Method and system for identifying lithology

Abstract

The invention provides a method for identifying lithology, and belongs to the technical field of geophysical exploration. The method comprises the following steps: acquiring magnetic field amplitude data obtained by inversion of a natural electromagnetic field; preprocessing the magnetic field amplitude data; carrying out square wave layering processing on the preprocessed magnetic field amplitude data and taking values layer by layer; magnetic field lithology sensitive parameters are extracted based on the magnetic field amplitude data after square wave processing; establishing a lithology identification plate and a lithology identification standard based on the magnetic field lithology sensitive parameters and the resistivity lithology sensitive parameters; the resistivity lithology sensitive parameters are obtained from logging data; and identifying lithology distribution of different depths based on the lithology identification plate and a standard. Therefore, the acquisition cost of the electromagnetic survey method is reduced, and the lithology is identified by using the electromagnetic survey method.

Description

Technical Field

[0001] The present application relates to the technical field of geophysical exploration, and in particular to a method and system for identifying lithology. Background Art

[0002] Electromagnetic surveying is a broad geophysical exploration method based on the principle of electromagnetic induction, used to investigate geological structures, structures, and other geological issues, as well as for engineering surveys. Existing electromagnetic surveying techniques often rely on the skin effect, a phenomenon inherent in electromagnetic induction, as their physical basis, and are volumetric exploration techniques.

[0003] Related technologies use artificially excited electromagnetic sounding (MT) to obtain information on the electrical distribution characteristics of underground rocks and minerals by measuring and analyzing electromagnetic field data on the ground. This information, combined with rock and mineral electromagnetic properties (resistivity, polarizability, magnetic susceptibility, etc.) and geological and other geophysical data, is used to comprehensively interpret these data to solve problems related to geological and engineering exploration. MT technology primarily aims to determine stratigraphic sequence and structure and cannot yet identify lithology.

[0004] Therefore, there is an urgent need to improve the acquisition cost and lithology identification capabilities of electromagnetic survey methods. Summary of the Invention

[0005] In order to solve the technical problems of existing electromagnetic survey methods, such as high cost, low deep layer accuracy and inability to identify lithology, the embodiments of the present application provide a method and system for identifying lithology.

[0006] In a first aspect, an embodiment of the present application provides a method for identifying lithology, characterized in that the method comprises:

[0007] Obtaining magnetic field amplitude data obtained by inversion of natural electromagnetic fields;

[0008] preprocessing the magnetic field amplitude data;

[0009] The pre-processed magnetic field amplitude data is subjected to square wave layering processing and the values are taken layer by layer;

[0010] Extract magnetic field lithologic sensitive parameters based on magnetic field amplitude data after square wave processing;

[0011] Establishing a lithology identification chart and standard based on the magnetic field lithology sensitivity parameter and the resistivity lithology sensitivity parameter; the resistivity lithology sensitivity parameter is obtained from well logging data;

[0012] The lithology distribution at different depths is identified based on the lithology identification plate and standards.

[0013] Optionally, the pre-processing the magnetic field amplitude data includes:

[0014] filtering out random interference signals in the magnetic field amplitude data;

[0015] Taking the well bypass as the benchmark, the difference between the main frequency values of the amplitude histogram of each channel and the benchmark channel in the marker layer is analyzed;

[0016] Correcting the temporal inconsistency of the magnetic field intensity of the natural electromagnetic field incident on the formation based on the difference;

[0017] Compare the logging depth and electromagnetic frequency of the marker interval and convert the frequency domain magnetic field amplitude data into depth domain magnetic field amplitude data;

[0018] A plurality of key layers are selected between any two marker layers, and the depth of the depth-domain magnetic field amplitude data is adjusted based on the logging depth.

[0019] Optionally, performing square wave layering processing on the pre-processed magnetic field amplitude data and obtaining values layer by layer includes:

[0020] Comparison of small layer distribution characteristics in well logging data with resistivity log curves;

[0021] The arithmetic mean of the intra-layer amplitudes with a confidence level greater than or equal to the reference value is taken as the amplitude value of each sub-layer.

