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Society of Petroleum Engineers Distinguished Lecturer Program www.spe.org/dl Integrated Reservoir Modelling for Carbonates Quo Vadis?

Dr. Jürgen Grötsch Shell Global Solutions International B.V.

Society of Petroleum Engineers Distinguished Lecturer Program www.spe.org/dl 2 Outline

• Integrated Reservoir Modelling (IRM) in Carbonates • Carbonate versus clastic reservoirs • Past - A brief history of IRM in Carbonates – 1990’s – Example: Malampaya Buildup – 2000’s – Example: Jurassic Arab Formation – 2010’s – Example: North Sea Chalk • Present – Current challenges • Future – Where are we going?

Grötsch, 2016 3 Why Do We Build Reservoir Models?

• To facilitate exploration, development and reservoir management decisions: – Support of exploration and appraisal activities – Field development planning – Field development – additional phases – Volumes in-place and Reserves reporting – Uncertainty estimation and management – Well Planning and Operations support – Equity determinations (re-determinations) – Farm in opportunities – Joint venture or governance obligations – Visualisation

Grötsch, 2016 4 Integrated Reservoir Modelling

• What is Integrated Reservoir Modelling? – Structural Model – Facies Model – Property Model – Fluid Model – Flow Model

• What else do we need from IRM?

Grötsch, 2016 5 IRM – Input Data

Field Analogue Survey Outcrop Analogue Studies Core Measurements Seismic Interpretation

? Natih E Channel Cut/Fill

Field Performance Review Integrated Core Review Field Correlation

Ekulama F1000 Production History 20000 900 Oil Rate bbl/d

18000 BHP psia 800 Water Cut % 16000 GOR scf/bbl 700

14000 600

12000 500

10000

400 8000

300 GOR scf/bbl, Watercut % Watercut scf/bbl, GOR Oil Rate bbls/d, BHP psia BHP bbls/d, RateOil 6000

200 4000

2000 100

0 0

Well Review Time Recovery Mechanism Conceptual Geological Model

Sor og 15?% Current state Vertical Equilibrium Sor wog 15?% WI Gascap High Sweep? Rim volume Y mil bbl

ROS WF 30 -50%

WOGD and viscous (fracflow) Sor wo 25 -30%

Current RF 35%, Ult. RF 45%?

Grötsch, 2016 6 Carbonate Reservoirs

• What controls reservoir • Modelling workflow architecture? commonly includes: – Depositional facies – Discrimination of depositional and diagenetic controls – Diagenetic overprint(s) – Pore typing and rock typing – Fracturing to model permeability and saturation THE RESERVOIR Well A Well B – No simple N/G cut-off criteria – Fracture models (Dual porosity: Dual permeability)

Grötsch, 2016 7 Porosity-Permeability Relationships

• Clastic Reservoirs – Porosity-permeability relationships are usually consistent in a reservoir (mostly intergranular pores)

• Carbonate Reservoirs – Complex pore systems: Often more than one porosity-permeability relationship – ‘Mega-fabrics’ (fractures and karst) are poorly characterized from core data – Correlations between core-based and well-test-derived permeability are complicated – Permeability heterogeneity is complex , varies between scales – Permeability upscaling and averaging can be important

Grötsch, 2016 8 Bi- and Multi-Modal Pore Networks

• Clastic Reservoirs • Carbonate Reservoirs – Unimodal pore systems are most common – Bi- and multi-modal pore – Correlation between storage (oil column) networks are common in and productivity is present. carbonates – Oil transition zones are usually short – Big differences in production behaviour between the pore systems that provide storage (volumetrics) and the pore systems that provide productivity – Microporous reservoirs have long transition zones

Grötsch, 2016 9 Fracturing Influences Flow Behaviour

• Clastic Reservoirs • Carbonate Reservoirs – Fractured reservoirs are – Most reservoirs are fractured. Intensity uncommon and character widely varies. (exception: tight gas) – Tiny pore volume has potential for Darcy – Faults commonly act as seals: permeability. clay smear, cataclasis and – Fractures can dominate productivity and cementation effects. Fault form high permeability pathways through compartments are common. the reservoir: Water and gas breakthrough. – Faults and fractures create permeability LS4

LS3 anisotropy.

LS2

LS1 – Faults are more often associated with fractures and less often act as seals.

