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.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "advanced_examples/cement_volume_estimation.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_advanced_examples_cement_volume_estimation.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_advanced_examples_cement_volume_estimation.py:


Cement volume estimation 
========================

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.. code-block:: Python



    import numpy as np
    import matplotlib.pyplot as plt
    import pandas as pd
    plt.rcParams['font.size']=14
    plt.rcParams['font.family']='arial'
    plt.rcParams['axes.labelpad'] = 10.0









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.. code-block:: Python



    # import the module 
    from rockphypy import QI








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The rock physics diagnostic elastic bounds can be used to infer the microstructure from velocity-porosity data (Avseth et al. 2010). By locally validating the constant cement model and other diagnostic models such as friable sand model and contact cement model, we can obtain a quantitative measure of the degree of cement volume from the resulting diagnostic crossplots.
``QI`` module provides convinient method to perform the cement estimation given data.The following code snippets show the cement volume estimation for synthetic sandstone data. 

Notice that, this method is not strictly valid for cement volume estimation for heavily cemeneted sandstone. The constant cement model has its valid range just like any other models. awareness of the model limitation is necessary when applying the approach in pratice. 


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.. code-block:: Python



    # parameters
    Dqz, Kqz, Gqz = 2.65, 36.6, 45 ## grain density, bulk and shear modulus
    Dsh, Ksh, Gsh = 2.7, 21, 7 # shale/clay density, bulk and shear modulus
    Dc,Kc, Gc =2.65, 36.6, 45 # cement density, bulk and shear modulus
    Db, Kb = 1, 2.2 # brine density, bulk modulus
    phi_c=0.4 # critical porosity
    sigma=20 # effective pressure
    scheme=2
    Cn=8.6
    vsh=0 # shale volume
    # define cement porosity for Vp
    phib=0.3
    f= 0.5 # slip factor









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Applied to field data 
^^^^^^^^^^^^^^^^^^^^^
Let's import the same synthetic well log data and apply the cement volum estimation using constant cement model  to the well log data 


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.. code-block:: Python


    # read data
    data = pd.read_csv('../../data/well/sandstone.csv',index_col=0)


    # estimate cement: 
    vcem_seeds=np.array([0,0.005,0.01,0.02,0.03,0.04,0.1] )
    phib_p=[0.3,0.37,0.38,0.39,0.395] # define cement porosity for Vp

    # compute the elastic bounds
    phi,vp1,vp2,vp3,vs1,vs2,vs3 = QI.screening(Dqz,Kqz,Gqz,Dsh,Ksh,Gsh,Dc,Kc,Gc,Db,Kb,phib,phi_c,sigma,vsh,scheme,f, Cn)



    # create an object with data 
    qi= QI(data.VP,phi=data.PHIT_ND,Vsh= data.VSH_GR)

    # estimate the cement volume for data
    vcem= qi.estimate_cem(vcem_seeds,Kqz,Gqz,Ksh,Gsh,phi_c,Cn,Kc,Gc,Db,Kb,scheme,vsh,Dsh,Dqz,Dc)









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.. code-block:: Python


    # color_coding cement volume in the porosity and velocity cross plot. 
    fig=qi.cement_diag_plot(vcem,Dqz,Kqz,Gqz,Dsh,Ksh,Gsh,Dc,Kc,Gc,Db,Kb,phib,phib_p,phi_c,sigma,vsh,Cn, scheme,f)
    plt.ylim([1900,6100])
    plt.ylabel('Vp (Km/s)')
    plt.yticks(np.arange(2000,6200, 1000),[2,3,4,5,6])
    plt.xlim(-0.01,0.51)






.. image-sg:: /advanced_examples/images/sphx_glr_cement_volume_estimation_001.png
   :alt: cement volume estimation
   :srcset: /advanced_examples/images/sphx_glr_cement_volume_estimation_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    (-0.01, 0.51)



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As shown by the figure, using a 2D PDF can provide a clearer visualization of the data distribution compared to a normal scatter plot.


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**Reference** 
- Avseth, P.; Mukerji, T.; Mavko, G. & Dvorkin, J. Rock-physics diagnostics of depositional texture, diagenetic alterations, and reservoir heterogeneity in high-porosity siliciclastic sediments and rocks—A review of selected models and suggested work flows  Geophysics, Society of Exploration Geophysicists, 2010, 75, 75A31-75A47


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.183 seconds)


.. _sphx_glr_download_advanced_examples_cement_volume_estimation.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: cement_volume_estimation.ipynb <cement_volume_estimation.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: cement_volume_estimation.py <cement_volume_estimation.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: cement_volume_estimation.zip <cement_volume_estimation.zip>`


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 .. rst-class:: sphx-glr-signature

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