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Interactive Petrophysics Advanced Training and Exercise Guide Version 3.1

Schlumberger Information Solutions December 30, 2004

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Copyright Notice © 2004 Schlumberger. All rights reserved. No part of this manual may be reproduced, stored in a retrieval system, or translated in any form or by any means, electronic or mechanical, including photocopying and recording, without the prior written permission of Schlumberger Information Solutions, 5599 San Felipe, Suite 1700, Houston, TX 77056-2722.

Disclaimer Use of this product is governed by the License Agreement. Schlumberger makes no warranties, express, implied, or statutory, with respect to the product described herein and disclaims without limitation any warranties of merchantability or fitness for a particular purpose. Schlumberger reserves the right to revise the information in this manual at any time without notice.

Trademark Information Software application names used in this publication are trademarks of Schlumberger. Certain other products and product names are trademarks or registered trademarks of their respective companies or organizations.

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Table of Contents Copyright Notice...................................................................................................................ii Disclaimer.............................................................................................................................ii Trademark Information ........................................................................................................ii

About This Course ................................................................................................. 1 Chapter 1 Interactive Mineral Solver.................................................................... 3 What is the Interactive Mineral Solver? ...................................................................... 3 Run Interactive Mineral Solver to Analyze A Well...................................................... 4

Chapter 2 Monte Carlo Error Analysis............................................................... 11 What is Monte Carlo Error Analysis?........................................................................ 11 Run a Monte Carlo Error Analysis on the results of an interpretation ..................... 12

Chapter 3 Fuzzy Logic Curve Prediction........................................................... 17 What is Fuzzy Logic? ................................................................................................ 17 Create a permeability curve from core permeability using Fuzzy Logic.................. 19

Chapter 4 Shear Sonic and Fluid Substitution ................................................. 23 What is Shear Sonic?................................................................................................ 23 What is Fluid Substitution?........................................................................................ 23 Create a shear from a compressional sonic............................................................. 26 Shear Velocity Quality Control Crossplot ................................................................. 27 Quality control the shear sonic created in the previous exercise. ........................... 27 Calculate the Fluid Substitution ................................................................................ 28

Chapter 5 Elastic Impedance .............................................................................. 35 What is Elastic Impedance? ..................................................................................... 35 Calculate the Elastic Impedance .............................................................................. 36

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About this Course

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About This Course The following training material introduces the advanced interpretation modules available in Interactive Petrophysics. The Merlin.las and Test Well1.las will be used as the data set for these exercises. The data should be loaded and saved to the database. It is assumed that the student has been to the Interactive Petrophysics introduction class and is familiar with most of the basic functionality. This manual is to teach the use of the software and not the theory of petrophysics.

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Interactive Mineral Solver

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Chapter 1 Interactive Mineral Solver What is the Interactive Mineral Solver? The Interactive Mineral Solver (MinSolve) is a module in Interactive Petrophysics used to solve for mineralogy, porosity and fluid saturations in a formation. This program uses a probabilistic approach in trying to solve the system of equations and find the most probable result for each layer in the well. This is traditionally called “Probabilistic Interpretation”. The typical workflow to setup a “Mineral” or “Rock” model is as follows: 1. Define a “Mineral” or “Rock” model of the formation. A mineral or rock model describes the main minerals and fluids in the rock. For example, the main minerals for a Carbonate / Oil reservoir consist of Limestone, Dolomite, Anhydrite, Clay, Oil and Water. 2. Select the logging tools to be used. The logging tools (Equations) that are available in the well are added to the model. You should have at least the same number of equations as minerals and fluids. 3. Setup the parameters relating to the tool equations to the Mineral model. o

The equation end-points (100%) reading for each mineral are entered. For example, the density would be 1 gm/cc if a formation layer were 100% filled with water.

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The weighting factor, which is the relative importance of one equation to another. For example, the density tool is generally considered to provide a far more accurate measurement of porosity then the sonic tool. Hence, the weighting factor of the density should be higher. 4. Run the model, and the reconstructed tool responses are compared to the original input tool responses.

