Daniel T Shaw Principal Molten Consulting. 12Sep2014. Data - the Oil & Gas Asset that isn t managed like one. Presented by Daniel T Shaw

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1 Data - the Oil & Gas Asset that isn t managed like one Presented by Daniel T Shaw Copyright 2013 and 2014 Molten Group 1 Daniel T Shaw Principal Molten Consulting Daniel is a performance leader with over 30 years experience working on capital projects, mostly in the oil, gas and energy industries. Clients appreciate his quantitative analysis and instigation of lessons learned, as Daniel has worked with and brings the experiences of over 200 project teams. Daniel has managed the design of upstream projects. His successes include leading, influencing and managing change in major organizations, conceiving and developing innovative strategies, planning and realizing improvements to business processes, quantifying opportunities and negotiating value driven contracts. He also has significant experience in coaching colleagues and staff to anticipate, plan and deliver. Daniel works in English and French. A chartered engineer and member of the Society of Petroleum Engineers, his qualifications include MSc in Financial Economics and BSc(Eng) in Mechanical Engineering. daniel.t.shaw@molten-group.com Copyright 2013 and 2014 Molten Group 2 1

2 Prize Draw Every entrant receives a soft copy of the slide pack Copyright 2013 and 2014 Molten Group 3 Data - the Oil & Gas Asset that isn t managed like one Quantify the value of your data Identify examples of poor data management Include all components in assessing data management Influence the role of data in your business Express data management capability and its relationship to corporate results Challenge suboptimal performance Promulgate excellence Copyright 2013 and 2014 Molten Group 4 2

3 Examples of poor data management in Oil & Gas Exploration Wells An individual (now retired) was in conversation with the head of region as they were about to abandon exploration rights. He pointed out that data had been acquired 15 years previously. After searching the office, the report was found under a desk. The outcome was recognition of a target worthy of exploration which would have been given up due to the lack of good data. Root cause poor management of exploration data The geodetic references for two separate data sets on an onshore gas prospect were different. However, the two data sets were combined using the same geodetic reference. The resulting analysis concluded that prospectivity was poor. Some time later an intern came across the anomaly and reported it. The appraisal was rerun and showed high prospectivity. An appraisal well was drilled as a consequence, resulting ultimately in one of the highest flow rate gas wells in North America. Root Cause poor management of geodetic data Subsurface Field tapes containing critical seismic lines went missing in a particular Business Unit. Consequences included loss of operating licenses and substantial fines from the State. Production Poor/inconsistent workflows across disciplines led to using faulty fluids models in fiscal allocation calculations. The impact was $3 million per year, for 6 years. Root cause poor management of seismic data Root cause poor management of reservoir fluids data Copyright 2013 and 2014 Molten Group 5 Data is a common business problem Data is both a management and a technical challenge Strategy People Process Technology & Tools Data Strategic objectives Strategic goals for critical business decisions to aim towards Standard organizational model Critical decisions taken to achieve strategic goals Business-wide common processes Clear, consistent critical decision making processes Standard tools and applications Tools to simplify and accelerate processes Proactive management of the data tier Accurate, complete, timely, accessible data to drive decision based on facts These three impact each other. Changes to any one will have an impact on the other two, and hence they need to be managed in association. Copyright 2013 and 2014 Molten Group 6 3

4 How much does your company spend on Data a year? Copyright 2013 and 2014 Molten Group 7 How to Quantify the Value Your Data Profit Improving business efficiency and better operational results from better informed decisions Acquisition Cost Obtaining data of satisfactory quality is expensive and requires careful specification Data Processing Cost The cost of storage, processing and dissemination of information and avoidable rework Risk Operating with bad data jeopardises licences to operate, or risks catastrophic loss Copyright 2013 and 2014 Molten Group 8 4

5 Evaluating Return on Investment of Data Forensic Analysis Costs and value of data management, for different functional areas in different geographies and target benefits : Differences in ROI can be questioned and explained. Strong rates of return can be identified and focused upon High value activities can be identified, maintained and improved where possible. Value* Planned cost Challenged cost Low value activities can be identified and targeted for cost reduction. Relatively poor rates of return can be challenged. Capital and operating expenditure require separate evaluation methods and must be clearly segregated. Regions or Assets Functional Activity Breakdown Copyright 2013 and 2014 Molten Group 9 Role of Data across the oil and gas value chain Copyright 2013 and 2014 Molten Group 10 5

6 How is Data managed in Oil & Gas companies? Copyright 2013 and 2014 Molten Group 11 Reserves growth vs. data management capability Copyright 2013 and 2014 Molten Group 12 6

7 What is Big data and what is its impact on Oil & Gas? The Oil and Gas sector perceives over 40 years of experience of Big data as they routinely splice and dice large complex data sets like seismic, well logs and reservoir models, to deliver key insights that drive critical decisions such as field development concept selection, depletion strategies and enhanced oil recovery plans Big data is a collection of complex data sets so large that they are often difficult to process using traditional database management tools or data processing applications. Opportunities Completely new business models Comparisons based on data, e.g. reliability Algorithm based decisions, e.g. safety New ways to manage customer, regulator or government expectations Challenges There are many and we need to work out how to deal with them: Access, analysis, capture, curation or maintenance, definition, secure deletion, presentation or visualization, search, sharing, security, storage and transfer. Copyright 2013 and 2014 Molten Group 13 Data Growth into Big Data Source: IBM Investor Briefing, Innovation Gallery Introduction by Dr. John Kelly, 2013 This chart shows raw data volumes. Processing data in context typically means about 1000 times that volume. Copyright 2013 and 2014 Molten Group 14 7

8 World class data and information management A framework to define world class data and information management This framework can be applied to assess your data management processes, strategy and capability against your peers, your business strategy, your ambition and can help to define a roadmap to bridge performance gaps Copyright 2013 and 2014 Molten Group 15 Key take aways 1. Data costs huge money 2. It s not enough for executives to consider people, process and technology when assessing their business initiatives. Now we must consider data too 3. Data management has been a career cul-de-sac. This point is emblematic of the whole data management issue 4. Get it wrong and it s wrong on a micro and a macro scale 5. Get it right and significant efficiencies flow Copyright 2013 and 2014 Molten Group 16 8

9 Finally Data has significant value The value can be articulated The value justifies a rigorous approach to its management Three critical success factors: Clear setting of accountabilities (governance) for data within the business Ensure that fit for purpose data is provided It must be a career Copyright 2013 Molten Limited 17 Molten s Expertise and Services Molten is a transformation consultancy that is focused on business performance improvement in the Energy Sector, building capabilities and improving operations, driving results to the bottom line with increased throughput, efficiency and safety. Organisation Operating Model Development Organisation Design Talent Management Change Management Technology and Data IT Technology Oilfield Technology Process Improvement Assessment and Strategy Process Improvement Data Analytics Data Management Performance Benchmarking and Design Systems Diagnostics and Design Copyright 2013 and 2014 Molten Group 18 9

10 Get in touch For more information or to read on "How oil and gas executives could use Big Data as a powerful source of competitive advantage," please visit our website here. Connect Like Follow Copyright 2013 and 2014 Molten Group 19 Contact us Molten Americas 4306 Yoakum Blvd Suite 350 Houston, Texas USA daniel.t.shaw@molten-group.com United Kingdom 22 Grafton Street Mayfair London W1S 4EX United Kingdom Copyright 2013 and 2014 Molten Group 20 10