RockSI TutorialTutorial outline Introduction RockSI software overview Part 1: Log Analysis Part 2: Rock Physics Template (RPT) Part 3: Creation and calibration of userdefined PEMs Part 4: Uncertainty analysis using Monte Carlo simulations Part 5: LithoSI analysis using simulated PDFs May 2015 2 Introduction Rock Physics: the interdisciplinary glue Petrology Mineralogy Coring Stratigraphy Geology Logging Petrophysics Structural Geology History Matching Reservoir Modeling May 2015 Rheology Reservoir Engineering Flow Simulation Gravity Geophysics Electro Magnetism Seismic 4 . pseudo-well creation Part of petrophysical inversion Stochastic: Augmentation of litho-classification training sets through Monte Carlo simulations Uncertainty analysis Time-lapse feasibility studies Trend modeling Inverse Rock Physics Transforms May 2015 5 .Rock Physics: Applications Interpretation and Quality Control: Well logs Inversion results Predictions: Deterministic: Logs prediction. These terms are: the Rock Physics Model (RPM) the Petro-Elastic Model (PEM) the Rock Physics Template (RPT) In the following slides we will define these three terms. and their display are Rock Physics Templates ( RPTs). In the RockSI program. or PEMs.Rock Physics: some definitions Note that there are a number of terms used in the creation of rock physics models that are almost synonymous. we will mainly be concerned with the creation of Petro-Elastic Models. May 2015 6 . and this tuorial. but have slightly different meanings. : Change of pressure (seismic waves) Change of temperature Electric/magnetic current May 2015 7 . is a model which describes how a rock react to a given stimulus.Rock Physics Model (RPM) A Rock Physics Model. or RPM.g. e. The elastic response mainly depends on: Rock composition (minerals and fluids) Rock texture (spatial distribution of minerals and porosity) May 2015 8 . or PEM. is a model which describes how a rock reacts to seismic waves.Petro-Elastic Model (PEM) A Petro-Elastic Model. Petro-Elastic Model (PEM) A PEM is comprised of a set of equations which model the elastic response of a rock from its petrophysical properties. The PEM is an important link between the well and seismic data. Porosity Sw Lithology PEM Vp Vs Density SEISMIC WELLS May 2015 9 Rock Physics Template (RPT) A Rock Physics Template, or RPT, is the projection of a Rock Physics Model in a particular N-dimensional space: Type of pores Change of P-Impedance due to gas injection (ΔSG = +0.6) May 2015 Cracks Intergranular Vugs 10 RockSI Overview May 2015 Input QC and display 12 .RockSI: Overview The RockSI program has two main windows with tabs: on the left is the input menu and on the right is the QC display. RockSI: Overview The RockSI program has two main windows with tabs: on the left is the input menu and on the right is the QC display. May 2015 13 . SIModels . 3.Wavelets Select rock types and PEMs. Select the input data: . 2.Seismic (Angle Stacks) . Create tie point for each well in depth (TVD) vs time (TWT). 4. 1 2 3 4 May 2015 14 . Create tables showing the correspondence between PEM variables and well logs or model attributes.Wells (in Depth or TWT) .RockSI: Overview The Input tab allows the user to: 1. Read-Only to see the content of the PEM .The ability to load existing models . 2.Parameters editing to edit the value of the internal parameters of the PEM .Access to standard models 1 2 The definition of each PEM: .RockSI: Overview 3 The PEM Library tab allows the user: 1. Three editing modes: .Advanced editing to modify the input/output and equations of the PEM May 2015 15 .Output variables with associated equations 3.Input variables .The ability to create new models . A list of available Petro-Elastic Models: . RockSI: Overview The variables tab gives: 1. Variable unit used in the Cross-Plots tab May 2015 16 . 2. Variable colormap used in the Log Viewers and Cross-Plots tabs 4. 1 2 3 4 A list of variables: any variable with a valid name is available for use in PEMs and QCs Default list User-defined if more variables are needed. Variable display limits used in the Log Viewers and CrossPlots tabs 3. temperature and fluid composition May 2015 17 .RockSI: Overview Fluids tab: Fluid property computation: Density Velocity Bulk modulus Based on Batzle & Wang equations Brine. oil and gas properties as a function of pressure. Selection of PEM used in Monte Carlo simulation 2. Definition of the input distributions and correlations 3.RockSI: Overview 1 2 Simulation tab: 1. Simulated correlations 4. Export of simulated data as ASCII file or xsel file used for lithoclassification (LithoSI) 3 4 May 2015 18 . Curve display options 2 2. Log table (selection of variables not the actual logs defined in the Input tab) 3 3.RockSI: Overview Log Viewers Options tab: Definition of the display template in the Log Viewers tab: 1 1. Angle Stack table (selection of keywords not the actual stacks defined in the Input tab) May 2015 19 . 1 RockSI: Overview 2 Cross-Plots Options tab: 1. Graphical options for the display of RPTs from the PEMs defined in the PEM Library tab 3. Graphical options for the display of the data simulated in the Simulation tab May 2015 3 4 5 6 20 . Definition of the display template in the Cross-Plots tab 2. Filters to apply on the cross-plots 4. Graphical options for the display of the predicted logs 6. Graphical options for the display of the data selected in the Input tab 5. RockSI: Overview Log Viewers tab: Logs and seismic traces display for each well selected in the Input tab (template defined in Log Viewers Options tab) May 2015 21 . RockSI: Overview Cross-Plots tab: Cross-plot display (template defined in Cross-Plots options tab) May 2015 22 . Load session 2. Save session 3. Create a new PEM 1 2 3 4 5 6 4. Update all the current QCs May 2015 23 .RockSI: Overview Menus/Toolbars: 1. Load an existing PEM 5. Save a PEM 6. Part 1 Log Analysis . fluid type Petrophysical and elastic properties May 2015 25 .Data interpretation