All end-point parameters and / or Mineral model can be adjusted to give the best possible reconstruction. Multiple Mineral Models Generally one Mineral Model is not sufficient to describe all formations present in a well. For example, one model is needed for a carbonate interval, another for a clastic interval. Special models are often required for zones of bad-hole conditions, where some of the logging tools are not reading correct values. In case of multiple mineral model, the separate Mineral models are combined to give a final “Combined Result”. The models are combined on a zonal basis, using a “Mixing Routine”. The “Mixing routine” allows the use of logic statements Interactive Petrophysics Advanced 12/30/04

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to decide which model should be used for the Combined result. Mixing routines can be as simple as setting a single model over a zone or more complex – for example, using multiple logic statements to determine which model to use for each individual depth level.

Multiple mineral models are combined to give a final “Combined Result”. NOTE: Please obtain detailed information about the MinSolve module in the Help guide accessible from Interactive Petrophysics.

Run Interactive Mineral Solver to Analyze A Well 1. Load the Merlin.las data using the Las loader in Input/Output. 2. Plot the loaded data using the Triple-combo template to see if all the data was loaded properly. 3. Use the Trend Curve module to create the trend curve for LLD.

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Go to Edit and click on Interactive Trend/Square Curve to launch the module.

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With the Trend/Square Curve module open, and Trend Curve selected, Interactive Petrophysics Advanced 12/30/04

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click on the LLD curve in the Top Insert of the plot, this will select LLD in the Curve to Trend box. •

Click on Start trend and then click on the LLD curve at about 4525 m, to determine resistivity of shale in the shale zone. You can now click on the point already selected, and the point becomes a cross hair, which you can use to drag the trend line to sit about the middle of the LLD curve in the shale zone.

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Click on the Finish Trend, and accept it to be displayed in the Track. You may want to save the trend on disk if you intend to edit it later on by using Recall Trend.

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You can now use the Trend Curve (LLD_t) or the value of the trend curve as the Illite Resistivity parameter.

NOTE: The 'Trend Curve' is very useful. For example, defining 'GRclean' and 'GRshale' lines over large log intervals, or for capturing Rw trends over long well sections as input to Sw determination. Trend Curves can be created for any log analysis parameter and substituted in any IP calculation module where a parameter is called for. The trend curve can be used to compute straight-line trends for logarithmically scaled curves for example, for defining normal shale compaction trend curves for sonic/resistivity in pore pressure analysis. 4. Make a Neutron-Density-GR crossplot to identify lithology, so that a model could be determined. 5. Identify different minerals on the crossplot by creating an area around the points of interest and then use the Create curve from Areas and plotting it on the main plot, to locate the depth of occurrence of the minerals identified. 6. Create a Temperature channel, using the Temperature Gradient module under Calculation. Use surface temperature as 60 degF and surface depth as 0 ft; BHT 285 degF, and bottom depth is 4739.6 ft. 7. Go to Mineral Solver Preprocessing to calculate U from PEF and RHOB, Ct from LLD and Cx0 from MSFL. 8. Now launch the Mineral Solver module, make sure the correct Resisitivity and Temperature curves are selected. 9. Select the SW logic tab, and select the saturation equation to be Indonesia equation. 10. Go to the Parameters tab and update the Waters/Clays tab parameters as below:

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11. Go to the Models tab to make the first model and setup the model as below:

12. Run Model and Make Plot. You will see that the Error is very high in the zone above 4520 m, and quite high in front of shales. The reconstructed GR and RHOB are not matching the original curves above 4520, and only the RHOB is not matching below that in front of shales.

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13. Change the RHOB for Illite to 2.75, which is the RHOB value in front of shales, and rerun the model. This time the error is reduced to the zone above 4520 and 4656 to 4666 m. The upper one is probably due to Anhydrite and the lower is due to bad hole. Another detail you may notice is that there are some hydrocarbon traces showing in front of shales. 14. Go back to Parameters tab and under the Sw Logic tab, select ‘m vari with Vcl’ and change the Vcl Cutoff to 0.4. Run Model 1 again and you will notice the shales have been cleaned up. 15. Go to the Models tab and click on the right arrow beside Model 1. This changes Model 1 with Model 2. Create the Anhydrite model as below, and Run Model then Make Plot. This model will fit well with the Anhydrite section above 4520 m.