Grötsch, 2016 10 Past: A brief history of IRM – 1990’s

• Advent of 3D graphics computing • Focus on tools – everybody made his own – Subsurface disciplines (GPs, GGs, PPs, REs, PTs) – Tool proliferation, limited integration

• Focus on reducing uncertainty – Linking reservoir parameters – 3D seismic Close-the-Loop – industry first

• Example: Malampaya, Philippines (appraisal & development)

Grötsch, 2016 11 Example: Malampaya, Philippines

• Conceptual geological model Seismic constrained reservoir modelling • 3D Seismic constrained reservoir models • Multiple realisations • Rock type based • 3D Seismic Close-the-Loop

Real vs. synthetic seismic Ref.: Grötsch & Mercadier, 1999: AAPG Bulletin Grötsch, 2016 12 Example: Malampaya, Philippines

• Velocity = f (POR, Rock type) • 3D Time/Depth conversion • Reduce Uncertainty

RRT-1 RRT-2 RRT-3 RRT-4 RRT-5

Pessimistic Most Likely Optimistic Ref.: Grötsch & Mercadier, 1999: AAPG Bulletin Grötsch, 2016 13 Past: A brief history of IRM – 2000’s

• Hardware gets more powerful – bigger models, more detail or area • Focus on adding functionality – Integration via using common 3D visualisation tools – Geostatistics – how can it help? – Carbonates require rock typing – how can we model this?

• Example: Arab Formation, UAE (brown field)

Grötsch, 2016 14 Example: Arab Formation, UAE

• From conceptual geological

models ..… Depositional facies distribution

Ref.: Grötsch et al, 2003, Geoarabia Grötsch, 2016 15 Example: Arab Formation, UAE

… to regional 3D reservoir models:

Static full-field model Dynamic full-field model

Facies Year 2

• Complex architecture Porosity Year 7 • Complex fluids

• Rock type Perm Year 17

based model Pressure • Dynamic simulation Rock Type Year 40

Ref.: Grötsch et al, 2003, Geoarabia Grötsch, 2016 16 Past: A brief history of IRM – 2010’s

• Major steps forward in technology • Tools get more complex and cumbersome

– Advent of “Frankenstein” models – one model fits all – Anchoring on best guess models – Modelling for comfort rather than analytical rigor – Carbonates require “grain scale” models (i.e. pore networks) – Unconventionals cannot be handled • Conclusion: IRM did not address root cause challenges • Example: North Sea Chalk (unconventionals, subtle traps)

Grötsch, 2016 17 Example: Unconventional Carbonates

• Emmons (1921): Not all hydrocarbons are in anticlinal structures … • Paradigm shift: In last ten years proven by production: IRM rules do not apply. Thick source rock potential shale gas opportunity

Modified after Schenk & Pollastro, 2001

• “Unconventionals” are not new: Not followed up – until recently – Example: “Tiroler Steinöl” in Austria: Triassic Seefeld Fm., Achensee National Park, carbonates mined >100 years – Example: North Sea Chalk: Discovered after many years of conventional development Grötsch, 2016 18 Example: North Sea Chalk, Denmark

• HC accumulations in Chalk 1 • Originally: 4-Way closures only... • Study 1999: Halfdan discovery – no closure Area • HC distribution in low K Carbonates: Poorly understood 2 A 3 A B

B

Ref.: S. Back, H. van Gent, L. Reuning, J. Grötsch, J. Niederau, P. Kukla (2011)

Ref.: Fabricius et al., 2007 Grötsch, 2016 19 Example: North Sea Chalk, Denmark

Mass-transport Complex Northern Valley Channel

3 2

Bo-Jens Ridge

Halfdan: Mound 1 linked to slumping

Iso-surface 2: Chaos attribute

0 0.5 1.0 1.5 2.0 2.5 km

Ref.: S. Back, H. van Gent, L. Reuning, J. Grötsch, J. Niederau, P. Kukla (2011) Grötsch, 2016 20 IRM – Where are we now?

