Quantified Value Creation through Data Flow Optimisation

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Quantified Value Creation through Flow Optimisation Chew Wei Liang Group Technical (GTD), Project Delivery & Technology (PD&T) 2016 PETROLIAM NASIONAL BERHAD (PETRONAS) All rights reserved. No part of this document may be reproduced, stored in a retrieval system or transmitted in any form or by any means (electronic, mechanical, photocopying, recording or otherwise) without the permission of the copyright owner. Petroliam Nasional Berhad (PETRONAS) 2016 1

Introduction What is Flow? flow is a diagram that documents data types and/or attributes that flow between two (2) or more entities in a domain space. Entities may be processes, applications or databases. Domain spaces may be sedimentology, petrophysics, biostratigraphy etc. or even subsets of these. Seismic Interpretation Workflow Seismic-Well Tie Structural & Stratigraphic Mapping -Fault Interpretation -Horizon Interpretation Seismic Attributes & QI Study Velocity Model & Time Depth Conversion Seismic Checkshot/VSP Sonic & Density Logs Geologic Markers Synthetic Curve New Time-Depth Wavelet Calibrated Sonic Fault Polygon Fault Stick 3D Structure Map Time Structure Map Seismic Attributes Reference Facies/Fluid/Litho Maps or Volumes MDM Derived DB Depth Structure Maps Fault in Depth 3D Velocity Model Polynomial Function Residual Map MDM Master Management DB base VSP Vertical Seismic Profile Petroliam Nasional Berhad (PETRONAS) 2016 2

Seismic to Well Tie As-Is Requirements Gathering Request Quality Control (QC) Seismic Well Tie 7% Search Reports Archive Study Reports Request from colleagues 40% 53% Requirements Gathering & Search QC & Review Interpretation 50% 50% Types Required Well Header Well Tops Well Deviation Checkshots/VSP Seismic Well Logs Sonic Density GR Deliverables Synthetic Curve New Time-Depth Wavelet Calibrated Sonic Note: * Average number of days based on our interviews. Problem Statement 52% of business users' time are spent on data-related matters such as data gathering & searching, quality control (QC) and loading based on 10 key workflows in Field Development Plan (FDP). Petroliam Nasional Berhad (PETRONAS) 2016 3

The Importance of Quantifying Flow Optimisation Increase Reserves Asset Development Increase Production as an Asset management framework Productivity Eliminate data downtime Risks Decrease bad & non compliance data. Cost Reduce operational cost Defined data flows and standards quality metrics (DQM) Corporate data & master data Reduce repetitive data QC tasks reusability Effective data access and retrieval Avoid data leakage. Utilising the right data and the right format. Increase accuracy in deliverables. Improved lifetime value of Exploration and Production (E&P) data Shorter project timeline Reduce churn Petroliam Nasional Berhad (PETRONAS) 2016 4

Case Study Collation & QC for Development Project Petroliam Nasional Berhad (PETRONAS) 2016 5

Overview of the Use Case Why are we doing this? To assure all priority data required are made available to the development team to start work in FDP. What are the selected projects? What is the goal? All priority Types are QC-ed and signed off by appointed Subject Matter Experts (SMEs). Greenfield Brownfield When to deliver? Where do we focus? Assurance Priority Types 3 months to collate, QC and assure. Petroliam Nasional Berhad (PETRONAS) 2016 6

Methodology August 2015 Oct 2015 Identify key workflows and data types for each discipline. Identify mandatory data types required by FDP (subsurface). Analyse and prioritise the data types. Ensure that the collated data for both projects are QC-ed by appointed SME/TP. Capture existing QC processes and ensure the QC is based on the processes. Ensure that the QC process is adhered to and QC-ed data types are signed off. Audit trail. Type Availability QC Accessibility Assurance Types 107 Workflows Collate the data available for both projects based on the mandatory data types. Ensure data are able to be delivered to users effectively. Identify data types that do not have a corporate databank. Ensure users know the quality of the data downloaded. Petroliam Nasional Berhad (PETRONAS) 2016 7

Quantified Time Saving A FDP flow Optimisation Survey 2015 Project Team 10 Workflows Assessed out of 135 Types Captured: 40 Req. Gathering, Search, Gathering & QC 226 days* B FDP Collation & QC -Brownfield Time Spent by the project team Searching QC 33% time saved Total Workflows Covered: 107 Types Captured: 56 FDP Project Team FDP Team Time Saved 80 days FDP Project Team 54.5 days 17 days 2 Feb 21 Aug 31 Oct Collation & QC 151.5 days 74.5 days Petroliam Nasional Berhad (PETRONAS) 2016 8

FDP flow Optimisation: Non Quantitative Benefits Quality Final QC-ed data unique and non ambiguous ensuring less clarification needed (improved data quality) Capturing of the existing QC processes help to assure the data quality To view data in an integrated way Accessibility Access to available QC-ed data types enables teams to collaborate better Inter-Disciplines Collaborations Strengthen the collaboration between Technical and Project Teams by clearly introducing the role of Technical Improve efficiency in data management Petroliam Nasional Berhad (PETRONAS) 2016 9

Summary 75 days 7 projects 525 days Time Saved Calculated time saved for a brownfield project Project Selected 7 developments project selected for second phase NEW OPPORTUNITIES Estimated Savings Estimated 1.5 man years of saving for the 7 projects Develop new QC processes Additional data types in Quality Inventory (QDI) Identified new Corporate banks Master Priority Well List Additional data types in Access & Retrieval (DART) Petroliam Nasional Berhad (PETRONAS) 2016 10

Thank you Petroliam Nasional Berhad (PETRONAS) 2016 11