THE IMPACT OF DIGITALIZATION OF SCAL ON FIELD DEVELOPMENT Presented - PowerPoint PPT Presentation

THE IMPACT OF DIGITALIZATION OF SCAL ON FIELD DEVELOPMENT Presented at the National IOR Conference Stavanger, Norway 2018-04-23 Lesley A. James, Christopher D. Langdon, Maziyar Mahmoodi, Daniel J. Sivira www.mun.ca

Acknow ledgements • National IOR Centre • University of Stavanger • The support I receive in Canada • My co-authors 2

Agenda • The Digital Revolution • Conventional Core Analysis • Digital Rock Physics • Digitalization of SCAL & EOR/IOR Screening 3

DIGITALIZATION - Digital revolution - Business Process Engineering - DIgitalization 4

The Digital Revolution 5

The Six Stages of Digital Transformation 6

CONVENTIONAL CORE METHODS - Core Analysis - Specialized Core Analysis – SCAL - Enhanced & Improved Oil Recovery Screening 7

Schlumberger Services • Wellsite Services • Special Core Analysis – Catalog, Stabilize for shipment, Sidewall cores https://www.slb.com/services/characterization/reservoir/core_pvt_lab/ – Electrical Measurement (Archie Exponents) rock_laboratory_services/core_analysis_conventional_resources.aspx • Routine Core Analysis – Nuclear Magnetic Resonance Multiphase – Porosity, Saturation, Permeability – Capillary Pressure – Core Gamma Logging • Mercury Injection – CT Scanning (heterogeneity) • Centrifuge – Photographs (White and UV Light) • Porous Plate • Fluid Analysis – Relative Permeability – Composition – Wettability – PVT • EOR • Petrology – Miscible-Gas & Chemical Flood Compositional – Viewing Rooms, X-Ray Diffraction Multiphase & – Core Flow & Sandpack – Thin Sections – Slim-tube & Rising Bubble – SEM – Multi Contact Miscibility • Formation Damage – IFT, Contact Angle, Viscosity – Perm after Mud Invasion – Chemical Combinations – Rock-Fluid Interaction – Optimal Salinity – Fluid-Fluid Interaction – Surfactant Adsorbtion 8 – Damage from T&P Change

SCAL Workflow • SCAL Program Design is very field specific and application specific – Beliveau (2007) details a SCAL Program for aggressive field development • Beliveau SCAL Program included: – Basic Rock and Fluid Properties • Oil viscosity • Porosity • Permeability • Rock Characterization (grain size, deposition) – Initial Water Saturation – Wettability – Relative Permeability – Capillary Pressure 9

SCAL Workflow • SCAL Program Design is very field specific and application specific – Gao, Kralik and Vo, 2010, outline a “State of the Art” SCAL Program Design • Large scale single study program – High accuracy measurements – Appropriate distribution across important static reservoir rock types 10

Timeline of an EOR Project DOES NOT INCLUDE: - Core Analysis - SCAL 11

Workflow ExxonMobil EOR Screening G. F. Teletzke, R. C. Wattenbarger and J. R. Wilkinson, "Enhanced Oil Recovery Pilot Testing Best Practices," in SPE International Petroleum Exhibition and Conference , Aby Dhabi, 2010. 12

EOR Screening Workflow • Smart EOR Screening: Breaching the Gap between Analytical and Numerical Evaluations 13

Conventional EOR Workflow Conventional EOR Screening 1-4 years R. Al-Mjeni, S. Arora, P. Cherukupalli, J. van Wunnik, J. Edwards, B. J. Felber, O. Gurpinar, G. J. Hirasaki, C. A. Miller, C. Jackson, M. R. 14 Kristensen, F. Lim and R. Ramamoorthy, "Has the Time Come for EOR," Oilfield Review, vol. 22, no. 4, 2011.

DIGITAL ROCK PHYSICS - Workflows - Core Analysis 15

Uses of Digital Rocks • Petrophysical Properties’ Correlations • Fluid Flow Properties and Calculations (pore network modelling) • Quality Control of Convectional Experimental and Indirect Measurements • Wettability and EOR Analysis • Formation Damage Studies • Testing of Brines and Surfactants 16

Digital Rock Physics (DRP) • All analyses undertaken on a single sample • Reduction in coring cost because of the sample flexibility • A digital rock can be obtained from sidewall cores, cuttings, damaged, unconsolidated, contaminated, heterogeneous, and trim ends • Faster answers to reduce risk • Pore-scale understanding of reservoir behaviour • Insight and properties upscaled to core plug and whole core sections • Improve reserves estimations 17