16. Go to Model 3 window to create a Bad Hole Model and set it up as below, Run Model then Make Plot to see the results:

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17. Now we need to get the complete analysis, by combining the results of each model over the appropriate zone. The Anhydrite model is applicable over a specific depth zone above 4520 m. So we need to create a Zone from the top depth to 4520 m. For the rest of the well we shall use Model 1 as the default model, and Model 3 kicks in whenever VCL calculated in Model1 exceeds 0.5. 18. Go to the Mixings tab and create Mixing 1 as follows:

19. Shift to Mixing 2 with the arrow, and create Mixing 2 as follows:

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20. Now go to the Parameters tab and create a new zone for the Anhydrite model by clicking on New Zone, select the existing Zone, enter the depth where you want to split the Zone (4520 m), and click on Split Zone.

21. Select Mix 2 for the top Zone, as this refers to Model 2, which is the Anhydrite model.

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22. Now Run, which will run all the models then Make Plot, which will create the combined plot according to our mixing and zoning selections:

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Chapter 2 Monte Carlo Error Analysis What is Monte Carlo Error Analysis? Monte Carlo Error Analysis is a technique of quantifying random errors caused by the selection of parameters in log analysis. This technique allows the exact estimation of uncertainty by computing several thousand possible solutions of reservoir parameter combinations. The result will be a summation report of the net pay, average porosity values and other reservoir properties. Where do the errors come from? The errors come from various parameters as the petrophysicist makes many judgments throughout the log interpretation process as to which are the best-input parameters to use, such as Clay Volume, Porosity, Water Saturation, and the Cutoff values. For example, is the Gamma Ray clean in a zone 20 API, or should it be 25 API, or is the Rw for the zone 0.25 Ohmm or 0.3 Ohmm. The likely error range of these estimated parameters can be computed through randomly changing the input parameters within a certain range of values. A complete analysis workflow is executed and the results are stored. This workflow is repeated several thousand times, storing the results each time. When the analysis is finished, the complete result can then be analyzed. Since there are several thousand possible solutions - one from each execution displaying the results in an organized manner is essential. Normally, the results are sorted in an ascending order for each input parameter. The results contain both the user computations along with the percentile computations for easy comparison. After completing the Monte Carlo analysis, not only can the best estimate of the interpretation be given, but also the most likely range of errors. A tornado plot error analysis (see figure below) can be generated showing the relative importance of each parameter in the overall error.

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Tornado Plot from Monte Carlo Error Analysis, showing the parameters and potential error values NOTE: Please obtain detailed information about the Monte Carlo Error Analysis module in the Help guide accessible from Interactive Petrophysics.

Run a Monte Carlo Error Analysis on the results of an interpretation 1. Load Test Well 1.las. 2. Compute a Clay Volume, Porosity/Sw, and a Cutoff/Summation. NOTE: These parameters are provided or you may do your own interpretation. 3. From the IP main window, select Interpretation/ Monte Carlo Error Analysis. 4. Select the Model tab if not selected. 5. Make sure that the Use column box is checked for Clay Volume, Porosity Sw and Cytoff. The set names should contain the defaults for the current analysis. These can be left as the default.

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6. Select the Clay Volume tab and remove the check from the SP clean, SP clay, Res clean, and Res clay.

7. Notice the Type Shift and Shift Distribution are selected from drop down lists. The Initial Value, Low Value Shift and High Value Shift can Interactive Petrophysics Advanced 12/30/04

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be changed by editing the values. 8. Click the Porosity Sw tab. Notice the Parameter Name, Type Shift, Shift Distribution, Initial Value, Low Value, and High Value. Leave the defaults.

9. Click the Cutoff tab. Notice the Parameter Name, Type Shift, Shift Distribution, Initial Value, Low Value, and High Value. Turn off the Other Cutoff 1, 2, 3.

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10. Click the Input Curves tab. Make sure all curve names are selected.

