RhoVeTM. (U.S. patent pending - copyright 2016) A New Empirical Pore Pressure Transform

Similar documents
Th SBT1 14 Seismic Characters of Pore Pressure Due to Smectite-to-illite Transition

Pore Pressure Estimation A Drillers Point of View and Application to Basin Models*

BPM37 Linking Basin Modeling with Seismic Attributes through Rock Physics

Pressure Regimes in Deep Water Areas: Cost and Exploration Significance Richard Swarbrick and Colleagues Ikon GeoPressure, Durham, England

Economic Geology Unconventional Energy Research

SPE DISTINGUISHED LECTURER SERIES is funded principally through a grant of the SPE FOUNDATION

Rock Physics of Shales and Source Rocks. Gary Mavko Professor of Geophysics Director, Stanford Rock Physics Project

Pore Types Across Thermal Maturity: Eagle-Ford Formation, South Texas*

Pressure Prediction and Hazard Avoidance through Improved Seismic Imaging

Dynamic GeoScience Martyn Millwood Hargrave Chief Executive OPTIMISE SUCCESS THROUGH SCIENCE

SPE These in turn can be used to estimate mechanical properties.

Seismic Driven Pore Pressure Prediction

Quartz Cementation in Mudrocks: How Common Is It?

OTC We attribute the high values of density porosity above the oil- Copyright 2001, Offshore Technology Conference

Downloaded 11/20/12 to Redistribution subject to SEG license or copyright; see Terms of Use at

So I have a Seismic Image, But what is in that Image?

Predicting Gas Hydrates Using Prestack Seismic Data in Deepwater Gulf of Mexico (JIP Projects)

Determination of Pore Pressure Using Divergences

Pore Pressure Prediction and Distribution in Arthit Field, North Malay Basin, Gulf of Thailand

Prediction technique of formation pressure

Overpressure Characteristic in the Langkat Field, North Sumatra Basin, Indonesia

Overpressure detection using shear-wave velocity data: a case study from the Kimmeridge Clay Formation, UK Central North Sea

Osareni C. Ogiesoba 1. Search and Discovery Article #10601 (2014)** Posted May 31, 2014

Integrating rock physics and full elastic modeling for reservoir characterization Mosab Nasser and John B. Sinton*, Maersk Oil Houston Inc.

Using rock physics for constructing synthetic sonic logs

From loose grains to stiff rocks The rock-physics "life story" of a clastic sediment, and its significance in QI studies

Th D Interpolation and Extrapolation of Sparse Well Data Using Rock Physics Principles - Applications to Anisotropic VMB

Reservoir Rock Properties COPYRIGHT. Sources and Seals Porosity and Permeability. This section will cover the following learning objectives:

Pore Pressure Predictions in the Challenging Supra / Sub-Salt Exploration Plays in Deep Water, Gulf of Mexico.

Technology of Production from Shale

Rock Physics of Organic Shale and Its Implication

The consequences of ignoring rock properties when predicting pore pressure from seismic and sonic velocity

Ingrain Laboratories INTEGRATED ROCK ANALYSIS FOR THE OIL AND GAS INDUSTRY

LITTLE ABOUT BASIC PETROPHYSICS

Optimizing Drilling Performance by Wellbore Stability and Pore-Pressure Evaluation in Deepwater Exploration T. Klimentos, Schlumberger

Distribution of Overpressure and its Prediction in Saurashtra Dahanu Block, Western Offshore Basin, India*

Reservoir properties inversion from AVO attributes

Estimation of Pore Pressure from Well logs: A theoretical analysis and Case Study from an Offshore Basin, North Sea

Competing Effect of Pore Fluid and Texture -- Case Study

Petrophysical Rock Typing: Enhanced Permeability Prediction and Reservoir Descriptions*

Mechanical Properties Log Processing and Calibration. R.D. Barree

Per Avseth (Dig Science) and Tapan Mukerji (Stanford University)

Earth models for early exploration stages

Two-step wireline log analysis of overpressure in the Bekapai Field, Lower Kutai Basin, Indonesia