[0022] Optionally, the magnetic field lithology sensitive parameter satisfies:

[0023]

[0024] Among them, β is the lithologic sensitivity parameter of the natural electromagnetic field amplitude curve, expressed as a decimal; AH is the amplitude characteristic value of the small layer in the natural magnetic field amplitude data, the unit is nT; AH min AH is the minimum amplitude characteristic value of the small layer in each natural magnetic field amplitude data in any depth segment, the unit is nT; max The maximum amplitude characteristic value of each small layer in the natural magnetic field amplitude data within any depth segment, in nT.

[0025] Optionally, the resistivity lithology sensitive parameter satisfies:

[0026]

[0027] Where α is the resistivity lithologic sensitivity parameter, expressed as a decimal; RT is the resistivity characteristic value of the small layer in the well logging data, expressed in Ω·m; RTmin is the minimum resistivity characteristic value of the small layer in each well logging data within any depth segment, expressed in Ω·m; RTmax is the maximum resistivity characteristic value of the small layer in each well logging data within any depth segment, expressed in Ω·m.

[0028] Optionally, the magnetic field lithology sensitive parameter satisfies:

[0029] When β>0.4, the lithology is sandstone;

[0030] When β≤0.2, the lithology is mudstone;

[0031] When 0.2<β≤0.4, the lithology is muddy sandstone / sandy mudstone.

[0032] Optionally, in the process of filtering out random interference signals in the magnetic field amplitude data, the filter half-window length is related to the vertical resolution capability of the natural electromagnetic field and the minimum thickness for lithology identification.

[0033] Optionally, the reference value is greater than or equal to 95%.

[0034] Optionally, the distribution characteristics of small layers in the logging data of the comparative resistivity logging curve include: a processing window length and / or an activity cutoff value of each small layer in the logging data of the comparative resistivity logging curve.

[0035] In a second aspect, an embodiment of the present application further provides a system for identifying lithology, characterized in that the system is applicable to the method for identifying lithology as described in any of the above embodiments, and includes:

[0036] A sampling module is configured to obtain magnetic field amplitude data obtained by inverting a natural electromagnetic field;

[0037] a preprocessing module, configured to preprocess the magnetic field amplitude data;

[0038] A layering module is configured to perform square wave layering processing on the pre-processed magnetic field amplitude data and obtain values layer by layer;

[0039] an extraction module configured to extract magnetic field lithology sensitive parameters based on the amplitude data after square wave processing;

[0040] The mapping module is configured to establish a lithology identification chart and standard based on the magnetic field lithology sensitivity parameters and the resistivity lithology sensitivity parameters; the resistivity lithology sensitivity parameters are obtained from well logging data.

[0041] The method and system for identifying lithology provided in the embodiments of the present application have at least the following beneficial effects:

[0042] By using natural electromagnetic field inversion to obtain magnetic field amplitude data, the data acquisition cost of the electromagnetic survey method is reduced and the deep-layer accuracy is improved; by preprocessing and square-wave conversion of the magnetic field amplitude data, the small layer division and value acquisition of the natural electromagnetic field amplitude data are realized, thereby extracting the magnetic field lithology sensitive parameters, and obtaining the resistivity lithology sensitive parameters through logging data. Based on the magnetic field lithology sensitive parameters and resistivity lithology sensitive parameters, a lithology identification map and standard are established to identify the lithology distribution at different depths. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0044] Figure 1 The method for identifying lithology provided by the embodiment of the present application is shown;

[0045] Figure 2 A flowchart of preprocessing magnetic field amplitude data provided by an embodiment of the present application is shown;

[0046] Figure 3 A schematic diagram of square wave conversion provided by an embodiment of the present application is shown;

[0047] Figure 4 A cross-plot of clastic rock lithology identification between the magnetic field lithology sensitivity parameters provided in the embodiment of the present application and the resistivity lithology sensitivity parameters of adjacent wells is shown;

[0048] Figure 5 An optional example of lithology identification according to the method provided by the present invention is shown. DETAILED DESCRIPTION

[0049] In order to enable those skilled in the art to better understand the present invention, the following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of this application.

