1. Log Analysis Using Microsoft Excel® Focus on the Marcellus
Tim Carr
West Virginia University
Advanced” log analysis techniques using commonly available modern logs and a Microsoft® Excel spreadsheet that is applicable to the Marcellus Shale

2. My Observations

3. Background Costs Are Becoming More Significant
High Land Costs
More Moderate Commodity Price
High Capital Costs
Horizontal Wells & Large Multi-Stage Fracture Stimulations
Key Reservoir Parameters
Thickness
Unit Definitions (Formation  Bed)
Lithology
Thermal Maturity
Total Organic Carbon (TOC)
Gas Fraction (Adsorbed and Free)
Permeability
More Energy at Lower Real Cost
Resources are Adequate
Increased Access to Energy
Slow Incremental Changes
Fossil Energy will be the Major Component of our Energy System for this Century
Need for Investment

4. AVERAGE WELL HEAD PRICE
$2.95 per MMBtu 2002
$6.25 per MMBtu 2007
$7.96 per MMBtu 2008
$3.71 per MMBtu 2009
$4.33 per MMBtu 2010
$4.04 per MM Btu on 11/16/2010
EIA ( )

5. Recent Growth in Natural Gas Production, Lower 48 States, Attributed Largely to Unconventional Gas
What caused the recent growth in domestic gas production?
Next slide shows the unconventional gas production accounts for the 2007 growth; unconventional gas has been increasing while production from other types of gas has decreased.
(EIA, 2010)

6. Natural Gas Supply by source, 1990-2030 (trillion cubic feet)
History
Projection
Unconventional
Alaska
Net imports
Non-associated offshore
Associated-dissolved
Non-associated conventional
Source: Energy Information Administration, Annual Energy Outlook 2009

7. Marcellus Shale Resource
Marcellus Resource
U.S. Resources1
2,080 Tcf
U.S. Proved Reserves2
244 Tcf
Marcellus
Shale Resource3
256 Tcf
Annual U.S. Consumption
23 Tcf
1 Potential Gas Committee, June 18, 2009
2 U.S. Energy Information Administration
3 Marcellus Proved Reserves < 1 Tcf

8. Marcellus Shale Production Forecasts
Sources: “An Emerging Giant: Prospects and Economic Impacts of Developing the Marcellus Shale Natural Gas Play.” T. Considine, R. Watson, R. Entler, J. Sparks, The Pennsylvania State University, College of Earth & Mineral Sciences, Department of Energy and Mineral Engineering. July 24, 2009.
Integrated Resource Plan for Connecticut. The Brattle Group. January 1, (Wood Mackenzie)

9. Marcellus Shale Production Outlook
Source: Williams Partners L.P.

10. Unconventional Resource Production
Technology, Economies of Scale, Integration
Successful pursuit of shale gas requires:
Extensive acreage position leading to large scale developments
Strong integration of engineering and geoscience disciplines
Innovative engineering and tolerance for experimentation
Embedded process for continued integration of technology advances and cost reduction
Cheaper to work underground
Maximize recovery of a cube of shale
Completion technology and horizontal drilling have emerged as the shale gas enablers to extract as much gas as possible from the resource
Cost in developed shale gas plays has been driven down through innovative use of technology, economies of scale, and effective integration of all the disciplines

11. Unconventional Resource Production
Technology, Economies of Scale, Integration
Successful pursuit of shale gas requires:
Extensive acreage position leading to large scale developments
Strong integration of engineering and geoscience disciplines
Innovative engineering and tolerance for experimentation
Embedded process for continued integration of technology advances and cost reduction
Cheaper to work underground
Maximize recovery of a cube of shale
Completion technology and horizontal drilling have emerged as the shale gas enablers to extract as much gas as possible from the resource
Cost in developed shale gas plays has been driven down through innovative use of technology, economies of scale, and effective integration of all the disciplines

12. Gas Shale Characteristics
Very High Gamma Ray Activity (Kerogen Content)
High Uranium
High Resistivity – Low Water Saturation
Relatively Low Clay Content
Smectite to Illite Transition
Low Bulk Density (Kerogen Content)
Kerogen - Petrophysical Characteristics
Bulk Density to 1.2 g/cm3
U to 0.24
Neutron Porosity 50 to 65 p.u.
Gamma Ray Activity 500 to 4000 API
Sonic Slowness 160 µs/ft

