilling path taken in three dimensions (in X, Y and Z directions; also known as the well trace) quickly/easily in JMP.
Consider the following example, where inputs were generated and reported in JMP, and where the X-Y-Z coordinates were generated and plotted with the Add-In through the Scatterplot 3D Platform (Graph > Scatterplot 3D).
Additional information about the geometrical calculations used to reconstruct the visual trace of the well can be found in in the reference article1. The analysis shown below is from the sample data file WellTraceExampleData.jmp linked directly herein, and also available on the JMP User Community(2).
Preview of Data Frame available in JMP: (n=123 observations)
We cast the variables: Depth, Inclination and Azimuth into their respective roles within the Add-In start dialogue window, and then Click OK to launch the 3D Scatterplot.
Selected rows can be assigned a custom color to make them more visually distinct:
For example, we can see that at a depth of 4,963 ft to 6,108 feet, the rate of change of TVD is relatively consant (indicated by points marked in red) and then starts a sudden rapid increase (in the direction of increasing depth) at approximately 8,401 ft (indicated by points marked in purple):
Note that additional customizations can be made to the 3D Scatterplot for enhanced visualization by simply right-clicking over the graph area and then selecting Settings (3D Display Settings):
Finally, additional aspects of the relationship between Depth, Inclination, and Azimuth can be explored in JMP using the Graph Builder Platform (Graph > Graph Builder), and using JMP’s dynamic linking capability to see the relationships among the variables:
Data View can be invoked as a right-click option under Selected Rows, to show only the rows in the data table that are actively selected by the user (these are opened in a separate linked data table view as shown below):
Data Analytics in a Competitive Landscape: Why JMP?
So, given the litany of other analytics software tools and programming languages available today – not the least of which include: Python, Matlab, Tableau, Spotfire, and R – Why is JMP such a powerful solution for our customers in the Oil and Gas Industry?
JMP is fast and easy to use with a point-and-click interface and provides interactive visualization so customers can see and touch their data. This feature is perhaps the most incredible part of the software architecture for Oil and Gas scientists and engineers who want to understand their data through interaction and exploration, in much the same way that they approach any problem!
Finally, JMP offers powerful leading edge statistical methods that are readily deployable without code and provides easy integration and extensibility with popular programming languages like Python.
Acknowledgements:
We would like to thank @ChuckBoiler, @Peter_Polito, and @Jason_Wiggins at JMP Statistical Discovery, LLC, for their thoughtful contributions and unique industry perspectives from Oil and Gas. We would also like to acknowledge the work of @NicholasShelton who also brings oil and gas industry experience to JMP.
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