Process, Zeit Bay Fields - Gulf of Suez, Egypt*

A new model for pore pressure prediction Fuyong Yan* and De-hua Han, Rock Physics Lab, University of Houston Keyin Ren, Nanhai West Corporation, CNOOC

and a contribution from Offshore Europe

The elastic properties such as velocity, density, impedance,

Realtime Geopressure and Wellbore Stability Monitoring while Drilling. Eamonn Doyle VP Real-time Operations

Integrated Reservoir Characterisation - a successful interdisciplinary working model

Pressure and Compaction in the Rock Physics Space. Jack Dvorkin

Core Technology for Evaluating the Bakken

Variety of Cementation Factor between Dolomite and Quartzite Reservoir

Quantifying Bypassed Pay Through 4-D Post-Stack Inversion*

But these are what we really measure with logs..

QUANTITATIVE ANALYSIS OF SEISMIC RESPONSE TO TOTAL-ORGANIC-CONTENT AND THERMAL MATURITY IN SHALE GAS PLAYS

Rock physics and AVO analysis for lithofacies and pore fluid prediction in a North Sea oil field

Pore Pressure Prediction Using Offset Well Logs: Insight from Onshore Niger Delta, Nigeria

Search and Discovery Article #10532 (2013)** Posted October 21, Abstract

Shale Diagenesis and Permeability: Examples from the Barnett Shale and the Marcellus Formation*

NAPE 2011 Lagos, Nigeria 28 November-2 December 2011 Extended Abstract

Exploration / Appraisal of Shales. Petrophysics Technical Manager Unconventional Resources

Effects of VTI Anisotropy in Shale-Gas Reservoir Characterization

Role of Data Analysis in fixing parameters for petrophysics & rockphysics modeling for effective seismic reservoir characterization A case study

We apply a rock physics analysis to well log data from the North-East Gulf of Mexico

FORMATION EVALUATION OF SIRP FIELD USING WIRELINE LOGS IN WESTERN DEPOBELT OF NIGER DELTA

Petroleum Geoscience: From Sedimentary Environments to Rock Physics

2015 Training Course Offerings

Overview of Selected Shale Plays in New Mexico*

Module for: Resistivity Theory (adapted/modified from lectures in PETE 321 (Jensen/Ayers))

A NEW APPROACH TO PORE PRESSURE PREDICTIONS GENERATION, EXPULSION AND RETENTION TRIO: CASE HISTORIES FROM THE GULF OF MEXICO

Seismic characterization of Montney shale formation using Passey s approach

Extended Abstract for presentation at EAGE Meeting Paris 13/ History of Norwegian Petroleum Exploration and its impact on Norwegian Geosciences

Pore Pressure Prediction from Seismic Data using Neural Network

The Influence of Pore Pressure in Assessing Hydrocarbon Prospectivity: A Review

Shear Wave Velocity Estimation Utilizing Wireline Logs for a Carbonate Reservoir, South-West Iran

Summary. Simple model for kerogen maturity (Carcione, 2000)

Evaluation of Rock Properties from Logs Affected by Deep Invasion A Case Study

Maturity Modeling of Gomin and South Gomin fields Southern Pattani Basin, Gulf of Thailand

The map The ma (Somaliland ( Somaliland Somalia) SOMALIA SOMALILAND

Seismic Guided Drilling: Near Real Time 3D Updating of Subsurface Images and Pore Pressure Model

Detection and estimation of gas hydrates using rock physics and seismic inversion: Examples from the northern deepwater Gulf of Mexico

Acoustic Anisotropy Measurements and Interpretation in Deviated Wells

Rock Physics Modeling in Montney Tight Gas Play

Quantitative Seismic Interpretation An Earth Modeling Perspective

We LHR1 01 The Influence of Pore Pressure in Assessing Hydrocarbon Prospectivity - A Review

The Precision Of Normal Compaction Trend Delineation Is The Keystone Of Predicting Pore Pressure.

