This document provides an overview of AGR Software and their probabilistic well planning software P1. AGR Software is a Norwegian company that delivers web-based applications to the oil and gas industry, focusing on replacing manual processes. Their suite of applications include P1 for probabilistic time and cost estimation, CT for tracking actual time and cost against estimates, and Ex for creating lessons learned. P1 allows users to build probabilistic time and cost models using Monte Carlo simulation for more accurate budgeting and risk assessment. It provides a structured, collaborative approach with continuous new functionality added like campaign modelling, custom tagging and filtering of results, and auto-fitting of offset data distributions. P1 aims to help standardize processes

1. Øystein Andersen - Vice President – AGR Software
Email: oystein.andersen@agr-software.com Tel.: (+47) 959 21 003
Presentation for Middle East Drilling & Completions Conference 2023
«Upscaling Geothermal Developments Via Standardizing And Value Engineering”
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2. AGR Software – Brief Summary
• Norwegian company, part of Aker/Akastor group, 20 employees
• Delivering web-based applications to oil and gas industry (D&W teams) since 2010
• Focusing on replacing manual processes and repetitive work, while allowing engineers to still be
engineers
• Applications should bring value both short term (immediately) and long term (build company
knowledge) and be used for any type of D&W project
• Applications are built on modern architecture and can integrate with other applications/ infrastructure
through API
• «It’s better to make some applications really well, than to make a super-system where everything is
half-way»

3. AGR Software – Suite of Software Applications
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• Build your probabilistic time and cost model
in P1 and generate AFE
• Track your actual time and cost in CT
against AFE, and provide oversight to
stakeholders
• Create lessons learned in Ex during
operations
• Reuse data from CT, Ex and previous P1
models to create new P1 models
• View/maintain the company’s overall rig
schedule using the RIG application
LEARN
TRACK
PLAN RIG
Focus for presentation

4. Software is used all over the world
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First Geothermal Application

5. Why probabilistic approach to well planning?
• More accurate results using probabilistic vs deterministic approach (given same input)
• “Something always happens”. A probabilistic approach allows for including risks in your model
• But…
STUDENTS ABOUT STATISTICS
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6. Monte Carlo simulation
• Particle physics
• 3D visualization and rendering
• Geology and geophysics
• Project time and cost frame estimation
• Anything!
Core value: Probabilistic Modelling reduces uncertainty, thereby improving “guesstimates” substantially.
For time and cost estimation: More accurate budget, best-case and worst-case scenarios.
What is the value of accurate budgets, best case and worst-case scenarios?
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7. P1 – Probabilistic Time and Cost Estimation Software for D&W
• Structured methodological approach
• Modern (Cyber-security compliant, can be
integrated with, local deployment possible)
• Collaborative (invite team members to
projects)
• Simple and intuitive
• Robust
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8. Deep Geothermal Drilling Operations (4000m+)
• Complicated wells
– High temp
– Rough drilling
– Challenging cement jobs
– Many other risks
• More cost sensitive than oil & gas projects
• Often low-spec land-rigs used
• Historically, more basic services (hardware,
software) used…
“We aim to develop our projects using
state-of-the-art technology. This also
includes thinking outside the box and
making technologies that have proven
valuable in other sectors, such as iQx,
usable for deep geothermal energy”
Deutsche ErdWärme Project Manager
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9. The way forward – New functionality released continuously…
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• Campaign functionality with learning curve application
 Relevant when many wells after each other with same stakeholders
• Define Company Structure for projects (names of levels, allowed entries for levels)
 Standardization across business units and applications
• Import offset data (from e.g. DDR system, casing design software or financial system)
 P1 will «auto-fit» the appropriate input distribution
• Generic tagging function to allow for «selective simulations» and results
 Results with/without NPT, how much cost comes from a specific vendor? Top hole contribution to
campaign?
• Introduce own equations (e.g. Carbon Footprint)
 Largely time-dependent, should be calculated using probabilistic method (same as cost)

10. Campaign Modelling
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You can define as many hierarchal levels as you want and name each level according to company
specific standards.
This example highlights a 3-well sequential campaign with four levels (FieldWellPhaseEvent).

11. Dedicated Settings area for Super Users (Time)
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Define the hierarchal structure (with custom
names) and parent-child relationship
Select pre-defined custom names/codes for the
different levels

12. Tagging and Filtering (1/2)
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13. Tagging and Filtering (2/2)
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Apply filter
“Exclude NPT from the simulation result and I am only interested in
viewing the cost contribution from SLB”

14. Auto Distribution
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Offset data samples inputted manually
or from API connection
PDF/CDF curves representing offset samples

15. Questions or comments?
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Please feel free to visit our stand also!