• Base case assumption persists: We build on it with ever increasing detail • Narrow range of production forecasts • Model does not address key development decisions: Ill-defined decision criteria • Perception of realism from model complexity

Single Make subsurface Complex linear Base case with Narrow range investment concept workflow perturbations Dynamic of forecasts decision STOIIP based Uncertainty only $

Grötsch, 2016 21 Present – Current Challenges

• Personal biases: Geological concepts & RE multipliers • Making the right models: Scaling • Uncertainty management: Parameterization, end-to-end • Linear versus iterative workflows: Enabler for integration • Technical data management: Manage models, audit trails

• (T)ECOP: Neglecting more important value drivers and risks – Non-technical risks (Economic, Commercial, Operational, Political) – Access to reserves – Short-term gains versus long-term success Grötsch, 2016 22 The Challenges of the Future

• Carbonate technology development IRM building blocks – Model scaling – Unconventional & subtle traps Scaled, – Grain scale & pore network modelling Integrated – End-to-end Uncertainty handling and management Workflows

• Process development Decision – Focus on business decisions Driven – End-to-end integration Modelling Strategy – Scenario management

• Collaboration platform Iterative – Decision Framework Tool (DFT) Model Testing – Decision Framework Model (DFM) – Technical Data Management (TDM)

Grötsch, 2016 24 Unconventionals & Subtle Traps

Eocene carbonate slope, Browse Basin, NWS, Australia

• Carbonate Slope Geometries

Map view 3D view (x5 vertical)

• Reservoir property Cross section along channel axis Cross Section proxy from seismic

Ref.: Reuning, L., Back, S., Schulz, H., Hirsch, M., Kukla, P., Grötsch, J. (2009)

Grötsch, 2016 25 Grain Scale & Pore Networks

Reservoir Rock Typing Pore Network Modelling

Ref.: Knackstedt et al, 2010

Ref.: Grötsch et al., 1998 Grötsch, 2016 26 End-to-end Uncertainty Handling

Experimental design and beyond

Single Step

P10

Time P50 Cum Oil Cum

P90

Create HM proxies Create Forecast proxies

Range of cases with acceptable history match Range of forecasts constrained by history match

Grötsch, 2016 27 Fast Iterations – An Enabler

Linear Single Long linear Base case with Small solution space Geological workflow perturbations Too much precision Concept • Long-winded • Narrow uncertainty STOIIP based H - Continuous range M • Over confidence in L base case Iterative Multiple Geological Concept - Categorical • Short iterations Short H - Continuous • Representative iterations in M workflow uncertainty range L • Robust decision evaluation Realistic solution space • Faster and shorter iterations • Develop better understanding around key uncertainties • Make more robust decisions

Grötsch, 2016 28 Scenario Management

Capture Uncertainties Evaluate Options Focus on Value

Decision Framework Model

Subsurface Development Development Realisations + Concepts = Scenarios

Grötsch, 2016 29 Must Have

Decide

Modelling Tools Decision & Framework Feedback Loops Scenario Plan Management Model S = DC + R

Content & Context Management

Manage Data Grötsch, 2016 30 Optimization & Focus on Value

The end in mind …

Surface

Subsurface

… still a long way to go

Grötsch, 2016 31 Improving IRM– Increasing Efficiency

From

DGx OFW MFE ITR Thinking whilst model building – complex single model realization

More Efficient Improved Modeling & Understanding Uncertainty Analysis More Time For & Evaluation Planning To DGx

OFW MFE ITR Time Saving

Thinking Model Building & Uncertainty Evaluation

Grötsch, 2016 32 IRM – The Three Pillars

People Process Tools

Decision Decision Makers Opportunity Framework Realisation Standard Front-end Content and Manager Decision Context Quality

Content Modelling Experts tools

Key challenge: Fast iterative feedback loops

Grötsch, 2016 33 Conclusions

• IRM is more than building models - Linking People, Processes & Tools

• IRM: Tremendous progress in last 25 years - key challenges ahead

• The Future of Integrated Reservoir Modelling: – New technologies – Decisions based IRM – Focus on model requirements & scales – Need for end-to-end integration – Need for scenario management – From linear workflows to iterative loops

Grötsch, 2016 34 Acknowledgements

• Shell Global Solutions International B.V.

• Shell Learning & Development

• My colleagues in industry and academia: - Hans Goeyenbier - Paul Wagner - John Brint - Henk-Jaap Kloosterman - Tim Woodhead - Christoph Ramshorn - and many more …..