RC 1.3. SEG/Houston 2005 Annual Meeting 1307

Drillworks. DecisionSpace Geomechanics DATA SHEET

Ursula Hammes. Research Associate Bureau of Economic Geology The University of Texas at Austin

Formation Pore Pressure and Fracture Pressure Estimating from Well Log in One of the Southern Iranian Oil Field

LINK BETWEEN ATTENUATION AND VELOCITY DISPERSION

We Density/Porosity Versus Velocity of Overconsolidated Sands Derived from Experimental Compaction SUMMARY

Effect of diagenesis on pore pressures in fine-grained rocks in the Egersund Basin, Central North Sea

Property of interest Core data Most useful log data. TOC LECO or RockEval GR, density, resistivity. Mineralogy XRD, FTIR, XRF Most + ECS-style logs

egamls Inc. What we do: Well and field studies using GAMLS software (plus GAMLS licensing)

Constraining seismic rock-property logs in organic shale reservoirs

Geological Classification of Seismic-Inversion Data in the Doba Basin of Chad*

MINERALOGICAL ASSOCIATION OF CANADA CLAYS AND THE RESOURCE GEOLOGIST

Halliburton Engineering for Success in Developing Shale Assets

Transcription:

RhoVeTM Method (U.S. patent pending - copyright 2016) A New Empirical Pore Pressure Transform This presentation and all intellectual property discussed in this presentation are the property of GCS Solutions, Inc. and/or Matt Czerniak. GCS Solutions, Inc. Copyright 2017 GCS Solutions, Inc.

Copyright 2017 GCS Solutions, Inc. 2

Copyright 2017 GCS Solutions, Inc. RhoVe TM Method

RhoVe TM Auto Compositional Changes (executable) RhoVe TM T Thermodynamic Solutions (executable) Acoustic Impedance, Density, Sonic Copyright 2017 GCS Solutions, Inc.

RhoVeTM Method (U.S. patent pending - copyright 2016) JIP seeking $55,000 investment for: Commercial implementation of RhoVe method as a plug-in or web-based application to include: Real-Time WITSML connectivity, notebook (ipad) capability, 1D temperature modeling, Explore automation capabilities, Copyright 2017 GCS Solutions, Inc.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

RhoVeTM Method (U.S. patent pending - copyright 2016) Summary Interactive (and fast). Premised on a continuum of virtual, normally pressured synthetic rock property relationships. Pore pressure is calculated by directly applying RhoVe-derived Velocity & Density-Effective Stress trends. Subsalt Applications Two-parameter approach: a-term & alpha (α); includes the effects of compositional changes (clay diagenesis) Rationale for subdivision of major flow units, which can be utilized in layerbased basin modeling simulations. Copyright 2017 GCS Solutions, Inc.

RhoVE-S V-rho V-z rho-z P-z RhoVE-ε RhoVE-ε RhoVE-ε RhoVE-ε 1.0 0. RhoVE-S RhoVE-S RhoVE-S 0. 1.0 0. 1.0 0. 1.0 0. 1.0 0. 1.0 V-ES rho-es RhoVE-S RhoVE-S RhoVE-ε RhoVE-ε

RhoVE-S a V-rho RhoVE-ε Two Parameter: RhoVE-ε 1.0 0. α RhoVE-S V-z a : fractional distance α : calculated property a, α 0. 1.0 0.37

V-rho V-z rho-z P-z 1.0 0. ESnorm 0. 1.0 0. 1.0 0. 1.0 0. 1.0 0. 1.0 V-ES rho-es ESnorm ESnorm

V-rho V-z rho-z P-z 1.0 RhoVe TM Method 0. ESnorm 0. 1.0 0. 1.0 0. 1.0 0. 1.0 0. 1.0 V-ES rho-es ESnorm ESnorm