and QC QC and interpret log data through templates: Rock type. Those tasks are not strictly talking part of the rock physics modelling but are a preliminary work that will ease the modelling task. Understand the impact of each of those variables. May 2015 26 .Part 1: Log Analysis This first exercise will guide the user through the following tasks: Identify the different lithologies encountered at the wells. Identify the main petrophysical variables that impact the rock elastic response. the first window that you see contains a list of any projects previously opened in Geoview. May 2015 27 .Part 1: Log Analysis Start the HRS10 Geoview program by clicking Geoview icon on your desktop: When you launch Geoview. Your list will be blank if this is the first time you are running Geoview. we will set all the data paths to point to the location where we have stored the workshop data. in the File Selection Dialog.Part 1: Log Analysis For this exercise. click the Settings tab: To change all of the directories to the same location. click on the option Set all default directories and then click the button to the right: Then. To do that. we will start with a prepared project. Before doing that. select the folder which contains the workshop (check with the instructor the folder location): May 2015 28 . the Geoview window will now show the selected directories (note that yours may be different): When you have finished setting all the paths. click Apply to store these paths: May 2015 29 .Part 1: Log Analysis After setting all three paths. Click Find Project: Select the project RockSI. Click OK to open the project: May 2015 30 .Part 1: Log Analysis Go to the Projects tab.prj. Part 1: Log Analysis Now the GEOVIEW window looks like this: In the project manager. May 2015 31 . there are four preloaded deviated wells. For example. Click on that tab to see a list of all the operations which are available in Geoview. Each of the processes can be expanded. if you click on the PetroElastic Modeling (RockSI) option and the RockSI option . You will see that one of those tabs is called Processes.Part 1: Log Analysis First. look at the tabs to the left of the GEOVIEW window. the following expanded list is seen: May 2015 32 . some data may already be loaded. On the right side of the window. (Note that depending on the project itself.Part 1: Log Analysis Double click on New RockSI Session: A new tab called RockSI is created in the GeoView window: On the left of the RockSI window are a series of tabs for data control. May 2015 33 . there are two tabs for displaying the Log viewer and Crossplot window. but we will re-do the loading). as well as the synthetic trace shown in red at the far right hand side of the plot. May 2015 34 . select the four available wells by clicking Select All Items button. In the seismic table. add two new lines by clicking the + sign button twice. This will select all four wells and create a QC display automatically in the Log Viewers tab for each of the wells.Part 1: Log Analysis Under the Input tab. Also note that three logs have already been selected. select the wavelets that have been previously extracted from the corresponding seismic volumes: Wav_10_1. Wav_30_1. Select each of the seismic volumes under the column Seismic by left-clicking on the down arrow and selecting the files Amp_10. Specify the Angle for each seismic volume (10. there are 3 angle stack seismic volumes at 10. 30). 20. which will be automatically displayed in the Log Viewers window. Click the Update QCs button at the top of the dialog. Wave_20_1. Specify the Amplitude as Seismic. 20 and 30 degrees. Finally. May 2015 Update QCs 35 .Part 1: Log Analysis For this exercise. Amp_20 and Amp_30. Synthetic Extracted seismic Note that well-seismic ties were performed prior to running RockSI. it shows the extracted seismic traces in black from each of the seismic volumes. the good match between synthetic and extracted seismic. the Log Viewers window on the right side of the RockSI window will look like this: As mentioned before. May 2015 36 .Part 1: Log Analysis After selecting the well and seismic data. The red line is the calculated synthetic trace using the logs and wavelet. On the right of the Log Viewers window. Hence. three logs are now displayed. VpVs. You can do that by clicking on the ‘+’ button a few times to add the following variables. Any extra row can be removed by clicking the ‘-’ button. Sw. Ip. Vqz and Facies. May 2015 37 . Phi. Proceed to add: Vsh.Part 1: Log Analysis We will add a few variables for QC purpose. Part 1: Log Analysis Next we need to map the variables to the actual log curves. This table will automatically display the input variables required by the Petro-Elastic Model (PEM) selected in subsequent steps. May 2015 38 . QC Variables are mainly used in various QC plots. Specify the variables and log curves mapping as shown. Click on the “Replicate selection to other tabs” button to apply the changes to all the well tabs. Input Variable table by default list P-wave(Vp). In each of the well tab. S-wave (Vs) and Bulk Density (Rho) variables. there are Input Variable and QC Variable mapping tables. and water saturation (Sw) for the top three logs in the well log table. Vs and Rho.Part 1: Log Analysis Click on Log Viewers Options tab. May 2015 39 . Highlight the first row and click on the + sign to add three rows. Select Shale volume (Vsh). porosity (Phi). We also want to color-code these logs by selecting them under the Color column. Change the logs in these new bottom three rows to Vp. Click on the Update QCs button and see the new display in the next slide.35. We can also change the color scheme by clicking on the color Palette and select the desired color scheme. Here. May 2015 40 . we will keep the default selection.Part 1: Log Analysis We can optimize the well log display in the General Options tab: Update the Max value for the porosity log type to 0. Part 1: Log Analysis Three newly