[0050] like Figure 1 As shown, the embodiment of the present application provides a method for identifying lithology. The method includes the following steps:

[0051] Obtaining magnetic field amplitude data obtained by inversion of natural electromagnetic fields;

[0052] Preprocessing the obtained magnetic field amplitude data;

[0053] The pre-processed magnetic field amplitude data is subjected to square wave layering processing and the values are taken layer by layer;

[0054] Extract magnetic field lithologic sensitive parameters based on magnetic field amplitude data after square wave processing;

[0055] Establishing a lithology identification chart and standard based on the magnetic field lithology sensitivity parameter and the resistivity lithology sensitivity parameter; the resistivity lithology sensitivity parameter is obtained from well logging data;

[0056] The lithology distribution at different depths is identified based on the lithology identification plate and standards.

[0057] According to the embodiments of the present application, obtaining magnetic field amplitude data obtained through inversion of a natural electromagnetic field refers to performing travel-time inversion on the natural electromagnetic field to obtain the corresponding magnetic field travel-time sequence. It is generally believed that because natural electromagnetic fields continuously penetrate underground, existing acquisition and processing methods are unable to obtain the initial incidence time of the electromagnetic signal excited by the natural field source, nor the initial zero time data of the electromagnetic signal reflected underground. In other words, existing technologies are unable to measure the actual travel-time sequence of the natural electromagnetic field. The inventors of the present application unexpectedly discovered that when an electromagnetic field propagates through the underground medium, it is reflected and refracted again when it encounters an underground electrical impedance interface. When the reflected electromagnetic field returns to the sensor location, it creates a superposition effect at the sensor with the external electromagnetic field that is continuously penetrating the ground from the air. The resulting composite electromagnetic field, after superposition of the natural electromagnetic fields, is then injected into the underground medium and propagates again. The intensity of each frequency component of the electromagnetic field injected into the underground again will be the composite electromagnetic field after superposition. Therefore, the superimposed electromagnetic field will be referred to as the composite electromagnetic field in the following text. It should be understood that the external electromagnetic field in this application is based on the ground, and the electromagnetic field emitted from the air to the ground is called the external electromagnetic field. It should also be understood that the sensor position in this application can be on the ground or in the air.

[0058] Therefore, the travel time inversion of the natural electromagnetic field in this application includes collecting the initial signal; the initial signal includes the natural electric field and / or magnetic field incident on the ground, and at the moment when it is reflected and refracted back to the sensor position by the underground electrical impedance interface (the electromagnetic field reflected back to the ground is the secondary field), and the natural electric field and / or magnetic field incident on the ground at that moment (the electromagnetic field incident on the ground is the primary field) meets at the sensor, and the two are superimposed to obtain the initial time series of the synthetic electric field and / or magnetic field strength.

[0059] Performing Fourier transform on the initial time series to obtain an initial frequency spectrum of the initial time series.

[0060] Travel time inversion is based on the principle of electromagnetic field superposition. The initial spectrum is superimposed through the harmonic synthesis algorithm to obtain the synthetic travel time series of the natural electric field and / or magnetic field; the synthetic travel time series is used to analyze geological information.

[0061] For the case of a homogeneous, single-layer underground medium, the initial signal must at least meet the following requirements: Where, is the phase difference between the natural electric field and / or magnetic field of any frequency at the moment when it returns to the sensor after being reflected and refracted by the underground electrical impedance interface, and the natural electric field and / or magnetic field of the same frequency that continues to incident at the same moment. f0 is the frequency of any single harmonic electric field and / or magnetic field in the initial signal, ρ1 is the resistivity of the medium, and h1 is the burial depth of any layer of electrical medium.

[0062] According to an embodiment of the present application, performing traveltime inversion on a natural electromagnetic field further includes screening the initial spectrum for dominant frequency components, where the dominant frequency components are associated with a specific underground electrical structure. Preferably, any frequency within the dominant frequency components is inversely proportional to the burial depth of the electrical impedance interface corresponding to that frequency.

[0063] Optionally, the dominant frequency component at least satisfies:

[0064]

[0065] Wherein, n is an integer greater than or equal to 0; It is the phase difference between the natural electric field and / or magnetic field of any frequency in the dominant frequency component, when it returns to the sensor after being reflected and refracted by the underground electrical impedance interface, and the natural electric field and / or magnetic field of the same frequency that continues to be incident at the said moment.