Examples a : fractional distance 1.08 0.99 0.75 0.56 0.0 RhoVe-S

1.08 0.99 0.75 0.56 0.0 DTCO Sonic 0.3 Rhob Density

0.75 DTCO Sonic 0.3 Rhob Density

0.75 DTCO Sonic 0.4 Rhob Density

1.08 0.99 0.75 0.56 0.0 DTCO Sonic 0.6 Rhob Density

1.08 0.99 0.75 0.56 0.0 DTCO Sonic 0.7 Rhob Density

RhoVE-Ɛ Bowers GOM slow trend RhoVE-S 0.6 γ = 2.0 V-Rho equation (Bowers, OTC 2001) : V = V 0 + A (ρ - ρ o ) B a = α BOWERS GOM Slow Trend RhoVE-ε RhoVE-S Vo: 4790 4800 4900 A: 2953 2000 4500 B: 3.57 4.2 3 ρ o : 1.3 1.3 1.3 RhoVE interm: a * (RhoVE-Ɛ RhoVE-S) + RhoVE-S

DWGoM Sub-Regional Study Bowers GOM slow trend γ = 2.0 0.6 V-Rho equation (Bowers, OTC 2001) : V = V 0 + A (ρ - ρ o ) B a = 2α α 2 BOWERS GOM Slow Trend RhoVE-ε RhoVE-S Vo: 4790 4800 4900 A: 2953 2000 4500 B: 3.57 4.2 3 ρ o : 1.3 1.3 1.3 RhoVE interm: a * (RhoVE-Ɛ RhoVE-S) + RhoVE-S

DWGoM Sub-Regional Study Bowers GOM slow trend (0.37,0.60) γ = 2.0 0.6 V-Rho equation (Bowers, OTC 2001) : V = V 0 + A (ρ - ρ o ) B a = 2α α 2 BOWERS GOM Slow Trend RhoVE-ε RhoVE-S Vo: 4790 4800 4900 A: 2953 2000 4500 B: 3.57 4.2 3 ρ o : 1.3 1.3 1.3 RhoVE interm: a * (RhoVE-Ɛ RhoVE-S) + RhoVE-S

Bowers GOM slow trend (0.37,0.60) γ = 2.0 0.6 V-Rho equation (Bowers, OTC 2001) : V = V 0 + A (ρ - ρ o ) B a = γα α γ BOWERS GOM Slow Trend RhoVE-ε RhoVE-S Vo: 4790 4800 4900 A: 2953 2000 4500 B: 3.57 4.2 3 ρ o : 1.3 1.3 1.3 RhoVE interm: f(α) * (RhoVE-Ɛ RhoVE-S) + RhoVE-S

Copyright 2017 GCS Solutions, Inc. RhoVe TM Method

RhoVe TM Auto Compositional Changes (executable) RhoVe TM T Thermodynamic Solutions (executable) Acoustic Impedance, Density, Sonic Copyright 2017 GCS Solutions, Inc.

Chemical Compaction From recent advances in EMI (electron microbeam instrumentation) and sample preparation it is now clear that the principal diagenetic processes of sandstones and limestones, compaction and cementation, also operate in mudrocks (Milliken, K., 2017). **Mudrocks at the Scale of Grains and Pores: Current Understanding, Kitty Milliken, 2017, Bureau of Economic Geology, The University of Texas, Austin. Copyright 2017 GCS Solutions, Inc.

MECHANICAL COMPACTION: (effective stress) CHEMICAL COMPACTION: (temperature) Copyright 2017 GCS Solutions, Inc.

Chemical Compaction Diagenesis (late) ** MIT course notes on sedimentary processes Copyright 2017 GCS Solutions, Inc.

Copyright 2017 GCS Solutions, Inc. Temperature versus depth profile BP Kaskida KC292-1BP2

T z o(bml) ( o F) = 65 o F > (266.4*WD) -0.2333 < 36 o F k (z) = ø (z) * k w + (1 ø (z) ) * k mx dt/dz (z) = Q * 3.048E-05 / k (z) T (z) ( 0 C) = T (z-1) ( 0 C) + {dt/dz (z) * ((z (bml) - z (bml-1) ) * 30.48(cm/ft)} Copyright 2017 GCS Solutions, Inc.