added logs are shown on the left of the Vp track. May 2015 41 . Click the Update QCs button.Part 1: Log Analysis Click on Cross-Plots Options tab. May 2015 42 . Select the logs for the X and Y axis. The Cross-plot window will appear on the right. Display legends turns on/off of the color keys on the plots. May 2015 43 . then click on Replicate current value to apply to the other cross plot. One option of the filter is to limit the number of points which by default is 100. We can also select the wells of our interest only.000. The number of points are randomly selected from these 4 wells.Part 1: Log Analysis Select Vsh to color code the crossplot. From the figure. May 2015 44 . The red points have a higher volume of clay (shale). The shale lithology can be easily identified by the cluster of red points as pointed by the arrow. we can clearly see that the porosity decreases with increasing Vsh.Part 1: Log Analysis The right of the RockSI window shows the cross plot of the selected wells. while the blue points have a lower volume. Part 1: Log Analysis Repeat previous steps to display the effects of volume of quartz (Vqz). The sand is now identified on the opposite side from the Vsh case. as shown by the arrows May 2015 45 . Vcoal (Coal Volume) … etc. May 2015 46 . Vcalc (Calcite Volume). the high porosity clusters roughly correspond to the sand as pointed by the arrows. We can check additional properties like: Sw(Water Saturation). Again.Part 1: Log Analysis Repeat for Phi (Porosity) as the variable used to color-code each of the cross-plots. First we will define a series of Facies by clicking on Define Facies Classification from the process list in the project manager. we will either read in or create a Facies log for each well to specify the associated rock type for each sample. click on the Load button: May 2015 47 . On the dialogue that appears.Part 1: Facies Logs Next. If you can’t find a facies xml file. skip the next slide.Part 1: Facies Logs Then. in the file chooser that appears. May 2015 48 .xml and select it and click Open. locate the file Facies. Part 1: Facies Logs When the facies xml file is loaded. Oil and Calcite facies: Then. May 2015 49 . it will look like this. with Coal. click OK. Shale. Sand. select Project Data / Well / well A and see if one of the logs is called FACIES. as shown on the right.Part 1: Facies Logs Next we want to find out if the four wells contain facies logs. May 2015 50 . To do this. and D also. Check wells B. C. and click the + sign to create a new row. May 2015 Click here before the + sign 51 . Click on the first line in the log viewer table. Select Facies to display and the Facies as color-coding variable.Part 1: Facies Logs Go to the RockSI window and click on the Log Viewers Options tab. select Facies for the Property Type. Click the color palette and select Facies. Specify 0-7 for min-max range. May 2015 52 .Part 1: Facies Logs Go to the General Options tab. Click on the + sign to add a row at the bottom of the table. we can see a strong reflection at this interface. We can also check the other wells by clicking those well tabs. we can see clearly that the Facies log is closely related to the other color coded logs (Vsh.Part 1: Facies Logs Now the Facies log is displayed on the first track of the log viewer window. By tracking the curser position. May 2015 53 . Phi. From the figure. it is the Oil sand and Shale interface. At depth of 1930 m. Sw and Vp). May 2015 54 . Select Facies as the variable used to color-code each of the cross-plots. The cross plot windows now look like this.Part 1: Facies Logs Click on Cross-Plot Options tab. The color key of the Facies displayed is the color of the five facies we have just defined. Part 2 Rock Physics Template (RPT) . needles.Different types of effective medium models Empirical models: Gardner Greenberg-Castagna Effective Medium models: Granular models: Pack of spheres with interstitial porosity Used to model high porosity rocks such as unconsolidated and lightly cemented sandstones Inclusion models: Background and inclusions (spheres. penny cracks): Self-consistent model (SC) Differential effective medium (DEM) Used to model low permeability rocks such as tight sandstones and carbonates May 2015 56 . Soft (unconsolidated) sandstone model Pack of identical smooth spheres Porosity filled by a single phase May 2015 Real rock Model Multiple mineral types Multiple fluids Complex texture Effective grain Effective fluid Simple texture 57 . Soft (unconsolidated) sand model Effective matrix: mix of Quartz and Clay 1 M matrix Vclay M clay 1 Vclay M quartz 2 ρmatrix Vclay ρclay 1 Vclay ρquartz 1 Hill average 1 Vclay Vclay 2 M clay M quartz ρ fluid SW ρW SO ρO SG ρG Effective fluid: K fluid May 2015 1 SW SO SG KW K O K G (Wood equation) 58 . Soft (unconsolidated) sand model Effective frame: C 1 φC G K HM 2 18π 1 PR 2 GHM 2 2 matrix 2 matrix Peff 1 3 2 2 5 4 PRmatrix 3C 2 1 φC Gmatrix Peff 2 2 52 PRmatrix 2π 1 PRmatrix K dry 1 φ φC 1 φ φC 4 4 K HM GHM K matrix GHM 3 3 φ φC G G 9 K 8GHM GHM HM HM 6 K HM 2GHM May 2015 1 3 (Hertz-Mindlin model) 4 GHM 3 1 1 φ φC G 9 K 8GHM Gmatrix HM HM 6 K HM 2GHM GHM 9 K HM 8GHM 6 K HM 2GHM 59 . Soft (unconsolidated) sand model Combination of frame and fluid: 2 K dry 1 K matrix K B K dry K dry 1 K fluid K matrix K matrix2 (Gassmann equation) Elastic attributes: fluid 1 matrix VP VS May 2015 4 KB G 3 G 60 . Unconsolidated sand model D Modified Voigt Unconsolidated Sand PHI C B A SG D May 2015 C B A 61 Part 2: Rock Physics Template (RPT) In the previous exercise, we used volume logs to interpret the different lithologies. When the volume logs are not available, we can use the standard Petro Elastic Models (PEMs). You can also create a new PEM with your own equations. In this next exercise, we will learn how to display Unconsolidated Sand RPT using one of the predefined PEMs. Also see how we can display these RPT on standard GEOVIEW crossplots. Go to the PEM Library tab. Right