Digital Rock Physics (DRP) Definition: • A new approach in SCAL field is digital rock physics. • CT-scan platforms can develop a 3D digital X-ray micro-tomographic images. Size and Resolution Range : Schematic diagram lab-based micro-CT setup [1] • Wide and dependent [2]. Sample Size Resolution Core 11 - 16.5 cm 400 - 500 µm Core plug 2 - 4 cm 12 - 19 µm 0.1 – 0.5 cm 0.3 - 5 µm Micro plug 50 – 300 µm 0.3 – 5 nm 18 CT axial scans of core [PERM Lab, Canada]

Digital Rock Physics (DRP) Pore Scale Core Scale - Pore network modeling - Direct pore modeling Measured Parameters: Petrophysical Properties • Total porosity • Absolute permeability • Density distributions of fluid/rock phases • Rock minerology Multiphase Fluid Flow • Capillary pressure • Relative permeability • Resistivity Index Different scale of core CT scans [PERM Lab, Canada] 19

Digital Rock Physics Workflow 3D Visualisation & Description of 3D pore structure Sample Preparation DYNAMIC: Multiphase flow and Imaging in 3D. displacement. Estimation of Reconstruction OOIP & residual saturation. Image in 2D/3D (Multiple States) STATIC Image quality control, Calculation of registration and mineral physical properties: identification in 3D. Integration of ɸ, k h , k v , m,n, Acoustic, NMR other imaging techniques 20 https://www.fei.com/videos/webinar-Bringing-Core-Analysis-into-the-Digital-Age/

Properties from Digital Rocks Solid Matrix Pore Space Pore Network Stress - Strain Pc Formation Factor NMR relaxation Relative Permeability Vp & Vs Permeability Andrä, H., et al. (2013) Lopez, O., et al. (2012) 21 https://www.fei.com/videos/webinar-Bringing-Core-Analysis-into-the-Digital-Age/

Properties from Digital Rocks 3D Digital Rock Digital Rock Properties Qualitative Fluid Flow Petrophysical 4D Imaging • Capillary pressure • Oil in Place • Porosity • Relative permeability • Enhanced Oil Recovery permeability • Absolute permeability • Resistivity index • Formation damage • Formation resistivity factor • Saturation exponent “n” • Fluid sensitivity • Cementation exponent “m” • Wettability analysis • Unconventional reservoirs • Elastic moduli • S w sensitivity • Geochemical reactivity • Acoustic velocities • Interfacial sensitivity • Wettability mapping • NMR relaxation times • Rate sensitivity • Mercury injection 22 https://www.fei.com/videos/webinar-Bringing-Core-Analysis-into-the-Digital-Age/

Upscaling from Digital Rocks Hibernia Field 20 New York Krones City Coins Size Comparison 23

Roles & Tasks Workflow: : A multidisciplinary process: • High-resolution images (step 1-2) of rock are typically obtained in 1-24 hours depending on spatial and time resolutions [4,5]. Roles include: • Petrophysicists • Lab technicians • Imaging experts • Computer scientists Typical workflow of performing DRP in SCAL [4]. • Reservoir engineers 24

Digital Rock Physics Summary • Based on core or sub-core samples – Is it representative of the field? • Formation properties are: – Directly measured/calculated: volumes, porosity, saturations – Correlated from measurements and conventional correlations: permeability, resistivity, capillary pressure, relative permeabilities • Pore network modelling: – Pore scale material balances based direct and Lattice Boltzman Models – Can consider reactive transport, adsorption/dissolution – Intermolecular forces – Computationally intensive – Scaling is a challenge 25

DIGITALIZATION of SCAL & SCREENING - Challenges - Possibilities? 26

Artificial Intelligence in EOR • Data Mining is used to extract important parameters in successful EOR fields • Large volume of data (365 successful EOR projects) required to train and validate model • Machine Learning algorithms are used to draw screening rules and interpret relationship between input and output https://www.capgemini.com/2016/05/machine-learning-has-transformed-many-aspects-of-our-everyday-life/ • 80% of the data-set selected at random for the training and the G. Ramos and L. Akanji, “Technical Screening of Enhanced Oil Recovery Methods – A Case remaining 20% used as the validation Study of Block C in Offshore Angolan Oilfields," in EAGE Workshop on Petroleum or prediction set Exploration, Luanda, Angola, 2017. V. Alvarado, A. Ranson, K. Hernandez, E. Manrique, J. Matheus, T. Liscano and N. Prosperi, “Selection of EOR/IOR Opportunities Based on Machine Learning,” in SPE 13 th European 27 Petroleum Conference, Aberdeen, 2002.

Artificial Intelligence • Five layered feed forward – backpropagation neural network • Input Layer – Input variables • Hidden Layers – Input/Output membership functions – Fuzzy logic AND/OR rules • Output Layer – Defuzzification – Resulting output is decision signal 28 A typical 5 layer neuro-fuzzy framework (Ramos, 2017)