Petrophysics @ Apache

1. Petrophysics @ Apache

2. Petrophysics @ Apache E&P Technology Mission Promote the application of technology to maximize asset values, provide technical and records support for Apache operations and staff; seek, evaluate and recommend emerging technologies and processes appropriate to Apache’s operations; and evaluate and provide technical training for Apache personnel. Petrophysics Definition Petrophysics is the description of rock, pores, and fluids and the characterization of fluid flow through permeable media at economic rates in a changing commodity environment. Process Petrophysics integrates data sets from multiple sources, disciplines, and scales. Multiple methods are used to describe the same parameter to minimize uncertainty

3. Basic Laws Of Petrophysics • All reservoirs are hydrocarbon bearing until proven otherwise • Hydrocarbon is where you have already found it • Well logs are inherently non-unique • Rocks, logs, and production will tell you a story if only you are curious enough to ask • Net pay is a dynamic economic term dictated by commodity price and cost of finding • What we need to know about hydrocarbon reservoirs can take 20 years to get, but we need to know it now!

4. Work Flow Reservoir Integration Process Model (RIPM) After Newsham and Rushing (2001) Stage 1: Geologic and Geophysical Assessment Stage 1: Geologic Assessment The first stage focuses on descriptions of the geological framework, including interpretations of structural geology, depositional environment, and stratigraphy. Lithofacies, based on lithology, rock texture and sedimentary structure, are derived from core data, while vertical distributions of lithofacies are identified from well logs. Stratigraphy Regional Geology Structural Geology Core Description Depositional Process Depositional Environment Basin Morphology, Stress Regime Trap Definition, Closure Genetic Units Flow Regime Facies Distribution Depositional Sequence, Architecture Stage2: Petrographic and Petrophysical Rock Types The second stage identifies the rock and fluid systems on a pore-level scale using petrographic observations of pore structure, mineralogy, and diagenesis. Rocks are classified into units of rock deposited under similar conditions and diagenetic processes. Each rock type exhibits a unique porosity-permeability relationship, capillary pressure profile, and relative permeability characteristics. Stage 2: Petrophysical Evaluation Hydraulic Rock Types Facies Distribution Rocks Pores Fluids Porosity, Permeability, Pore Size Distribution Krgas, PVT, Capillary Sw, Compressibility Depositional Architecture Petrology, Mineralogy, Diagenesis, Porosity Classification Stage 3: Up-scaling Rock Types to Flow Units and Reservoir Compartments. The third or formation evaluation stage integrates the core data, well logs, rock types, and fluid properties to identify reservoir flow units, seals, and baffles controlling the physics of fluid flow in the reservoir. Flow units are identified from the relationship between rock flow and storage capacity. Stage 3: Formation Evaluation Reservoir Compartments Log Analysis Permeability Profiles Flow Units Lithology, Porosity, Fluid Models Stratified Lorenz, Storage and Flow Capacity Hydraulic Connectivity, LeverettJ(Sw), Pressure Porosity, Sw, Permeability, Pressure Correlation Methods Stage 4: Flow Characterization The fourth or reservoir modeling stage uses wellbore, reservoir, and geo-cellular reservoir models to test the description from the first three stages. The models typically included at this stage include pressure transient testing, material balance-type curve analysis of production data, conventional finite difference simulators, and geostatistic studies. Integrated stochastic and deterministic reservoir models are history matched to production to validate the description processes of the first three stages. Stage 4: Reservoir Modeling Wellbore Models Stochastic Models Deterministic Models Conventional Material Balance Production Performance Analysis Well 1 Well 2 Well 1 Well 2 Object-Based Sand Modeling Shale Final Conditions Initial Conditions Flow Simulation with History Matching Local Conditional Probability Distribution Pressure Transient Testing Grid-Based Probability Rock Property Modeling Variogram Matrix Response Line 100% Clay Point Clay Response Line g(h) h

5. Well Performance Analysis Reserves Core Studies Volumetric GIP (Static) Contacted GIP (Dynamic) Reservoir Simulation Logging Program Pilot Infill Drilling Program Well Surveillance & Monitoring Fluid Studies Reservoir characterization integrates data sets from multiple sources, disciplines, and scales. Multiple methods are used to describe the same parameter to minimize uncertainty. Work Flow To Describe Hydrocarbon Systems

6. Reservoir Storage Capacity Reservoir Flow Capacity Hydrocarbon-In-Place - ( 1 S ) w = GIP 43560 A H F · · · · B gi Expected Ultimate Recovery Hydrocarbon Porosity Volume Effective Permeability Thickness Expected Ultimate Recovery Expected Ultimate Recovery Hydrocarbon Porosity Volume Effective Permeability Thickness Criteria For Net Pay? Fundamentals Traditional methods attempt to correlate storage capacity to EUR with variable success Advanced analysis method correlates flow capacity to EUR