click on the PEMs item and select the Load PEMs. May 2015 62 Part 2: Rock Physics Template (RPT) A number of published models are included in RockSI. Click different tabs to review them. Select the Unconsolidated Oil Sandstone model To see the full documentation of this model, click the Information Icon. May 2015 63 Part 2: Rock Physics Template (RPT) This brings up the documentation for the Unconsolidated Oil Sandstone model as shown on the right. May 2015 64 . May 2015 65 . then close the dialog.Part 2: Rock Physics Template (RPT) Click Apply to load the Unconsolidated Oil Sandstone PEM. we can see a list of reservoir conditions.Part 2: Rock Physics Template (RPT) After loading the sandstone PEM. Click the Advanced toggle to change to full editor mode. May 2015 66 . mineral and fluid properties. Part 2: Rock Physics Template (RPT) In Advanced editing mode. you can modify the relationships. parameters or define new variables as needed. We will not make any changes to the PEM in this exercise. May 2015 67 . It requires the FACIES log curve and Classification table to be specified. it will be useful to limit the crossplot QCs to show only sandstone facies. May 2015 68 . Scroll down to well tabs parameters section. In the Input tab. select the option Several rock types and the Facies table imported in previous exercise as the rock classification.Part 2: Rock Physics Template (RPT) Before display the unconsolidated sandstone RPT. click the Replicate Icon to select the same log curve for the other three wells. May 2015 69 .Part 2: Rock Physics Template (RPT) Specify the FACIES log curve for Well A. Then. Then click the Update QCs icon. Toggle on Display only rock type and select Sand. modify the first crossplot to show Vp vs Rho. May 2015 70 . The plots now show data points for only the Water Sand.Part 2: Rock Physics Template (RPT) In the Cross-Plots Options tab. 5. We need to specify the Facies classification and the range 2.5 to 4.5 May 2015 71 . Also. Range: 2.5-4. we will use the Display only range option.Part 2: Rock Physics Template (RPT) To display both Water Sand and Oil Sand facies. the Display only Rock Type option must be unchecked. Part 2: Rock Physics Template (RPT) We are now ready to display the RPT. we are modelling 100% Oil saturation. Fill in the PEM parameters as shown in the table. Main graduation: Phi and check Secondary Graduation and select Vsh. May 2015 72 . Go to the CrossPlots Options tab Select PEM Unconsolidated Oil Sandstone. With Sw= 0. 35 and Vsh between 0 and 0.1 and 0.4. Meshes are displayed in the plots that represent the Oil sandstones with Phi between 0. May 2015 73 .Part 2: Rock Physics Template (RPT) The soft sandstone template is as shown in the crossplot window. Part 2: Rock Physics Template (RPT) Set Sw to 1 to model the water sand. May 2015 74 . Part 2: Rock Physics Template (RPT) Observe that the meshes now match the water sand. You can model any combination of two parameters in the table with ranges. May 2015 75 . You can control how often the increments of the mesh without recalculating the RPT.Part 2: Rock Physics Template (RPT) The color of the RPT can be changes by clicking on the color selector icon. Click the Palette Icon to bring up the Viewer options. May 2015 76 . Click Close. May 2015 77 . Next we will use the GEOVIEW standard crossplot tool.Part 2: Rock Physics Template (RPT) Click Save current session to save your work in RockSI. . We will start by creating a standard VpVs vs P-impedance crossplot in GEOVIEW.Double click Cross Plot Logs May 2015 78 .Part 2: Rock Physics Template (RPT) The same RockSI PEM/RPT can also be displayed in the standard Hampson-Russell Crossplot tool. It requires a license of RockSI to enable the option. .Go to the Processes tab.Expand the Cross Plotting folder . well_A .Part 2: Rock Physics Template (RPT) In this example. Click OK. we will only use Well A to demonstrate the steps. Make the following selections: -Single Well .Vp/Vs vs P-impedance We will use all data. May 2015 79 . On the menu bar.Part 2: Rock Physics Template (RPT) A crossplot similar to the one on the right will appear. May 2015 80 . click Options and select “RPM and PEM…” Note that this require a RockSI license. See the picture for various ways to access PEM.Part 2: Rock Physics Template (RPT) The PEM parameters dialog will appear as shown on the right. May 2015 81 . Any PEM created in RockSI can be used in this Crossplot tool. May 2015 82 .Part 2: Rock Physics Template (RPT) The Unconsolidated Oil sandstone PEM should readily available for use since we previously loaded it in RockSI. Select Unconsolidated Oil Sandstone. we are modelling 100% Oil saturation.Part 2: Rock Physics Template (RPT) Fill in the PEM parameters as shown in the table. May 2015 83 . With Sw= 0. Part 2: Rock Physics Template (RPT) RPT of Unconsolidated Oil Sandstone is now displayed in the crossplot. Any dynamically created models in RockSI can be posted on standard GEOVIEW crossplots to guide seismic and well logs interpretation. May 2015 84 . Click the Cross Plots icon in the lower right hand corner to dock the window. Part 3 Creation and calibration of user-defined PEMs . Part 3: Creation of Petro Elastic Models In this exercise. you will create or import a Petro Elastic Model (PEM) for each of the previously determined lithologies. The quality of the modelling will be tested by comparing the model predictions with the actual logs both in 1D viewers and cross-plots. May 2015 86 . Part 3: Geological context Lithostatic Pressure (MPa) Pore Pressure (MPa) Effective Pressure (MPa) 0 10 20 30 40 Temperature (°C) 50 0 10 20 30 40 50 0 Sea Water ρ = 1g/cc 500 9.4 15.4 12 May 2015 Gradient = 30°C/km 1500 27 26.1 4 Reservoir ρ = 2.25 g/cc 10.5 g/cc 35.8 1000 Overburden ρ = 2.5 24.9 11.5 33 Depth (m) 45 2000 38 49 2500 Depth (m) 87 . 