[0066] Therefore, optionally, the phase difference of any frequency in the dominant frequency component of the present application when superimposed at the sensor falls within the frequency band In the above frequency band, int means rounding. It is the phase difference between the fundamental frequency at the moment it returns to the ground after propagating, reflecting, and refracting in the underground medium, and the external electromagnetic field of the same frequency that is continuously incident at that moment. Therefore, while the frequency that meets the above conditions is enhanced by superposition, based on similar principles, the frequency components that are in a frequency-multiplier relationship with the frequency are also enhanced by superposition. Therefore, the present application provides a method for surveying using natural electromagnetic fields, which effectively avoids the reduction in measurement accuracy due to increased depth and realizes measurement at great depths (for example, a measurement depth greater than 8000 meters).

[0067] The initial signal acquisition location is not limited to the ground; it can also be located on the water surface or in the air. In traditional electromagnetic and seismic surveys, sensors must be installed on the ground or buried shallowly to avoid signal attenuation and interference that prevent them from receiving signals with a satisfactory signal-to-noise ratio.

[0068] Further, see Figure 2The magnetic field and amplitude data obtained through inversion are further preprocessed. This preprocessing process first filters out random interference signals from the magnetic field amplitude data. For example, the arithmetic mean filter algorithm used in smoothing filtering eliminates random interference signals from the amplitude information of the natural magnetic field. The filter half-window length is one of the key factors affecting the filtering effect. The appropriate filter half-window length should be selected by comprehensively considering the vertical resolution of the natural electromagnetic field and the minimum thickness for lithologic identification.

[0069] Next, based on the well bypass, the difference in the dominant frequency values of the amplitude histograms of each channel in the marker layer and the reference channel is analyzed. Specifically, the magnetic field amplitude histograms of each channel in the marker layer are extracted, and the difference between the magnetic field amplitudes of the dominant channel and the reference channel is calculated. A marker bed is a layer with distinct amplitude characteristics in the well logging data or magnetic field amplitude data. This difference is then used to correct for temporal inconsistencies in the magnetic field intensity of the natural electromagnetic field incident on the formation.

[0070] Next, the logging depth and electromagnetic frequency of the marker layer section are compared, and a frequency-depth conversion curve is established to convert the frequency domain magnetic field amplitude data into depth domain magnetic field amplitude data. Given that the speed of electromagnetic waves is very fast, slight changes in the propagation process will significantly affect the detection depth. Therefore, multiple key layers are selected between any two marker layers, and the depth of the depth domain magnetic field amplitude data is adjusted based on the logging depth to eliminate the influence of the heterogeneity of parameters such as conductivity, permeability and dielectric constant of the formation on the electromagnetic wave velocity, thereby improving the depth accuracy of the depth domain magnetic field amplitude data. For example, based on the logging depth, the magnetic field amplitude curve is moved in the depth direction so that the depth of the magnetic field amplitude curve corresponds to the logging depth.

[0071] According to an embodiment of the present application, preprocessed magnetic field amplitude data is squared and layered, and values are taken layer by layer, including comparisons with resistivity logging curves to determine the distribution characteristics of sub-layers in the logging data. The arithmetic mean of the amplitudes within the layers with a confidence level greater than or equal to a reference value is used as the amplitude value for each sub-layer. Optionally, the reference value is greater than or equal to 95%. Figure 3 The square wave conversion of the detection data is given as an example. Figure 3 The natural gamma curve in is squared to form a square wave.

[0072] According to an optional embodiment, the magnetic field amplitude curve of continuous depth is processed into a square wave curve by an active layering method. During the processing, the distribution characteristics of the small layers in the logging data of the resistivity logging data (i.e., the resistivity-depth curve) are compared, and the processing window length and / or activity cutoff value are selected. Thereafter, the arithmetic mean value of the amplitude within the layer with a confidence level greater than or equal to the reference value is used as the amplitude value of each small layer. Optionally, when the confidence level is n%, it is necessary to eliminate (1-n%) data points of the upper and lower interfaces of the corresponding small layer. For example, when the confidence level is 95%, it is necessary to eliminate 5% of the data points of the upper and lower interfaces of the corresponding small layer.