PI526-1 Jack Hays DW Gulf of Mexico, U.S.A. Copyright 2017 GCS Solutions, Inc.

P2 P3 P1 0.51 dt rhob 0.0 Bowers DW GoM (Default)

0.51 0.1 Bowers DW GoM (Default)

0.51 0.2 Bowers DW GoM (Default)

0.51 0.3 Bowers DW GoM (Default)

0.51 0.4 Bowers DW GoM (Default)

0.51 0.5 Bowers DW GoM (Default)

0.51 0.6 Bowers DW GoM (Default)

0.51 0.7 Bowers DW GoM (Default)

0.51 0.8 Bowers DW GoM (Default)

0.51 0.9 Bowers DW GoM (Default)

0.51 1.0 Bowers DW GoM (Default)

0.51 1.0 Bowers DW GoM (Default)

σ rhob AI sonic rhob sonic

σ rhob sonic

Copyright 2017 GCS Solutions, Inc.

Alpha σ Copyright 2017 GCS Solutions, Inc.

Alpha σ Copyright 2017 GCS Solutions, Inc.

Alpha σ Rhob Copyright 2017 GCS Solutions, Inc. 56

AREA: Viosca Knoll DATA: wireline 0.00 MDT 57

AREA: Viosca Knoll DATA: wireline 0.07 MDT 58

AREA: Viosca Knoll DATA: wireline 0.10 MDT 59

AREA: Viosca Knoll DATA: wireline 0.20 MDT 60

AREA: Viosca Knoll DATA: wireline 0.30 MDT 61

AREA: Viosca Knoll DATA: wireline 0.40 MDT 62

AREA: Viosca Knoll DATA: wireline 0.50 MDT 63

AREA: Viosca Knoll DATA: wireline 0.60 MDT 64

AREA: Viosca Knoll DATA: wireline 0.70 MDT 65

AREA: Viosca Knoll DATA: wireline 0.75 MDT 66

AREA: Viosca Knoll DATA: wireline MDT 67

RhoVeTM Method (U.S. patent pending - copyright 2016) Predrill PPFG Estimation RhoVe T This presentation and all intellectual property discussed in this presentation are the property of GCS Solutions, Inc. and/or Matt Czerniak.

dtc rhob pseudorhob from dtc more accurate OBG & FG estimation from seismic improved sub-regional PPG calibration for predrill estimates Copyright 2017 GCS Solutions, Inc. 69

dtc rhob pseudorhob from dtc more accurate OBG & FG estimation from seismic improved sub-regional PPG calibration for predrill estimates Copyright 2017 GCS Solutions, Inc. 70

KC WR Sub- Regional Study Area Deepwater Gulf of Mexico KC WR Kaskida Rickenbacker Rickenbacker Bioko Moccasin Buckskin Hadrian Logan Lewis Julia Jack Copyright 2017 GCS Solutions, Inc. 71

Alpha σ Rhob Copyright 2017 GCS Solutions, Inc. 72

σ rhob sonic

σ rhob sonic

σ rhob sonic

rhob σ sonic 76

σ rhob sonic

σ rhob sonic

Alpha σ +/- 10% Rhob Copyright 2017 GCS Solutions, Inc. 79

Advantages Efficiency through simplicity RhoVe TM method has universal application - RhoVe TM method provides interactive solutions for: Prospect Exploration Prospect Maturation Operations RhoVe TM RhoVeR (Remote) Drone Rhob density transformed to effective stress and pore pressure provides a rationale for subdivision of major flow units. Automate pore pressure solutions related to compositional changes using RhoVe TM Auto Thermodynamic transition from mudstone to shale utilize RhoVe TM T; applicable to unconventional shale reservoir plays. Copyright 2017 GCS Solutions, Inc. 80

RhoVeTM Method (U.S. patent pending - copyright 2016) JIP seeking $55,000 investment for: Commercial implementation of RhoVe method as a plug-in or web-based application to include: Real-Time WITSML connectivity, notebook (ipad) capability, 1D temperature modeling, Explore automation capabilities, Copyright 2017 GCS Solutions, Inc.

Chemical Compaction Late Diagenesis JIP (future work) $40,000 investment for: EMI (electron microbeam instrumentation) project to study the effects of late stage diagenesis (temperature, ph) on effective stress and pore pressure (2+ wells), Sample collection, preparation, analysis & reporting 1 1 Bureau of Economic Geology, The University of Texas, Austin Copyright 2017 GCS Solutions, Inc.

Additional References Alberty, M.W. [2011]. SPE Distinguished Lecturer Series, Pore Pressure Detection: Moving from an Art to a Science. Real-Time Downhole ph Measurement Using Optical Spectroscopy, Raghuraman, B. et al. 2007, SPE-93057-PA Mudrocks (shales, mudstones) at the Scale of Grains and Pores: Current Understanding, Milliken, K., 2017, Bureau of Economic Geology The University of Texas, Austin. Jahren, J, Thyberg, B, Marcussen, O, Winje, T, Bjorlykke, K. and Faleide, J.I., 2009, From Mud to Shale: The Role of Microquartz Cementation, AAPG Annual Convention. Sargent, C., Goulty, N.R., Cicchino, A.M.P., Ramdhan, A.M. [2015] Budge- Fudge method of PorePressure Estimation from Wireline Logs with Application to Cretaceous Mudstones at Haltenbanken. Petroleum Geoscience, 21, 219-232. Copyright 2017 GCS Solutions, Inc.

BACKUP SLIDES Copyright 2017 GCS Solutions, Inc. 84

RhoVe versus Bowers Copyright 2017 GCS Solutions, Inc. 85

V = V 0 + A σ B DWGOM V o : 4930 A: 14.2 B: 0.724 Copyright 2017 GCS Solutions, Inc. Bowers - 1995 SPE; 2001 OTC

A = 10.5 87

A = 12 88

A = 13.0 89

A = 14.2 90

A = 16.0 91

A = 16.0 92

A = 16.0 93

V = V 0 + A σ B DWGOM V o : 4100 fps A: 16.0 B: 0.724 Bowers A: 16.0 Vo: 4100 fps 94

RhoVe Method dt Compaction Trend: Δt n = (Δt ml Δt i ) e cz + Δt i Δt i = ø i (Δt ml Δt mx ) + Δt mx Δt mx: : dt matrix: 55 usec/ft Δt ml : dt mudline 200 usec/ft c compaction coeff: 0.00016-0.00030 z: depth below mudline ø i : irreducible porosity (fractional) V-Rho equation (Bowers, OTC 2001) : V = V 0 + A (ρ - ρ o ) B BOWERS DW GOM Slow Trend RhoVE-ε RhoVE-S : c Vo: 4790 4800 4900 A: 2953 2000 4500 B: 3.57 4.2 3 ρ o : 1.3 1.3 1.3 Copyright 2017 GCS Solutions, Inc.

meters Ebrom & Heppard, 2010 α : calculated property 0.37 0. 1.0

0. 0.4

σ rhob sonic

2.165 Salt Shale Shale Shale Sand Marl

γ = 2.2 V-Rho equation (Bowers, OTC 2001) : V = V 0 + A (ρ - ρ o ) B a = γα α γ BOWERS GOM Slow Trend RhoVE-ε RhoVE-S Vo: 4790 4800 4900 A: 2953 2000 4500 B: 3.57 4.2 3 ρ o : 1.3 1.3 1.3 RhoVE interm: f(α) * (RhoVE-Ɛ RhoVE-S) + RhoVE-S

H-23 CVX Offshore Nova Scotia, Canada Copyright 2017 GCS Solutions, Inc.

Offshore Nova Scotia γ = 2.0 Offshore Nova Scotia γ = 2.2

From Mud to Shale: The Role of Microquartz Cementation*

104

VK988-1 RHOB vs. Temp deg F 105