01 kg/L Gas-Water ratio: 0 L/L Oil gravity: 30 API Gas-Oil ratio: 50 L/L Gas gravity: 0.6 May 2015 88 .Part 3: Geological context Fluid Parameters: Temperature: 35 °C Lithostatic Pressure: 30MPa Pore Pressure: 20 MPa Brine Salinity: 0. That should be enough to demonstrate how it can be done. Instead of building a full PEM. May 2015 89 .Part 3: Creation of PEMs In this exercise. (Optional) Create a user defined PEM to model Shale. Vs and Rho. The predicted curves can be visually compared with the measured curves. we will only build it up to modelling bulk density. we will: 1. 2. Then proceed with importing a PEM for each lithofacies and use these PEMS to predict elastic properties: Vp. Click Yes to delete the PEMs. Right click on the PEMs item and select Create New PEM. May 2015 90 . Right click on the PEMs item and select Delete all PEMs.Part 3: Creation of PEMs Click the PEM Library tab. Toggle the Advanced button. May 2015 91 .Part 3: Creation of PEMs Right click on the newly created PEM and select Rename PEM. Name this PEM as Shale and click Ok. Set Facies as the color-coded variable for the crossplots if it is not already set. May 2015 92 .Part 3: Creation of PEMs Go to the Cross-Plots Options tab. toggle off Display only Range and toggle on Display only rock type with shale selected. Part 3: Creation of PEMs We have seen in Exercise 1 that the main variables affecting the elastic response of the shale are Vsh. May 2015 93 . Click on PEM Library tab. Depth (True Vertical Depth) and Pp (pore pressure) respectively. Phit. Pay attention to ensure that proper units are specified. add three new lines in the input table of the Shale tab by clicking on the Add Line Below button. Select Vsh. Phit (total porosity) and the effective pressure Peff . Peff is derived from Depth when Pp is known.25*(Depth 1000) / 1000) Pp Input parameters Click the Arrow sign to see a list of Input parameters. In many cases.Part 3: Creation of PEMs Select Peff as the Output Variable. and MPa as the unit. which we will use for writing the equations.81* (1 2. May 2015 Math operators Precompiled equations 94 . Math operators and precompiled equations. Effective pressure in our case is given by the following equation: Peff 9. May 2015 95 . Click the arrow sign beside the equation box and select Depth. Type in the rest of the equation and select the variable Pp.Part 3: Creation of PEMs Type in part of the equation as shown on the right. Next we will select the variable Depth. Salinity. Gas/Water Ratio. and five different densities: A red cross will now appear after the PEM name.Part 3: Creation of PEMs The final equation to calculate Peff looks like this: If you have entered the equation correctly. Select the output variables as shown (notice that the new Variables are Temperature. a green check mark will appear after the PEM name. indicating that the equations must be filled in: May 2015 96 . Add eight new lines by clicking on the Add Line Below button. Part 3: Creation of PEMs We will start with the modelling of the shale density as this is the easiest elastic attribute to model. The density is given by the following volumetric averages: Rho Phit*Rhow 1 Phit *Rho ma Rho ma Vsh*Rhosh 1 Vsh *Rhoqz We will use 2.65 for the quartz density and the shale mineral density is given as a function of the effective pressure: Rhosh 2.43 0.02*Peff The water density can be calculated using Batzle & Wang equation as a function of: Temperature [°C] We will assume a temperature gradient as shown earlier: May 2015 Pore Pressure [MPa] Salinity [kg/L] Gas-Water ratio [L/L] T 4 30*( Depth 1000) / 1000 97 Part 3: Lithofacies PEMs Next, we will create PEMs for each of the lithofacies defined earlier. For example, the shale PEM is created using the following equations: w 1 m where : m Vsh sh 1 Vsh qz and sh 2.43 0.02*Peff . May 2015 98 Part 3: Creation of PEMs The Batzle & Wang equation for brine density is quite complex and it has already been precompiled. Click the arrow sign beside the equation box for the fifth row (Rhow), and select Precompiled Equations->Brine density (Batzle Wang). On the menu, we can also see a list of other pre-defined equations. May 2015 99 the green check mark will appear again. May 2015 100 . If you fill in the equations correctly.Part 3: Creation of PEMs Enter the equations for the rest of the output variables as shown. Make sure the units of the input variables and output variables are correct. See next slide for a description of the variables involved. Part 3: Creation of PEMs Vsh – Volume of Shale Phit – Total Porosity Depth – True Vertical Depth Pp – Pore Pressure Peff – Effective Pressure T– Temperature Sal – Salinity GWR – Gas Water Ratio Rhow – Brine Density Rhoqz – Quartz Density Rhosh – Shale Density Rhom – Rock Matrix Density Rho – Bulk Density May 2015 101 . TVDSS (true vertical depth). and select Shale for the Petro-Elastic Model for the Rock Type shale. PHIT (total porosity). Click Replicate Icon to select the same logs for other wells. and PP (pore pressure).Part 3: Creation of PEMs Click the Input tab. Click Update PEM predictions Icon to calculate the predicted logs May 2015 102 . Specify the mapping of input variables to their corresponding log curves: VCL (clay volume). The match of the two logs are quite good.Part 3: Creation of PEMs You can see the predicted density in the Log Viewer of each well. The predicted density (red) for Shale facies (Brown color facies) is now overlaid on top of the measured density (black). May 2015 103 . The predicted density (red) for Shale facies and measured density in brown (colored by facies). You can uncheck the Predictions to see measured density.Part 3: Creation of PEMs You can see the predicted density overlaid with measured values in the crossplot QCs as well. May 2015 104 . Part 3: Creation of PEMs Now that the density is correctly modeled.5*(Vsh*Ksh 1 Vsh *Kqz) 0. the effective pressure and the total porosity: G 0.5 /(Vsh/Ksh ( 1-Vsh)/Kqz) Gma 0. we will need the bulk modulus and shear modulus of the rock to calculate the P-wave and S-wave velocities. We will use 25 and 