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GeologyPetrophysics

Lithology Identification From Well Logs




Learning Objectives

After completing this course “Lithology Identification From Well Logs“, you will be able to:

  • Use spontaneous potential (SP) logs to help determine the formation lithologies.
  • Analyze natural and spectral gamma ray well logs to establish the lithologies.
  • Derive the formation lithologies from porosity logs.
  • Generate a range of specialist crossplots to facilitate lithology determination.
  • Interpret multi-mineral analyses to establish the formation lithologies.

Overview

Well logs are an invaluable source of information for geologists and petroleum engineers, providing critical insights into subsurface formations. One of the key tasks in analyzing well logs is lithology identification, which involves determining the rock types present in a wellbore based on the recorded log measurements.
Well logs, whether they are acquired by logging while drilling (LWD) or wireline operations, can be integrated with the other subsurface data acquired to interpret the lithologies (Figure 1) of the different formations encountered when drilling a well.

This article will explore the process of lithology identification from well logs, discussing the techniques, challenges, and benefits associated with this important geological analysis.

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Figure 1: Different geological formations and lithologies encountered in the drilled interval of a well

Introduction

Lithology identification from well logs is a fundamental task in the field of petroleum geology. It involves interpreting the recorded log data to determine the types of rocks encountered while drilling a well. By understanding the lithology, geoscientists can assess reservoir characteristics, such as porosity, permeability, and fluid saturation, which are crucial for reservoir evaluation and hydrocarbon exploration.

Well Logs: A Brief Overview

Well logs are measurements taken during drilling or after completion of a well. These measurements provide information about the properties of rocks, such as their electrical, acoustic, or radioactive characteristics. Common types of well logs include gamma ray, resistivity, sonic, density, and neutron logs, among others. Each log provides specific data that can aid in lithology identification.

Importance of Lithology Identification

Accurate lithology identification is vital for various reasons. Firstly, it helps in understanding the geological history of the formation and the depositional environment. This information is crucial for predicting the presence of hydrocarbons and estimating the reservoir’s production potential. Additionally, lithology identification aids in wellbore stability analysis, drilling optimization, and formation evaluation, enabling engineers to make informed decisions during the drilling and production phases.

Well Logs for Interpreting Lithologies, Techniques for Lithology Identification

Various well log measurements and techniques are employed for lithology identification. Here are some commonly used ones:

Spontaneous Potential (SP) Log

Spontaneous potential (SP) log (Figure 2)

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Figure 2: Spontaneous potential log as a lithology indicator

Spectral Gamma Ray Log




Spectral natural gamma ray log (Figure 3)

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Figure 3: Spectral natural gamma ray log data

Natural Gamma Ray Log

Natural gamma ray log (Figure 4)

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Figure 4: Natural gamma ray log used in lithology interpretation

Density Log: Photoelectric Factor

Density log: photoelectric factor, ρe (Figure 5):

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Figure 5: Photoelectric factor data from a density log useful for lithological and mineralogical interpretation

Bulk Density

Bulk density, ϕb (Figure 6):

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Figure 6: Density log: bulk density

Neutron Porosity Log

Neutron porosity log: neutron porosity, ϕN (Figure 7):

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Figure 7: Neutron porosity log: neutron porosity

Sonic, or Acoustic, Log




Sonic, or acoustic, log: transit time, Δt (Figure 8):

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Figure 8: Sonic, or acoustic, log: transit time

With the exception of the photoelectric factor measurement, ρe, no single porosity tool measurement gives, by itself, a direct indication of the formation lithology. All other well logs require some interpretation, or calibration, prior to their use as lithology indicators.

Useful lithology information can be derived with combinations of different porosity tool measurements.

The most useful combinations are:

Combination Logs for Interpreting Lithologies

Density-Neutron Crossplot

Density-neutron crossplot, ρb versus ϕN (Figure 9):

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Figure 9: Density-neutron crossplot as a lithology indicator

Photoelectric Factor Versus Bulk Density Crossplot

Photoelectric factor versus bulk density crossplot, ρe versus Δt (Figure 10):

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Figure 10: Photoelectric factor versus bulk density crossplot

Sonic Versus Neutron Porosity Crossplot




Sonic versus neutron porosity crossplot (Figure 11), Δt versus ϕN.

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Figure 11: Sonic-neutron crossplot as a lithology indicator

Photoelectric Factor From Density Log in Conjunction With Density and Neutron Porosity

Photoelectric factor from the density log used in conjunction with density and neutron porosity (Figure 12):

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Figure 12: Photoelectric factor as a lithology indicator used in conjunction with density and neutron porosity

M-N Crossplot

The M-N crossplot (Figure 13 and Figure 14), where the M and N values plotted on the crossplot with M (y-axis) and N (x-axis) axes are the slopes of the individual lithology lines on the sonic-density and density-neutron crossplots, respectively.

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Figure 13: M-N crossplot template showing the locations where pure lithologies plot
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Figure 14: Example of real well log data plotted on an M-N crossplot to enable lithology determination

The Matrix Identification Crossplot

The matrix identification crossplot (MID plot) (Figure 15), which is a crossplot of the apparent matrix density versus the apparent matrix travel time:

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Figure 15: Matrix identification plot (MID) as a lithology indicator

Photoelectric Factor ρe and Spectral Gamma Ray Playbacks




Photoelectric factor ρe and spectral gamma ray measurements of potassium, uranium and thorium (K, U, and Th) (Figure 16):

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Figure 16: Photoelectric factor ρe and spectral gamma ray measurements of K, U, and Th

Some logging service companies offer proprietary multi-mineral elemental analysis well log interpretation techniques for the log data which they have acquired. These analyses (Figure 17) compute the most probable formation lithology, mineralogy and pore fluid volumes, often using a multi-log, least squares inversion technique. Such petrophysical techniques are most applicable in reservoirs of mixed lithologies and mineralogies, and in dual porosity reservoir systems. The correct identification of all the minerals likely to be encountered in the well is absolutely critical to constraining the number of possible solutions and so generate a plausible log interpretation.

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Figure 17: Multi-mineral elemental analysis well log interpretation

It is also possible to play back digital porosity log data in different formats to give a visual indication of the rock type and lithology, in combination with mud logs (Figure 18) and any available full diameter or sidewall core data (Figure 19). In sections of mixed lithology and different formations within an open wellbore section, it is essential to break the interval logged into several different, coherent zones (zoning), and to identify the relevant rock type(s) for each zone to correctly pick the parameters needed for the shale volume, porosity and water saturation calculations.

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Figure 18: Mud log indicating lithologies drilled
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Figure 19: Integration of full diameter core data with well logs for lithology identification



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