7. - ( 1 S ) w = GIP 43560 A H F · · · · B gi Storage vs. Flow Capacity Storage Capacity Hydrocarbon-In-Place Hydrocarbon Porosity Volume Application of core-log effective permeability model Flow Capacity I.P or Expected Ultimate Recovery EUR (BCF) Effective Permeability Thickness

8. Example of Integrated Research At Apache:Fluid PVT Sourced From Rocks, Pores and Fluid Distribution Observations

9. Can Water Saturation < 5%? The Sub-capillary Equilibrium Problem How do you drive water saturation below capillary equilibrium thresholds?

10. Direct Extraction of Water Saturation From Core Core-Based Measurements of Archie Water Saturation Parameters Core-Based Tests of Capillary Pressure – Water Saturation Distribution Formation Resistivity Factor MICP Capillary Pressure In-Situ Water Saturation Estimates m Invaded Zone Non-Invaded Zone n Dean Stark Analysis Extracted Water Volumes Resistivity Index Leverett J(Sw) Petrophysics Sources of Water Saturation

11. Capillary-based water saturation (magenta) log-based water saturation (dark blue) In the Qasr Field, observations of an ultra low water saturation have been made, yielding initial water saturation as low as 3-5%. The Lower Safa permeability ranges from 10 – 1000 mD. Hypothesis: Could the process that desiccates the rock be related to the catalyst effect of the CO2 (9% by volume) in the hydrocarbon volume? Water Vaporization/Condensation Phenomenon

12. Water Vaporization/Condensation Workflow Ppr g Tpr Ppr = P/Ppc Tpr = T/Tpc Z-factor correlations developed in terms of pseudoreduced pressure (Ppr) and pseudoreduced temperature (Tpr) Pseudoreduced pressure and pseudoreduced require pseudocritical pressure (Ppc) and pseudocritical temperature (Tpc) Ppc, Tpc Gas Composition Known Gas Composition Unknown • Compute Ppc and Tpc using mixing rules: • Kay’s • Stewart, Voo, Burkhardt • Correct Ppc and Tpc for CO2 and H2S using Weichert and Aziz correlation • Correct for N2 and water vapor • Compute Ppr and Tpr using z-factor correlations • Hall-Yarborough • Dranchule Abou-Kasem • Compute Ppc and Tpc using correations. Most common correlations developed in terms of gas gravity, e.g. Sutton’s • Correct Ppc and Tpc for CO2 and H2S using Weichert and Aziz correlation • Correct for N2 and water vapor • Compute Ppr and Tpr using z-factor correlations • Hall-Yarborough • Dranchule Abou-Kasem Three year Apache sponsored research program at U of Calgary to examine the effects of non-hydrocarbon components at HPHT on gas compressibility and water vaporization.

13. Example of Integrated Discipline Solutions From Rocks, Pores and Fluids to Reservoir Simulation

14. Petrophysics, RTA, and Simulation Advantages of Using Physical Model-based Methods • The goal is to better predict future production performance and optimize field development • Provide early assessment of contacted gas volume, drainage area, and EUR • Provide early assessment of well spacing and placement • Provide benchmarking for well completions effectiveness • Provide input into economic merit of completing (fracturing) specific zones Beyond Decline Curves “The Aries Alternative” Gas Flow Profile Match to Calibrate Net Pay Threshold Criteria Log-based Intrinsic Storage Reservoir Properties Transient Properties from Rate Transient Analysis Numerical Reservoir Simulation History Match

15. Gas Flow Prediction From Core-Log Model (black) Actual Gas In-Flow from Production Log (discrete red) Core-log model effective permeability is integrated from net pay intervals only. Layer storage properties are derived from the calibrated core-log model results. Net Pay Calibration Using Production Logs

16. Use of RTA to validate Core-Log Flow Properties Layer properties sourced from core-log model based intrinsic reservoir properties after calibration from production log surveys Rate Transient Analysis provides transient properties; fracture dimensions and effective permeability. Core-log model effective permeability values are used to select the appropriate Xf/Re ratio within RTA. Put storage and transient properties together into a numerical reservoir simulation to forecast rate and EUR Numerical Reservoir Simulator

17. Use of RTA to validate Core-Log Flow Properties Log-based intrinsic reservoir properties Fracture dimensions from Rate Transient Analysis

18. Use of Simulation to Estimate IP, EUR, Well Spacing • Early assessment of well spacing and placement • Benchmarking for well completions effectiveness • Input into economic merit of completing (fracturing) specific zones Integrated approach provides: • Future production performance and optimize field development • Early assessment of contacted gas volume, drainage area, and EUR