9 for the shale bulk and shear modulus respectively.36*Peff 90*Phit/Peff 10 Keff 0.2*Gma 1. The modulus of the saturated rock can be computed as a function of the mineral modulus.3*Kma 1.5*(Vsh*Gsh 1 Vsh *Gqz) 0. The modulus of the mineral can be computed with a simple Hill volumetric average: Kma 0.5 /(Vsh/Gsh ( 1-Vsh)/Gqz) We will use 37 and 45 for the quartz bulk and shear modulus respectively.8*Peff 210*Phit/Peff 8 May 2015 105 . Part 3: Creation of PEMs Now that we have modelled the bulk, shear modulus and density of the shale formation, we have all the input needed to compute its P-wave and S-wave velocities: VP VS G Rho Because those equations are used very often, they have been precompiled in the software and can be used through the following keywords: 4 Kb G 3 Rho VP_WAVE_PROPAGATION_EQ VS_WAVE_PROPAGATION_EQ. You can continue to enter equations and variables to build a full PEM to predict Vp and Vs for shale. Now that you have some experience on building a PEM, we will stop and simply import a number of prebuilt PEMs instead. May 2015 106 Part 3: Creation of PEMs Click the PEM Library tab. Right click on the PEMs item and select Delete all PEMs. Click Yes to delete the PEMs. Toggle on the Advanced button. Right click on the PEMs item and select Load PEM(s). May 2015 107 Part 3: Creation of PEMs On the Load PEM(s) dialog, click the Folder Icon. May 2015 108 Note that water and oil sand use the same model. On the Load PEM(s) dialog. You should find five files with “. Sand (Water sand). Click Open to select them.pem” extension. Coal. We separated them so that it will be easier for comparing simulation results later. Oil (Oil sand) and Shale. Select Calcite. May 2015 109 .Part 3: Creation of PEMs Go to the same directory where the RockSI project resides. Click Apply to import them. Part 3: Creation of PEMs The PEM Library tab should now show four PEMs available for use. You can review the equations and parameters defined in each PEM. The Shale PEM is named Shale #1 since we had one defined previously. May 2015 110 . Go to the Input tab. Rho. Specify the associated PEM for each Rock Type. Ip and Vpvs selected.Part 3: Creation of PEMs With all the necessary PEMs available. Use the + sign to add new variables. Make sure the Output Variable table has Vp. Scroll down to the Well Tabs. Vs. we are ready to use them for predicting Vp. Vs and Rho for all facies. May 2015 111 . specify the log curves as shown for each table. click on Update PEM predictions Icon to generate the log curves. Lastly. May 2015 112 . Click through all the wells to confirm the selections.Part 3: Creation of PEMs For Well A. Make sure you click the Replicate Icon for each table to ensure the selections are applied to the other three wells. Part 3: Creation of PEMs In the Log Viewers tab. Vs and Rho (red) overlay with their associated measured curves (black). you should see the predicted Vp. You may need to use the horizontal scroll bar to scroll to the right in order to see the results. The angle synthetics are also generated based on the predicted curves. May 2015 113 . Uncheck Display only rock type filter.Part 3: Creation of PEMs Click on the Cross-Plot Options tab. Predicted values are in red and measured values are colored by facies. May 2015 114 . Go to the Cross-plot tabs to see the crossplot QCs. Part 3: Creation of PEMs Click the Save session button to save the current parameters and QC templates. May 2015 115 . This concludes this exercise. Part 4 Uncertainty analysis using Monte Carlo simulations . Sg Pore Pressure Overburden Pressure PEM V p f (inputs) f Porosity Clay Volume Rock Model Parameters May 2015 117 . Sh.Uncertainty analysis Sw. Uncertainty analysis Sw. Sg Pore Pressure Overburden Pressure PEM f Porosity V p f (inputs) Output PDF Output Uncertainty Clay Volume Input PDFs Input Uncertainties May 2015 Rock Model Parameters 118 . Sh. Mode.Input Distributions Constant Uniform: Min and Max Normal: Mean and standard deviation Beta (PERT): Min. Lambda (see Annex C for charts) Discrete: Min. Max. Max. Step May 2015 119 . 5 3 5 lambda 7 9 120 May 2015 .5 mode 2 2.Beta (PERT) distribution Parameterization suited to rock physics properties: Min/Max Most likely = mode Shape factor reciprocal of “standard deviation” at mode =1 1. Input Correlations Correlations between the input variables are simulated through the ImanConover technique (see Annex C for more details).7 mX mX X X PX May 2015 Y X PX 121 . Y PY | X PY | X PY PY Y Y|X mY Y mY | X Y|X mY mY | X CC = -0. Y PX . PX . Simulation of scenarios Production effect on elastic attributes: Is water flooding gas out of solution due to depletion shale water-sand oil-sand gas sand May 2015 Ip 122 . Part 4: Monte Carlo simulations In this exercise the user will run Monte Carlo simulations using the PEMs defined in the previous exercise. May 2015 123 . The objective is to make sure that the PEMs reproduce the variability observed in the log data. May 2015 124 . Turn off the display of Predictions result. Set the following cross-plots parameters in the Cross-Plots Options tab.Part 4: Monte Carlo simulations We will start the simulation of the shale. Filter the data to display shale only. Enter the input distributions and correlations as shown. Compare the simulated points with the actual logs. May 2015 125 .Part 4: Monte Carlo simulations Select the Shale PEM in the simulation tab. Total porosity (Phit) is negatively correlated to volume of Shale (Vsh). Launch the simulation by clicking Launch Simulation button. Part 4: Monte Carlo simulations The Shale simulation result looks like this: Measured Data May 2015 Simulated Data With P10. and P90 PDFs contours 126 . P50. LithoSI is a Bayesian Classification software. Enter Shale. Select attribute Ip and VpVs. For the training set name.Part 4: Monte Carlo simulations After the simulation. Remove all output and add two new output attributes. we can select to output a list of petro-elastic attributes as