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11. Click the Output Curves tab. Make sure PHIE, SW, and VWCL are selected

12. Keep the defaults for the Stop simulation, Update Graphics and the Output Percentiles. 13. Click the Display button by the Auto Log Plot and arrange the windows so that you are able to see both the Monte Carlo Simulation window and the log plot. 14. Click Start to begin the simulation. 15. Notice the Log Plot updating automatically every 20 iterations. 16. After the simulation is complete maximize the Log Plot to view the MN, PSD and MSN curves created. 17. Click the Display button by Histogram and Crossplot to view these graphical outputs. 18. Go back to the Monte Carlo Simulation window and click Results Listing view the results. 19. Close the Results Listing window, the Log Plot and the Monte Carlo Simulation window.

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Chapter 3 Fuzzy Logic Curve Prediction What is Fuzzy Logic? The Fuzzy logic allows the prediction of one curve from a number of other curves. Single or Multiple wells can be used to create the prediction model. Fuzzy Logic is a type of logic that recognizes more than simple true and false values. With fuzzy logic, propositions can be represented with degrees of truthfulness and falsehood. For example, the statement, today is sunny, might be 100% true if there are no clouds, 80% true if there are a few clouds, 50% true if it's hazy and 0% true if it rains all day. The program analyzes the input curves by dividing the data up into bins. The number of bins maybe selected by the user and depends on the type of data to predict. The ‘Variable size bins’ should be used for discrete input data such as Facies log data. For this type of data, the number of bins depends on the number of Facies. For example, if you have 'facies-type' data with facies numbers between 1 and 8, then set the number of bins to '8', the starting bin number will be '1' and the bin width will be '1'. If user selects this option, the ‘Weight bin by number of samples in bin’ needs to be toggled on. The ‘Equaled sampled bins’ should be used for continuous data (other than Facies data type). The user selects the number of bins; bin numbers should be large enough to describe the range of data but small enough so that the statistics in each bin is not too erratic. This can be accomplished by running the prediction model few times using different number of bins and then comparing the final result with the input curve defined in the prediction model. The program will try to distribute the data samples equally into each bin however in some cases, this will not always provide an exactly equal number of samples in each bin. For example, when data samples have more identical data values than there should be in a bin. The data samples in each bin are computed to provide statistical data of the Mean and Standard deviation for each input curve. The Mean and Standard deviation statistics for each curve represents the model and are the inputs to the prediction model. The final result will be an output curve with the highest combined probability of all the input curves in the bins. After the final result is produced and quality controlled, the prediction model can then be used to predict similar curve for the other wells in the project.

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Fuzzy Logic module is used to produce the Perm_ml (most likely) curve. It is compared with PERMCORE.

NOTE: Please obtain detailed information about the Fuzzy Logic module in the Help guide accessible from Interactive Petrophysics.

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Create a permeability curve from core permeability using Fuzzy Logic 1. From the IP main window, select Interpretation > Statistical Curve Prediction > Fuzzy Logic. 2. Click the Input tab. 3. Under the Well 1 column, select Test Well 1 for the Well Name row. 4. Select PERMCORE for the Curve to Predict row. 5. Under the Default Name column, enter Perm for the Curve to Predict. 6. Under the Well 1 column, select RHOB for the Input Curve 1 row. 7. Select TNPH and SGR for Input Curve 2 and Input Curve 3. Notice the corresponding Default Names are populated. 8. Leave the defaults for the Log Norm, Model Build depths and Model Run depths.

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Interactive Petrophysics Advanced Features 9. Click the Create Model tab. 10. Enter 10 for the Number of bins. 11. Select the Equal sampled bins. 12. Check the Weight bin by number of samples in bin.

13. Leave the defaults for the DISCRIMINATORS and the Model Set Name. 14. Click Run and the Model Statistics window will appear.

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15. Use the right arrow from the Scroll Bin Statistics to view bins 1-10. 16. Scroll back to bin 1 with the left arrow.

17. Click the Show Stats Histo’s button to view the histogram. 18. Close the histogram window. 19. Click the Show Curve Xplots button to view the crossplots. 20. Close the crossplot window. NOTE: The Bin value rows are editable.

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Interactive Petrophysics Advanced Features 21. Select the Run Model tab.

