Visual Analytics in the New Normal: Past, Present & Future geologic Technology Showcase Adapting to the New Normal, Nov 16 th, 2017
Presentation Overview PAST How did we get here and what is the new normal? PRESENT How are innovators adapting to the new normal? FURTURE What could it look like & what challenges do we face? 2
PAST How did we get here? 3
Producing Wells In 2017 horizontal wells account for 23% of total Producing Wells 4
Gas Production In 2017 horizontal wells account for 65% of total Gas Production 5
Growth of the Montney 6
Oil Production In 2017 horizontal wells account for 79% of total Oil Production 7
Growth of the Oil Sands 8
Completions Learning Curve 9
Oil Price (lower for longer) 10
Gas Price (has been low since 2009) 11
Price Impact on Drilling Activity 12
Impacts of Low Commodity Prices Exodus of larger companies from Canada Stranded production (pipelines not approved & Petronas FID) Service price reduction is now rebounding 13
Consolidation of Producers 14
What is the new normal? 1) Prices lower for longer Smaller teams, same amount of work (~50,000 job reduction in Canada) Attempt to grow with minimal hiring 2) This will result in a greater reliance on data and technology 3) Smaller margins will create a greater emphasis on: Reduced operating costs Calculated capital expenditures Better uncertainty/risk management and planning Market sensitivity to production shortfalls 15
Market Sensitivity 2017 investors reactions to production guidance shortfalls resulted in share price reductions Reduced by 40% in 8 months Reduced by 50% in 7 months Reduced by 30% in 2 weeks Reduced by 40% in 8 months Reduced by 70% in 8 months Reduced by 26% in 1 month Reduced by 40% in 8 months Reduced by 40% in 8 months From Verdazo blog: Managing Uncertainty: the difference between Investing & Gambling 16
PRESENT How are innovators adapting to the new normal? 17
Analytics in the Royalty Review Visual analytics informed the Alberta Oil & Gas royalty review Use of geologic s Well Completion & Frac Database Consortium contribution of actual data for calibration with DOE results C* calculation evolved to include proppant Analysis was done in VERDAZO in real-time with stakeholders in the room 18
Operator Example 1: Digital Meetings 1) Bye-bye production reports paperless, digital discussions that happen in real time 2) Zero prep time for well reviews interactive live visualization and collaboration integrated analysis of production, financial, forecast & public data Example company: >$175,000 reduction in well review prep time alone 19
Operator Example 2: Digital Workshops 1) Visual analysis workshops questions explored and answered in real-time connected to live data sources (e.g. geologic data sources + proprietary data sources) reliable, repeatable, auditable decision support 2) Workshops include: Downtime reduction (e.g. $12 million net revenue improvement on 41 wells) Completion optimization (statistical, multivariate, Machine Learning) Competitor analysis Acquisition analysis Tasks that would take an entire day now take 1-2 hours or in some cases minutes with ultimately a better result Chevron Senior Engineer 20
Operator Example 3: Optimizing Revenue 1) Creative integration of multiple data sources 2) Complex algorithms to find value & plan ahead for example: Current netback analysis (supports shut-in planning for different price scenarios) Theoretical gas component vs actual sales (ensuring all liquids revenue is being captured) 21
Operator Example 4: Automation ~10,000 CBM wells (managed by 5 engineers) Avg rate = 30 mcf/day Creative use of data to develop optimization algorithms Algorithms run daily Automatically sends cleanout requests to service company 22
Analytics Adoption Adoption is strongest where data is readily available with a strong connection to a production outcome. Completions Industry adoption = moderate to high Data is readily available & of high quality Analysis: correlations, statistical, regression/multi-variate & AI/ML Drilling Industry adoption = low to moderate Data volume is massive & complex Analysis: mainly focused on basic KPI s (+ real-time) Operations Industry adoption = low Requires significant data integration Analysis: dominated by Excel (often isolated efforts by individuals) 23
Current Trends 1) Stronger integration across disciplines to look at assets more holistically, across all life stages (G&G, Planning, Drilling, Completions, & Operations) 2) More and better integration of multiple data sources 3) Visual analytics use company wide (a culture of analytics) 4) Increased reliance on data quality in decision making 24
Current Trends cont d 5) Automation of repeatable tasks 6) Stronger reliance on technology & vendors with domain expertise to expedite process improvements & efficiencies 7) Emphasis on best practices (e.g. asset reviews, type-curves, uncertainty management) 8) Vendors working together to deliver better solutions for their clients 25
FUTURE What could/should it look like & what challenges do we face? 26
Expectations Analytics Hype vs Proven Benefits Start with proven technology Visual Data Discovery Time 27
Analytics Adoption Rate by Industry 2017 we believe the next 5 years to be the first tangible commercialization period for Big Data & Advanced Analytics in the Oil & Gas Industry Darcy Partners, Perspectives on DATA & ADVANCED ANALYTICS IN THE OIL & GAS INDUSTRY, 2015 28
Digital Journey by Industry Several major disruptions have occurred. Impact of Digitization Disruptive moves (by pure online players, for example) have affected these industries, but the final outcome is still to be determined. Effect of digitization still unknown, and disruptive changes remain to be seen; these industries have a similar level of digitization ENERGY Extremely limited use of digital, primarily in internal operations. 29 2015 Point on Digitization Journey
Upstream O&G Challenges to Analytics Adoption 1) The O&G Industry has a long way to go (see previous 2 slides) 2) Investing in innovation while in a cost reduction mode I know I can save money if I invest in technology but I don t have any money to spend 3) Change Management: Technology is not the obstacle, it s People, Processes and quality Data 30
Future Trends 1) Advanced Analytics Automation, notifications, predictive analytics, AI / Machine Learning Will help us to understand, focus on what counts & improve the dialogue across disciplines Will move activities up the value chain, it won t replace people 2) Consortiums / data sharing / joint studies Operators sharing data to leverage processing capabilities and insights of advanced analytics 3) Continued focus of advanced analytics on G&G modelling, drilling and completions with slow adoption across operations 31
Conclusions 32
Conclusions 1) The industry has transformed how it produces, increasing their response to supply demands, which could limit price recovery. 2) Lower prices for longer and growth without hiring are the new normal making data and technology key to market survival and success. 3) The industry requires a major shift in its approach towards, & investment in, technology and will rely more on forward thinking vendors with domain expertise to take full advantage of analytics opportunities. 33
Thank You Bertrand Groulx President, Verdazo Analytics 403-561-6786 bertrand@verdazo.com Check out our blog 34