LithoSI training set. Name this training set as Training_Set and click Save. May 2015 127 . it has to be one of the facies we have defined. Part 4: Monte Carlo simulations Now the simulation has been saved. Right click on Training_Set and select View saved session: In the training set file. We can view the simulation results in the saved file. May 2015 128 . we can see that we have three columns including the two output volumes Ip and VpVs and the class of the facies Shale. Check off Shale simulation results. Set the rock type filter to display the water sand only. May 2015 129 .Part 4: Monte Carlo simulations In the Cross-Plots Options tab. Select Phi instead of Phit in the cross-plots. Enter the input distributions and input correlations as shown: Launch the Water Sand simulation by clicking Launch Simulation button. May 2015 130 .Part 4: Monte Carlo simulations Select the PEM Sandstone in the Simulation tab. P50. and P90 PDFs contours May 2015 131 . Compare the simulated points with the actual logs Simulated Water Sand Data Measured Data With P10.Part 4: Monte Carlo simulations The Water Sand simulation result looks like this. Name this training set as Training_Set and click Save. it has to be one of the facies we have defined. May 2015 132 . For the training set name. Enter Sand.Part 4: Monte Carlo simulations Save the simulation result for Water Sand. e. May 2015 133 . we will simulate the Oil Sand. Compare the simulated points with the actual logs. (i.Part 4: Monte Carlo simulations Next. The only difference here is that we are varying Sw with a Beta distribution between 10%-70%. So ranges 30%-90%) Launch the simulation by clicking Launch Simulation button. Set the range filter to display only the oil sand. Modify the input distributions as shown in the table. Compare the simulated points with the actual logs Simulated Oil Sand Data Measured Data With P10. and P90 PDFs contours May 2015 134 .Part 4: Monte Carlo simulations The Oil Sand simulation result looks like this. P50. Change the Training set name to Oil. Select the training set Training_Set and click Save: On the pop-up message. May 2015 135 .Part 4: Monte Carlo simulations Save the simulation result for Oil Sand. click Ok. Set the range filter to display only the water and oil reservoirs. May 2015 136 . Modify the input distributions for Sw and Sg as shown in the table: Launch the simulation by clicking Launch Simulation button. Compare the simulated points with the actual logs. Click to redraw. Compare with the simulated gas reservoir.Part 4: Monte Carlo simulations We can also simulate what would happen if the reservoir was filled by gas instead of oil. May 2015 137 . This is just for comparison purpose. We will not save this result to Training_Set.Part 4: Monte Carlo simulations The Gas Sand simulation result looks like this. There is no need to save this result since we did it previously. Click on Launch Simulation again.Part 4: Monte Carlo simulations Reset simulation back to the Oil case by modifying Sw and Sg as shown on the right. May 2015 138 . Part 4: Monte Carlo simulations Select the PEM Calcite in the simulation tab. Change the Training set name to Calcite. Enter the input distributions and input correlations as shown. May 2015 139 . Launch the simulation by clicking Launch Simulation button. Select the training set Training_Set and click Save. and P90 PDFs contours May 2015 140 . Compare the simulated points with the actual logs Simulated Calcite Data Measured Data With P10. P50.Part 4: Monte Carlo simulations The Calcite simulation result looks like this. Launch the simulation by clicking Launch Simulation button. After the simulation. Enter the input distributions and input correlations as shown.Part 4: Monte Carlo simulations Select the PEM Coal in the simulation tab. Select the output attribute Ip and VpVs: Change the Training set name to Coal. Select the training set Training_Set and click Save: May 2015 141 . and P90 PDFs contours May 2015 142 . P50.Part 4: Monte Carlo simulations The Coal simulation result looks like this. Compare the simulated points with the actual logs Simulated Coal Data Measured Data With P10. Go to Cross-Plot Options tab.Specify corresponding color for each facies May 2015 143 .Uncheck outline for each Simulation .Uncheck pdf for each Simulation .Uncheck Data and Predictions . Reduce to number of crossplots to only showing Ip vs VpVs Set the display parameters as shown on the right: .Uncheck any filters .Part 4: Monte Carlo simulations To see all five simulated facies data. May 2015 144 .Part 4: Monte Carlo simulations This the simulated data for the five facies. In the next excerise we will use these simulated data points as training data set for LithoSI (Bayesian Classification). This concludes Part 4 exercise.Part 4: Creation of PEMs Click the Save session button to save the current parameters and QC templates. May 2015 145 . Part 5 LithoSI Analysis using Simulated PDFs . 2 2.1 2.8 1.1 2.2 1400 2.2 Vp/V 2.3 2.Litho-classification Ip 1600 2000 24001.4 2.0 1.5 2.0 2. V p / Vs ) 1600 1700 1800 1900 2000 2100 2200 2300 2400 2.8 1.0 Compute probability litho-cubes May 2015 P(Class i I p .8 1600 1600 1700 1800 1900 2000 2100 2200 2300 2400 Seismic inversion results Well logs I p Compute multivariate PDFs Vp/V 1.9 1.3 2.4 2.5 2.0 2.9 1.6 1200 2.1 1250 Vp/Vs 1600 1700 1800 1900 2000 2100 2200 2300 2400 s 1300 Extract training sets 1450 1500 1550 2.2 2.3 2.9 1.5 2.5 2.2 2.3 1350 2.0 Oil s Water Gas 0.8 2.4 2.1 2.8 1600 1700 1800 1900 2000 2100 2200 2300 2400 I p 147 .4 2.9 1.0 1. 2 Vp/V 2.1 2.2 2.2 2.4 Gas sand 2.5 2.9 1.0 1.0 1.8 I p Compute multivariate PDFs Vp/V 1.8 1600 1700 1800 1900 2000 2100 2200 2300 2400 I p 148 .8 1.5 2.5 1250 1600 1700 1800 1900 2000 2100 2200 2300 2400 2.9 1.3 2.0 1.4 2.3 2.3 2.0 2.5 2.2 1400 2.Litho-classification Training Set Issues 1600 2000 24001.8 Cemented sand? 1600 1600 1700 1800 1900 2000 2100 2200 2300 2400 Well logs 2.1 Extract training sets 1500 1550 2.2 2.4 1350 1450 2.3 2.0 Compute probability litho-cubes May 2015 P(Class i I p .9 1.9 1.4 2.1 2.1 2.6 1200 Too sparse and not representative of natural reservoir variability s 1300 May not include all “litho-classes” May not capture expected depth trends 2.8 2.0 Oil s Water Gas 0.V p / Vs ) 1600 1700 1800 1900 2000 2100 2200 2300 2400 2. 