22. For the Output Result, select Most Likely, Wt av. 2 most likely, Most Likely high/low probability and Wt av. 2 most likely high/low probability. Leave the defaults for the Curve Name, Probability, Closeness of fit, Result Bin and Percentile. 23. Use Perm for the Default curve name and click Run. 24. Click the Show Log Plots button to view a log plot of the results. Notice the results in each track. 25. Right mouse click in the closeness of fit track (track 4) and open up the histogram. From the cumulative frequency curve it can easily be seen that 70% of the results are within 2 bins and 50% are within 1 bin. 26. Close the crossplot and log plot window. 27. Click the Show CrossPlot button. View the results on the crossplot. The crossplot will seem to be banded since the results have only discrete values (the mean of each bin). 28. Close the crossplot window. 29. Close the Fuzzy Logic window.

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Shear Sonic and Fluid Substitution

Chapter 4 Shear Sonic and Fluid Substitution What is Shear Sonic? The Shear sonic module is used to create a synthetic shear sonic curve from a compressional sonic log, or to quality control a recorded shear sonic curve. The shear sonic or “DT Shear” is calculated using the Greenberg-Castagna (1992) empirical relationships for different minerals, and needed as an input curve in the Fluid Substitution module. It is also used to compute the velocity compressional (Vp) and velocity shear (Vs) curves plus the 'Poissons ratio', 'Vp/Vs ratio', 'Bulk Modulus' and 'Shear Modulus' curves. The relationship between Vp and Vs curves are analyzed in a cross plot to check that the recorded shear sonic curve is a good shear curve and is not a mud-wave or Stoneley-wave velocity produced by bad processing of the sonic waveform data.

What is Fluid Substitution? The Fluid Substitution is a process of removing the effect of the drilling fluid in order to make a good synthetic seismogram from the density and velocity (sonic tool) that represent the true nature of the formation. The density and sonic logs are run in a borehole and make measurements in the invaded zones. The fluid substitution is done by first removing the effects of invasion of the logs and producing logs, which represent the formation containing 100% water. The second step is to replace any water by the true hydrocarbons seen in the formation. The fluid substitution for the density is relatively straight forward since the density equation is linear and well characterized. Fluid substituted densities:

Where reservoir condition is 100% wet.

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: input log density

fbrine : density of brine for the reservoir fluids fSxo

: density of the fluid mixture in the flushed zone

fRes

: density of the fluid mixture in the reservoir zone

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Fluid Substitution

: input porosity The fluid substitution for the sonic is more complicated due to the different hydrocarbon (gas) effect on velocity at different frequencies of sound. Sonic logging tools are at relatively high frequency around 15kHz compared to seismic frequencies, which are around 5 Hz. The effect of a small amount of gas (~3%) in a formation is relatively significant at seismic frequency while logging tools will hardly notice it. Since we are interested in the response at seismic frequencies we must first remove the hydrocarbon effects at logging tool frequencies in the invaded zone and then substitute in the hydrocarbon response at seismic frequencies. The basic equation for removing drilling fluid from the sonic tool comes from Gassmann, which relates the elastic bulk and shear moduli of a fully saturated rock to the elastic and shear moduli of the dry-rock frame, porosity, and bulk moduli of the mineral phase and pore fluid.

Where, Kf

: Fluid module of the pore space (hydrocarbon and water)

Kma

: matrix moduli

Kd

: dry rock moduli : porosity

Ksat

: wet rock moduli

Once the wet rock moduli for the different zones are found, the velocity is easy to calculate.

Where,

Ksxo : wet rock moduli in the flushed zone KRes : wet rock moduli in the non-invaded zone

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Fluid Substitution VpRes: velocity in the non-invaded zone

The substituted density and sonic logs will then be used to produce the acoustic impedance AI (density x velocity). From the AI, the reflection coefficient (RC) of a boundary between two different types of rock can be calculated and then used to generate the synthetic seismograms.

RC = (D2 V2 – D1 V1) / (D2 V2 + D1 V1)

D1: density of medium 1 D2: density of medium 2 V1: velocity of medium 1 V2: velocity of medium 2 A1: acoustic impedance of medium 1 A2: acoustic impedance of medium 2 .

The most commonly usage of a synthetic seismogram is to compare it to the normal seismic to depth tie the seismic to the logs.

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Fluid Substitution

NOTE: Please obtain detailed information about the Shear Sonic and Fluid Substitution modules in the Help guide accessible from Interactive Petrophysics.