13. Three Approaches Logs to be used
Bulk Density g/cm3
Density Porosity Percent or Decimal
Neutron Porosity Percent or Decimal
Photo-Electric Barns
Gamma Ray API Units
Clay Typing – Related to Deposition & Diagensis
Spectral Gamma Ray Logs
Uranium (PPM), Thorium (PPM) and Potassium (Percent)
Compositional Lithology Logs
Rhomaa-Umaa
Computational Analysis (Linear)

14. Spreadsheets Ubiquitous and Low Cost
Provide Some Hands-On Understanding of the Process
Allow Easy Export to Higher End Packages
Use Basic Logs
Clay Typing
Estimate Uranium Content from Full Spectrum Gamma-Ray Logs
Compositional Lithology Logs
Rhomaa-Umaa
Computational Analysis (Linear)
Organic Content (Next Time)
Saturation (Next Time)
Heavily Modified Archie

15. Gamma-Ray Log Analysis
4/21/2017
Gamma-Ray Log Analysis U Th K

16. Gamma-Ray Spectrum
Uranium
Thorium

17. Gamma-Ray Spectrum Schlumberger Log Interpretation Principles
1989, Page 3-7

18. Geochemists’ concept of typical shale and black shale
North American Shale Composite (NASC) Gromet et al. (1984)
Th 12.3 ppm, U 2.66 ppm, K 3.2%
GR = API units
Black Shale Composite (BSC) Quinby-Hunt et al. (1989)
Th 11.6 ppm, U 15.2 ppm, K 2.99%
GR = API units
API unit multipliers: Th ppm 4 : U ppm 8 : K% 16

19. Typical Spectral Gamma-Ray Log Presentation Format

20. Potassium-Thorium Crossplot with Generalized Mineral Fields (after Schlumberger)

21. Potassium-Thorium Crossplot with Generalized Mineral Fields (after Schlumberger)
Increasing Th/K Ratio

22. Thorium and Uranium Concentration and Redox Potential
Adams and Weaver (1958)

23. Gamma-Ray and Spectral Ratio Logs Permian – Cretaceous Central Kansas

24. Photo-Electric and Spectral Gamma Ray
Schlumberger, Log Interpretation Principles 1989, Page 6-4

25. Photo-Electric and Spectral Gamma Ray
Schlumberger, Log Interpretation Principles 1989, Page 6-4

26. Idealized Kansas Pennsylvanian Cyclothem

27. Spectral Gamma-Ray Log Lansing Group, Wabaunsee County, Kansas

28. Chestnut Drive Section Spectral Gamma Ray Response

29. Devonian Shale Analysis
Harrell
Tully
Mahantango
Marcellus
Onondaga

30. Devonian Shale: Oxidizing and Reducing Conditions
Reducing Vs. Oxidizing conditions determined by Th/U
Oxidizing

31. Devonian Shale: Clay Type
Clay type can be determined from Th/K
Illite-Pink
Smectite-Green
Illite can increase porosity by 4%

32. Wells 1 & 3

33. Wells 1 & 3

34. Well 2

35. Project 1 Make sure you open an LAS File with Notepad
Make sure you open an LAS File with Notepad
Import a LAS File to EXCEL
Well 3.LAS
Open Spectral Gamma Ray Template
Well 1.LAS
Marcellus (7375’-7562’)
Well 2.LAS
Marcellus (7359’-7501’)
Create & Examine Plots
What is the difference in the two wells

36. Open with Notepad

37. Importing a LAS File to EXCEL

38. Importing a LAS File to EXCEL

39. Importing a LAS File to EXCEL

41. Introduction to Porosity Logs
Porosity Logs DO NOT Directly Measure Porosity
Acoustic (Sonic) Logs Measure Wave Travel Time
Density Logs Measure Formation Bulk Density
Neutron Logs Measure Formation Hydrogen Content

42. Neutron Log Applications
Porosity
Lithology with Density and/or Sonic
Gas Indicator
Clay Content
Correlation
Cased Hole