Grötsch, 2016 35 Q&A

36 Definitions & Cautionary Note

Reserves: Our use of the term “reserves” in this presentation means SEC proved oil and gas reserves. Resources: Our use of the term “resources” in this presentation includes quantities of oil and gas not yet classified as SEC proved oil and gas reserves. Resources are consistent with the Society of Petroleum Engineers 2P and 2C definitions. Organic: Our use of the term Organic includes SEC proved oil and gas reserves excluding changes resulting from acquisitions, divestments and year-average pricing impact. Resources plays: Our use of the term ‘resources plays’ refers to tight, shale and coal bed methane oil and gas acreage. The companies in which Royal Dutch Shell plc directly and indirectly owns investments are separate entities. In this presentation “Shell”, “Shell group” and “Royal Dutch Shell” are sometimes used for convenience where references are made to Royal Dutch Shell plc and its subsidiaries in general. Likewise, the words “we”, “us” and “our” are also used to refer to subsidiaries in general or to those who work for them. These expressions are also used where no useful purpose is served by identifying the particular company or companies. ‘‘Subsidiaries’’, “Shell subsidiaries” and “Shell companies” as used in this presentation refer to companies in which Royal Dutch Shell either directly or indirectly has control. Companies over which Shell has joint control are generally referred to as “joint ventures” and companies over which Shell has significant influence but neither control nor joint control are referred to as “associates”. The term “Shell interest” is used for convenience to indicate the direct and/or indirect ownership interest held by Shell in a venture, partnership or company, after exclusion of all third-party interest. This presentation contains forward-looking statements concerning the financial condition, results of operations and businesses of Royal Dutch Shell. All statements other than statements of historical fact are, or may be deemed to be, forward-looking statements. Forward-looking statements are statements of future expectations that are based on management’s current expectations and assumptions and involve known and unknown risks and uncertainties that could cause actual results, performance or events to differ materially from those expressed or implied in these statements. Forward-looking statements include, among other things, statements concerning the potential exposure of Royal Dutch Shell to market risks and statements expressing management’s expectations, beliefs, estimates, forecasts, projections and assumptions. These forward-looking statements are identified by their use of terms and phrases such as ‘‘anticipate’’, ‘‘believe’’, ‘‘could’’, ‘‘estimate’’, ‘‘expect’’, ‘‘intend’’, ‘‘may’’, ‘‘plan’’, ‘‘objectives’’, ‘‘outlook’’, ‘‘probably’’, ‘‘project’’, ‘‘will’’, ‘‘seek’’, ‘‘target’’, ‘‘risks’’, ‘‘goals’’, ‘‘should’’ and similar terms and phrases. There are a number of factors that could affect the future operations of Royal Dutch Shell and could cause those results to differ materially from those expressed in the forward-looking statements included in this presentation, including (without limitation): (a) price fluctuations in crude oil and natural gas; (b) changes in demand for Shell’s products; (c) currency fluctuations; (d) drilling and production results; (e) reserves estimates; (f) loss of market share and industry competition; (g) environmental and physical risks; (h) risks associated with the identification of suitable potential acquisition properties and targets, and successful negotiation and completion of such transactions; (i) the risk of doing business in developing countries and countries subject to international sanctions; (j) legislative, fiscal and regulatory developments including potential litigation and regulatory measures as a result of climate changes; (k) economic and financial market conditions in various countries and regions; (l) political risks, including the risks of expropriation and renegotiation of the terms of contracts with governmental entities, delays or advancements in the approval of projects and delays in the reimbursement for shared costs; and (m) changes in trading conditions. All forward-looking statements contained in this presentation are expressly qualified in their entirety by the cautionary statements contained or referred to in this section. Readers should not place undue reliance on forward-looking statements. Additional factors that may affect future results are contained in Royal Dutch Shell’s 20-F for the year ended 31 December, 2014 (available at www.shell.com/investor and www.sec.gov ). These factors also should be considered by the reader. Each forward-looking statement speaks only as of the date of this presentation, 19 August, 2015. Neither Royal Dutch Shell nor any of its subsidiaries undertake any obligation to publicly update or revise any forward-looking statement as a result of new information, future events or other information. In light of these risks, results could differ materially from those stated, implied or inferred from the forward-looking statements contained in this presentation. There can be no assurance that dividend payments will match or exceed those set out in this presentation in the future, or that they will be made at all. We use certain terms in this presentation, such as discovery potential, that the United States Securities and Exchange Commission (SEC) guidelines strictly prohibit us from including in filings with the SEC. U.S. Investors are urged to consider closely the disclosure in our Form 20-F, File No 1-32575, available on the SEC website www.sec.gov. You can also obtain this form from the SEC by calling 1-800-SEC-0330. 37 Your Feedback is Important

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