Create a shear from a compressional sonic. 1. From the IP main menu, select Interpretation > Rock Physics > Shear Sonic QC/Create. 2. Select the Create DT Shear tab.

3. Select DTLN as the DT compressional input curve. 4. Enter DTsEmp for the output curve name. 5. Select uSec/ft for the units. 6. For the Mineral Method, select curves. 7. Select the Default radio button for sandstone. 8. Pick the VCL curve, for shale from the drop down list. 9. Leave the constant values a, b and c as the defaults. 10. Select Decimals for the Mineral Volumes. 11. Leave top and bottom depth as default and click Run. 26

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Fluid Substitution 12. Open a resistivity/sonic log plot.

13. Add the sonic shear to the sonic track and compare the newly created shear with the compressional.

Shear Velocity Quality Control Crossplot The Shear Velocity Quality Control Crossplot uses the Greenberg-Castagna empirical relationships to check that the recorded shear sonic is a good shear curve and is not a mud wave or Stoneley wave velocity produced by bad processing of the sonic waveform data. The measured DT compressional and DT shear sonics are entered. Equivalent velocities are generated as well as the Poisson ratio and Vp/Vs ratios. The input units for the slowness curves and the output units for the velocity curves can be set by the user. The Poisson ratio is calculated as follows:

Vp 2 − 2Vs 2 ν= 2 Vp 2 − Vs 2

(

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The default Z-axis curve, which is optional, is the gamma ray. When Run is clicked, a crossplot of Vp versus Vs is displayed. The crossplot contains the overlay lines set by the Lithology Lines box. The overlay lines are created each time the user clicks Run. These lines represent the relationships setup on the Create DT shear tab. Changing the coefficients for the relationships will change the lines on the crossplot but only when a new crossplot is run. A crossplot interval can be set by either specifying the depths or by specifying a zonation set and zone number. The following crossplot displays a good quality shear sonic. The relationship between Vp and Vs shows the Greenberg-Castagna relationships for sand and shale.

Quality control the shear sonic created in the previous exercise. 1. From the DT Shear window, click the DT Shear QC tab. 2. For the Input Curves DT Compressional, DT Shear and Crossplot Z axis select DTLN, DTS and SGR. 3. Use the defaults for the output curves. 4. In Units should be set to uSec/ft. 5. Select the Shale and Sand for Lithology Lines. 6. Output Units should be set to ft/sec. 7. For the Crossplot Interval, select Zonal Depths, the clay volume for Interactive Petrophysics Advanced 12/30/04

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Fluid Substitution the Interval Set and 4 selected for the Zone. 8. Click Run and the crossplot should appear. 9. Select all zones to view all data points. 10. Close the crossplot window and the DT Shear window.

Calculate the Fluid Substitution NOTE: For this lesson you will need to create a Top Set called Fluidsub with the following zones; Top Gas 7776-7922.5, Water 7922.5 – 8240.5, Bottom Gas 8339 – 8464 and Bottom Water 8464-8632.

1. From the IP main menu, select Interpretation > Rock Physics > Fluid Substitution. 2. Click the Fluid Properties tab.

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3. In the Reservoir Pressure and Temperature box, enter 200 for the temperature and 6000 for the pressure. 4. Select Deg F for the temperature units and PSI for the pressure units. 5. In the Water box, enter 38861 for the Salinity ppm NaCL. 6. Select the Gas Saturated water radio button. 7. Click the Calculate button. Notice the Brine column populates in the Fluid Properties Results box. 8. In the Oil box, enter 35 for the API, 0.8 for Gas Density. 9. Toggle Gas Saturated to ON. 10. Select ScuFt/bbl for the units. 11. Click the Calculate button. Notice the Oil column populates in the Fluid Properties Results box. The GOR box will also display 1781.6, this is the calculated GOR assuming a gas-saturated oil. 12. In the Gas box, enter 0.8 for the Gas Density. 13. Click Calculate. Notice the Gas column populates in the Fluid Interactive Petrophysics Advanced 12/30/04

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Fluid Substitution Properties Results box.