43. Neutron Tool Background
Outgrowth of Work by Italian Physicists (1935)
Slowing down and stopping of neutrons by a hydrogen rich material (e.g., water).
Radioactive Source of High Energy Neutrons
Americium and Beryllium
Fairly Shallow Zone of Investigation
~ 6 inches (Flushed Zone (Rxo) in most cases)
Neutrons lose energy each time they collide with nuclei as they travel through the formation
Greatest loss in energy when neutrons collide with nuclei of a similar mass
Hydrogen atoms
As the neutrons slow they can be captured and emit a gamma ray.
Reduction in Neutron Flux (Increased Gamma Rays) is largely controlled by concentration of hydrogen in the formation.
Water (Oil) Filled Porosity in Flushed Zone of Clean Units
Clays
Lithology Effect
Hydrocarbon Gas Effect
Depress apparent neutron porosity

44. The Neutron Porosity Tool

45. Historical Development of Neutron Logging
Common Curve Mnemonics
ΦN, PHIN, NPHI
Usually Tracks 2 or 3 and dashed line.
Units
Counts
%, Decimal Fraction

46. Neutron Energy Loses

47. Density Log Applications
Porosity
Lithology with PE, Neutron and/or Sonic
Gas Indicator
Synthetic Seismograms with Sonic
Rock Properties with Sonic
Poisson’s Ratio, Young’s Modulus
Clay Content
Borehole Conditions (Size and Rugosity)

48. Density Tool Background
Source of High Energy Gamma Rays
Cesium 137
Shallow Zone of Investigation
<2 inches
Gamma rays interact with the electron clouds of the atoms they encounter, with a reduction in the gamma ray flux, which is measured by both a near and far detector.
Higher Energy Range Affected by Compton Scattering
Reduction is a function of the electron density of the formation
Number of Electrons Matched by the Number of Protons
In Most Cases Z/A = 0.5
Z - Atomic Number
A – Atomic Mass
Two Density Values
Bulk Density (RhoB or ρb) – Measured by Logging Tool – Solid + Fluid
DEN, ZDEN
Matrix Density (ρma) – Density of the Rock that has no Porosity
Hydrocarbon Gas Effect
Enhances apparent density porosity
For any element, the number of electrons is matched by the number of protons, which is the atomic number, Z. The atomic mass is contained in the atomic nucleus, is effectively the sum of the number of protons and neutrons, and is given by the atomic number, A. In general, the number of protons is approximately the same as the number of neutrons, so that the Z/A ratio of many elements is close to 0.5, particularly for elements that are in the lower part of the periodic table. Using this simple atomic theory and a Z/A ratio of 0.5, the actual measurement of electron density can be converted to an apparent density, measured in units of grams per cubic centimeter, which is usually close to the real density of common rock types.
The primary use of the density log is as a measure of porosity, using a simple mass balance relationship, and interpolating between the matrix mineral density (2.65 quartz; 2.71 calcite ; 2.87 dolomite) and mud filtrate, since most of the density reading is from the flushed zone. The difference in density between that of any residual oil and the mud filtrate is usually insufficient to affect porosity estimations. However, the markedly low density of any residual gas will strongly influence the density reading to suggest a higher apparent porosity.

49. The Formation Density Tool

50. Density Porosity ΦD = (ρma – ρb) / (ρma – ρfluid) DPHI, PHID, DPOR
Sandstone gm/cm3
Limestone gm/cm3
Dolomite gm/cm3
Anhydrite gm/cm3
Halite gm/cm3
Freshwater 1.0 gm/cm3
Saltwater ~1.15 gm/cm3

51. Question
Why does ΦN read
much higher
Than ΦD in the red boxed
area?
What are the general
lithologies
in this well?

52. Photo Electric Pe Tool Lithology with Density, Neutron and/or Sonic
Supplementary Measurement of the Density Tool
1970’s Onward
Lower Energy Range Gamma Rays Affected by Photoelectric Effect
Logged Value is a function of Z - Atomic Number
Pe = (Z/10)3.6
Barns per electron
Only mild affect of Pore Volume and Fluid/Gas Content
Quartz = 1.81 Barns
Dolomite = 3.14 Barns
Calcite = 5.08 Barns
Pe, PE, PEF
For any element, the number of electrons is matched by the number of protons, which is the atomic number, Z. The atomic mass is contained in the atomic nucleus, is effectively the sum of the number of protons and neutrons, and is given by the atomic number, A. In general, the number of protons is approximately the same as the number of neutrons, so that the Z/A ratio of many elements is close to 0.5, particularly for elements that are in the lower part of the periodic table. Using this simple atomic theory and a Z/A ratio of 0.5, the actual measurement of electron density can be converted to an apparent density, measured in units of grams per cubic centimeter, which is usually close to the real density of common rock types.
The primary use of the density log is as a measure of porosity, using a simple mass balance relationship, and interpolating between the matrix mineral density (2.65 quartz; 2.71 calcite ; 2.87 dolomite) and mud filtrate, since most of the density reading is from the flushed zone. The difference in density between that of any residual oil and the mud filtrate is usually insufficient to affect porosity estimations. However, the markedly low density of any residual gas will strongly influence the density reading to suggest a higher apparent porosity.