0 Oil s Water Gas 0.2 2.1 2.3 2.8 1.2 2.3 2.5 2.5 2.4 2.2 2.9 1.5 2.V p / Vs ) 1600 1700 1800 1900 2000 2100 2200 2300 2400 2.2 2.9 1.1 2.0 1.9 1.4 2.0 1.9 1.0 Compute probability litho-cubes May 2015 P(Class i I p .8 1600 1700 1800 1900 2000 2100 2200 2300 2400 I p 149 .3 2.3 2.0 2.8 Additional simulated litho-class 1600 1700 1800 1900 2000 2100 2200 2300 2400 Peff Augmented training set for existing class Compute multivariate PDFs Vp/V 1.8 1.4 2.5 2.1 2.4 2.Litho-classification Sw F Vclay Vp/V Monte Carlo Simulation s Simulate training sets PEM 1600 1700 1800 1900 2000 2100 2200 2300 2400 2.1 2.0 2. we will use the previously defined PEMs to interpret an elastic inversion result. May 2015 150 .Part 5: LithoSI analysis In this exercise. We will also perform a litho-classification of that inverted model using both the well data and the synthetic training sets created in the previous exercise. Part 5: LithoSI analysis To initiate the LithoSI program. go back to the Processes tab and under Facies Classification (LithoSI) . May 2015 151 . double-click <New LithoSI Session>. Part 5: LithoSI analysis The dialog which appears is multi-tab. These seismic volumes are collected in a “Super Volume”. which will help you set up the LithoSI process. May 2015 152 . The first tab of the dialog defines which seismic volumes will be used in the process. In this example we select both the Zp and VpVs volumes as shown on the left (either click once on each volume and click Select or double-click each volume). so Select these wells: May 2015 153 .Part 5: LithoSI analysis When you have changed the first page as shown above. click the Wells tab to see the next page: This page specifies which wells to use in the analysis. well_C and well_D). We want to use three wells (well_B. click the Facies Classification tab: The Facies Classification page is used to define the set of facies classes in our training data.Part 5: LithoSI analysis Then. Click on Facies: May 2015 154 . which was created in each of the wells in the previous section. We will select the classes we just defined in the previous section. we define the classes. telling the program how many classes and what their names are. First we select the lithology log. This was called FACIES. In the rest of the page. Inverted_Ip. We associate the seismic inversion volume. The default number of attributes is 2. May 2015 155 .Part 5: LithoSI analysis Now click the last tab. and we will accept that: The mapping of volumes is as on the right. Seismic Attributes-Well Log Mapping: On this page. Similarly. and how the seismic volumes are related to the well log curves. we associate the seismic inversion volume Inverted_VpVs with the well log curve VpVs. with the curve IP. we specify how many seismic attributes are used. Part 5: LithoSI analysis When you have filled in the dialog as shown above. click OK to create the LithoSI window: May 2015 156 . The first thing we can do is create more space on the computer screen by temporarily removing the Project Manager.Part 5: LithoSI analysis The LithoSI window contains a series of options for creating the probability distributions associated with each class. Click the “x” as shown: Note that we can restore the Project Manager any time later by clicking the rotated name Project Manager on the left side: May 2015 157 . Part 5: LithoSI analysis Go to the Data Selection tab We want to use the simulated data created in RockSI so select “Load training-set from RockSI”. Note that the session name will be different in your case since by default the name is created with date and time. May 2015 158 . Specify the mapping of the properties used in RockSI with the log curves. Select RockSI Session and the training set. The a-posterior proportions on the rightmost column in the bottom table are calculated from all the wells based on facies curves. Turn on External Training-set. Turn off Well logs data points.Part 5: LithoSI analysis To display the external training set from RockSI in a crossplot. May 2015 159 . Next step is to generate the pdfs for each of these facies and fine-tune by adjusting the smoother parameter. May 2015 160 .Part 5: LithoSI analysis LithoSI Kernel Analysis now shows the data points simulated in RockSI. Part 5: LithoSI analysis Reduce the smoother length to 2. May 2015 161 . In Kernel Analysis tab. The pdfs between these facies overlap quite a bit. Reducing the smoother length also reduces these overlaps. Click on Compute in Common Parameters panel. turn off Coal distribution. Click Compute button again.Part 5: LithoSI analysis Use the slider to adjust the smoother to 1. The pdfs now fit the facies data points tighter. May 2015 162 . Part 5: LithoSI analysis Click on QC at Wells. May 2015 163 . Select only Well Logs toggle. The Confusion Matrix gives an overall success and misclassification rates of the facies at all three well locations. Part 5: LithoSI analysis Next we QC with an automatically generated arbitrary line that passes through the three wells. Go to QC on Sections. May 2015 164 . Select “Passing through wells” and click on the Select all wells icon. Finally.Part 5: LithoSI analysis You can also QC constant time map of the classification by going to the QC on Maps tab. It is not necessary to run the process for this exercise. you can generate the classification results for the entire volume by running it in “Run on 3D volume” tab. May 2015 165 . This concludes our RockSI tutorial.Part 5: LithoSI analysis This final exercise demonstrate how RockSI simulated data points can be used in the Bayesian Classification process (LithoSI). May 2015 166 .