14. Click the Reservoir button on the blue View Properties box. The Fluid properties box will now display the fluid properties for the reservoir zone (the zone away from any wellbore influence). 15. Click the Calculate buttons for the Water, Oil and Gas sections to populate the fluid properties for the reservoir zone. We will be assuming that the fluid properties for the flushed zone and the reservoir zone are similar. 16. Click the Input Curves/Matrix tab.

17. Select DTLN for the DTp/Vp Compressional, DtsEmp for the DTs/Vs Shear, RHOB for the Bulk Density, PHIE for the Porosity, SW for the Water Saturation and SXO for Sxo Saturation. 18. The Display Velocity units box should be set to ft/sec. 19. Set the Sonic Input Type and Units set to DT usec/ft. 20. In the Matrix Properties, on the mineral row, select Quartz in the first cell and Wet Clay in the second cell. Use the default values for Density, Modulus and Velocity. 30

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21. In the Input Curve row, select VWCL for the Wet Clay and select Default Mineral for Quartz. 22. Click the Average Gassmann tab.

23. Select Zonal Depths in the Zonal Log Average box. 24. From the Top Set drop down box, select the Fluidsubs and 1 for zone. 25. Click Calculate Averages. 26. In the Fluid Substitution box, select Oil/Brine.

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27. Click the Fluid Substitution Crossplot and observe the crossplot produced.

28. Close the crossplot and click the Discriminators tab. Here discriminators can be setup to be used in the calculation. For this exercise we will leave them blank.

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29. Click the Log Fluid Substitution tab.

30. In the Actual Reservoir fluid type seen by Sonic/Density box, click in the Oil box. 31. Make sure Interval Depths is selected in the Analysis Interval box. 32. Click the Run button.

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Fluid Substitution

33. Click the Log Plot button. Notice the results plot in the Log Plot.

34. Close the log plot and the Fluid Substitution window.

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Chapter 5 Elastic Impedance What is Elastic Impedance? Elastic Impedance (EI) is the generalization of acoustic impedance (AI) for variable seismic incidence angle. For zero-offset incident angle, AI can be computed directly from the well logs, however the far-offset incident angle stacking data requires a different approach. This Elastic Impedance module uses the equation proposed by P. Connolly (1999):

Based on this equation, it was found that there is little difference between the low angle equation and the high angle equation for angles below about 20°. But for angles above 30° the low angle equation starts to become unstable.

NOTE: For more detailed information about the Elastic Impedance module, please access the Help guide from the Interactive Petrophysics software.

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Elastic Impedance

Calculate the Elastic Impedance 1. From the IP main menu, select Interpretation > Rock Physics > Elastic Impedance. 2. In the Input Curves box, use the default curves as inputs and for the Velocity Curve Units select ft/sec. 3. In the Results Elastic Impedance Curves box, select EI_ for the Base Name. 4. Enter 10, 15 and 20 for the Angles to process. 5. In the K constant box, enter 7940.5 for the top depth and 8179 for the bottom depth. 6. Click the Calculate ‘K’ from interval button.

7. Click OK to the “Calculate ‘K’ curve : EI_Kconst?” pop up window.

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Elastic Impedance

Schlumberger

8. Leave the Normalize to AI curve box unchecked. 9. In the Intervals box, leave the selection to Interval Depths. This computes the EI from top to bottom depth. (Or you may wish to use the Zonal Depths :Fluidsub which computes only the EI for those zones). 10. Click Run. 11. Click the Log Plot button and select New Log Plot. View the log plot.

12. Leaving the Log Plot open, go back to the Elastic Impedance setup window and in the EI Normalization box, enter 7710.5 for the Log Depths to normalize EI curves to AI curve. 13. Check the Normalize to AI curve box. 14. Click Run to recalculate the EI curves. Notice that now all the EI curves have been shifted so that at 7710.5 they read the same value. 15. Close the Log Plot window and the Elastic Impedance window. REFERENCE: Interactive Petrophysics Advanced 12/30/04

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Elastic Impedance Interactive Petrophysics User Guide. Interactive Petrophysics Training Notes., PGL.

Boucher, Kyle., The Monte Carlo Error Analysis and Quantifying Interpretation Result in Interactive Petrophysics, 2003., SIS the Click Support Newsletter. Monte Carlo – Log Analysis., a white paper developed by PGL.

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