53. Photoelectric factor log

54. Compositional Analysis
Combing More Than Two Logs

55. Compositional Analysis
Determine Lithology
Graphic Plots
Computation
Identification and Semi-Quantitative Estimates

56. Porosity Log Combinations
Single Porosity Measurement
Lithology is Specified for Correct Porosity
Choice of Matrix Value
Two Porosity Measurements
Two Lithologies can be Predicted along with Porosity
Three Porosity Measurements
Three Lithologies can be Predicted along with Porosity
Greater the number of Measurements the Greater the Complexity of the Lithology that can be Estimated

57. 2 Logs 2 Minerals

58. Dolomitic-Limestone System

59. Three-Measurement Cross-Plot
Three Mineral Matrix Can Be Determined
Usually Reduce From 3-D to 2-D
Collapse the 3 measurements to two axes with common denominator
M-N Plots
Axis 1 – Sonic and Density
Axis 2 – Neutron and Density
Problem of Density and Sonic being Correlated
Addition of Pe in Newer Methods

60. M-N Cross Plot

61. M – N Crossplot Remove the effect of pore fluid
4/21/2017
M – N Crossplot
Remove the effect of pore fluid
Usually drilling fluid
Combine Sonic and Density Logs (M)
M = (∆tfluid – ∆tmatrix) / (ρmatrix – ρfluid)
Combine Neutron and Density
N = (Φnfluid – Φn matrix) / (ρmatrix – ρfluid)

62. M-N Cross Plot

63. RHOmaa – Umaa Crossplot
Mineral Identification (MID) Plots
Apparent Matrix Density RHOmaa
Density and Neutron
Apparent Matrix Photoelectric Cross Section Umaa
Density, Neutron and Photoelectric Effect

64. Apparent Matrix Density RHOmaa

65. Photoelectric (PE) Factor

66. Volumetric Photoelectric Absorption U/cm3
The photoelectric absorption index (Pe) is measured in units of barns per electron. In order to linearize its relation with composition, the variable must be converted to a volumetric photoelectric absorption index (U) with units of barns per cc
and is approximated by:

67. Volumetric Photoelectric Absorption U of the matrix
This is the volumetric photoelectric absorption coefficient of the zone (matrix plus fluid). The hypothetical volumetric photoelectric absorption coefficient of the matrix is UMAA.
or approximated by

68. Umaa Values (Apparent 𝜙)

69. RHOmaa
Umaa
Plot
Pyrite

70. Shale Characterization

71. Computational Analysis
2 Logs 2 Minerals

72. Computational Analysis
C - matrix of the log responses of the components
V - vector of the component proportions
L - vector of the log readings
To Solve for V need the inverse of the component
matrix
CV=L
V = C-1L

73. Log response equations:
Rewritten as matrices:

74. We are Saved - Easily computed in Excel
The compositional solution vector is then given by pre-multiplying the log response vector by the inverse of the coefficient matrix
We are Saved - Easily computed in Excel

76. Compositional Analysis

77. Project 2 http://www.geo.wvu.edu/~tcarr/PTTC_11_2010
Use Parameters From Appendix B
Open Compositional Template
Load in Separate Template Well 1.LAS
Marcellus (7375’-7562’)
Onondaga (7562.5’ 7578’)
Why are data points outside the Rhomaa-Umaa Triangle
Load in Separate Template Well 2.LAS
Marcellus (7359’-7501’)
Onondaga (7501.5’ 7516’)
Create Computational Plots
What is the difference in the two wells

79. My Observations

81. Email: tim.carr@mail.wvu.edu
Earth at Night Credit: C. Mayhew & R. Simmon (NASA/GSFC), NOAA/ NGDC, DMSP Digital Archive
Tim Carr
Phone: