RockPile Energy Services
RIC S Proce ss De scri pt ion
A Multi Company, Multi Disciplinary Team
developed to Identify, Analyze, Quantify, De-Risk, and Rank Candidates
to meet Customer’s Economic Returns Requirements
Customer
Potential
Intervention
Candidates
RockPile
Sigma3
Well
Data
Base
Quantico
• Geomechanical Properties from
Drilling Data
• Big Data Analytics for Candidate
Recognition
• Pumping Services
• Engineering Services
• Workover Rigs
• Operations in Field
• Production Engineering
• Reservoir Engineering
• Fracture Engineering
• Micro seismic
• Software Solutions for
dynamic 3D Geo-Models
• Oil & Gas Mapping
• Data Management
• Custom programming to aid data analytics
• Hosting, Bandwidth, Security, and Support of team
De-risked
Candidates
Design to Fit
Completions
Technology
Proprietary
Analytics
Massive
Public
Domain Data
RICS Process Employs “Large Data Analytics”
for Fast Efficient Screening of Candidates
Proprietary Diversion Technology Fit for Purpose
• Customized tri-modal diversion blends designed for all diversion needs:
- Sliding Sleeves (large surface area)
- Phased perforations in a lateral
• Near Field Diversion with post diversion conductivity retention
• Partnerships with industry leading mechanical diversion developers to
deploy expandable casing liners and patches
Diversion Slide
Diversion Blend in Laboratory Slot Test
Bridging within the fracture slot
How does RockPile’s RICS Lower Risk on Refracs?
7
Feature Benefit
RICS Team Integrated Team of Industry Experts to provide all
services within the Refrac domain
Proprietary “Large Data Analytics”
(Nested Neural Net) Engine
Ability to review large quantities of Data and isolate
optimal candidates
Candidate Rankings Performing Interventions on highly ranked wells
lowers your chances of uneconomic recompletions
Agreed upon Success Target Understanding the financial definition of success
from each client gives benchmarks for post refrac
analysis
Customizable Business Model Traditional Services Model
Risk Reward Model
Third party financing model
Summary
• Interventions are prescreened to help insure success
• Client defines the financial parameter for success
• Candidate selection represents the universe of wells that meet/exceed
customer target parameter.
• Diversion technology selected in Fit for Purpose design to maximize diversion
success
• RICS team performs candidate selection autonomous from client’s team
freeing up client resources to stay on their internal business objectives
• Interventions are designed and performed with most current technology
• Flexible business model allows for any structure desired by the client
8
Short RICS overview presentation

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Short RICS overview presentation

  • 1. RockPile Energy Services RIC S Proce ss De scri pt ion
  • 2. A Multi Company, Multi Disciplinary Team developed to Identify, Analyze, Quantify, De-Risk, and Rank Candidates to meet Customer’s Economic Returns Requirements
  • 3. Customer Potential Intervention Candidates RockPile Sigma3 Well Data Base Quantico • Geomechanical Properties from Drilling Data • Big Data Analytics for Candidate Recognition • Pumping Services • Engineering Services • Workover Rigs • Operations in Field • Production Engineering • Reservoir Engineering • Fracture Engineering • Micro seismic • Software Solutions for dynamic 3D Geo-Models • Oil & Gas Mapping • Data Management • Custom programming to aid data analytics • Hosting, Bandwidth, Security, and Support of team
  • 4. De-risked Candidates Design to Fit Completions Technology Proprietary Analytics Massive Public Domain Data RICS Process Employs “Large Data Analytics” for Fast Efficient Screening of Candidates
  • 5. Proprietary Diversion Technology Fit for Purpose • Customized tri-modal diversion blends designed for all diversion needs: - Sliding Sleeves (large surface area) - Phased perforations in a lateral • Near Field Diversion with post diversion conductivity retention • Partnerships with industry leading mechanical diversion developers to deploy expandable casing liners and patches
  • 6. Diversion Slide Diversion Blend in Laboratory Slot Test Bridging within the fracture slot
  • 7. How does RockPile’s RICS Lower Risk on Refracs? 7 Feature Benefit RICS Team Integrated Team of Industry Experts to provide all services within the Refrac domain Proprietary “Large Data Analytics” (Nested Neural Net) Engine Ability to review large quantities of Data and isolate optimal candidates Candidate Rankings Performing Interventions on highly ranked wells lowers your chances of uneconomic recompletions Agreed upon Success Target Understanding the financial definition of success from each client gives benchmarks for post refrac analysis Customizable Business Model Traditional Services Model Risk Reward Model Third party financing model
  • 8. Summary • Interventions are prescreened to help insure success • Client defines the financial parameter for success • Candidate selection represents the universe of wells that meet/exceed customer target parameter. • Diversion technology selected in Fit for Purpose design to maximize diversion success • RICS team performs candidate selection autonomous from client’s team freeing up client resources to stay on their internal business objectives • Interventions are designed and performed with most current technology • Flexible business model allows for any structure desired by the client 8

Editor's Notes

  • #3: The statement in black on this slide sums up the entire effort of what the RICS process is and why it is important to our customers. A Multi Company, Multi Disciplinary Team developed to Identify, Analyze, Quantify, Derisk, and Rank Candidates to meet Customer Multi Disciplinary Requirements The system needs to be able to review large amounts of public domain data and from that identify the potential candidates. Once identified, we need to analyze the wells in three major ways Stimulation Index (how was the well originally completed versus how we might do it today)? Productivity Index How has this well performed compared to peers, and taking into account its original completion method Reservoir Index What can we learn about the well related to its reservoir quality. Dis the well perform as it did due to reservoir quality or in spite of reservoir quality? Once they are analyzed we run production analysis to optimize a frac design. From this we run economics models and risk models to rank the wells and predict their economic returns based on the customers requirements. Wells that meet this final hurdle are then presented to the customer as RICS process wells. This leads to the designed intervention being run.
  • #4: In addition to what each team member brings to the RICS group, they have added services that can be used to enhance the solutions we provide to our customers. Each company shown represents a best in class company for the expertise they provide and together “The whole is greater than the sum of the pieces”
  • #5: This graphic is designed to represent a very complex process in a simplistic manner. The funnel represents the RICS engine and its ability to take vast quantities of data and to distill it into specific candidates that represent the best chance for customers to reap optimal financial benefits from their inventory of aging wells. It incorporates all available public domain data, proprietary data from customers on their wells (not required, but beneficial), proprietary filtering analytics, and customized recompletion designs that incorporate best of class completion technology into a tool to deliver de-risked candidates that will meet or exceed the customers definition of success….ie exceeds X% IRR or deliver Y% ROI etc.
  • #8: This slide is designed to push the differentiation we provide to the customer from other pumping companies. RICS Team represents a broad array of talents and expertise. We represent a Virtual Extension of the Customers Staff that can be working refrac and intervention arena even if the customers team is busy with the new drill market Proprietary Large Data Analytics differentiates us from competitors as well as customers. This is the first of its kind in the industry engine to review big data sets and return viable candidates quickly, efficiently, and without the human bias that can impact success of interventions Candidate Ranking provides a means of selecting target wells based on an economic return versus any other criteria. Since our customers make all decisions based on rate of return, it only makes sense that we present the candidates in a similar manner Understanding what defines success financially for the customer will allow us to queue up the candidates that meet or exceed this parameter. Other wells can still be recompleted, but it now becomes a “business decision” for the customer, knowing what they now know rather than guessing at which might work, thus reducing poor performers from the refrac candidates. Customizable business model allows maximum flexibility for our customers. From our traditional model, to a risk reward, even going so far as to arranging outside funding of projects that might not have internal spending support, but could easily support outside funding. These all help RockPile to provide what the customer wants, when they want it, and how they want to pay for it.
  • #9: This summary is meant to reinforce differentiators that we bring to the market in the Refrac domain.