[0073] Next, we extracted magnetic field lithology sensitivity parameters based on the squared-wave magnetic field amplitude data. The inventors unexpectedly discovered that the magnetic field amplitude data and the resistivity data from the well logging data exhibited a significant consistent trend. Therefore, we defined two parameters: the resistivity lithology sensitivity parameter and the magnetic field lithology sensitivity parameter. The resistivity lithology sensitivity parameter characterizes the response of resistivity to different lithologies; the magnetic field lithology sensitivity parameter characterizes the response of different lithologies to the magnetic field.

[0074] Among them, the resistivity lithology sensitive parameters meet the following requirements:

[0075]

[0076] Wherein, α is the resistivity lithologic sensitivity parameter, expressed as a decimal; RT is the resistivity characteristic value of the small layer in the well logging data, in ohm-meter (Ω·m); RTmin is the minimum resistivity characteristic value of each small layer in the well logging data within any depth segment, in Ω·m; RTmax is the maximum resistivity characteristic value of each small layer in the well logging data within any depth segment, in Ω·m.

[0077] Among them, the magnetic field lithology sensitivity parameters meet the following requirements:

[0078]

[0079] Where β is the lithologic sensitivity parameter of the natural electromagnetic field amplitude curve, expressed as a decimal; AH is the amplitude characteristic value of the small layer in the natural magnetic field amplitude data, in nanotesla (nT); AH min AH is the minimum amplitude characteristic value of each small layer in the natural magnetic field amplitude data within any depth segment, in nT; max The maximum amplitude characteristic value of each small layer in the natural magnetic field amplitude data within any depth segment, in nT.

[0080] For example, Figure 4 The cross-plot of clastic rock lithology identification using magnetic field lithology sensitivity parameters calculated by inversion of natural electromagnetic field measurement data and resistivity lithology sensitivity parameters of adjacent wells is shown. Figure 4 , the magnetic field lithology sensitivity parameters and resistivity lithology sensitivity parameters are positively correlated. Figure 4 The identification criteria for the magnetic field lithologic sensitivity parameters are further determined as follows: if β>0.4, the sublayer is sandstone; if β≤0.2, the sublayer is mudstone; if 0.2<β≤0.4, the sublayer is argillaceous sandstone or sandy mudstone.

[0081] According to the implementation mode of this application, Figure 5 As shown in the figure, a lithology identification chart and standard are established based on the magnetic field lithology sensitivity parameters and the resistivity lithology sensitivity parameters. In the depth domain, a comparison chart is established between the depth-matched magnetic field amplitude lithology sensitivity parameters and the resistivity lithology sensitivity parameters obtained by logging. Figure 5 As shown in the figure, with the detection depth of the natural electromagnetic field as the scale, the resistivity lithologic sensitivity parameter-depth curve and the magnetic field lithologic sensitivity parameter-depth curve are placed side by side, and the depths of the two curves are aligned according to the marker layer. Then, according to the changes in the resistivity lithologic sensitivity parameter and the lithology of the logging layer, the corresponding standard between the value of the magnetic field lithologic sensitivity parameter and the lithology is established to obtain the lithologic identification chart and standard.

[0082] According to the implementation of the present application, based on the above-mentioned lithologic identification chart and standards, lithologic identification based on the natural magnetic field amplitude is achieved depth by depth point (ie, sampling point) or small layer by small layer.

[0083] In summary, the method for identifying lithology provided in the embodiment of the present application effectively controls the acquisition cost by adopting the magnetic field amplitude data obtained by inversion of the natural electromagnetic field; further, the inverted magnetic field amplitude data is squared and layered through preprocessing to obtain depth domain magnetic field amplitude data corresponding to the logging data; further, magnetic field lithology sensitivity parameters are extracted based on the squared magnetic field amplitude data, and by comparing the magnetic field lithology sensitivity parameters with the resistivity lithology sensitivity parameters of the logging, a lithology identification plate and standard are obtained, and the depth domain lithology distribution reflected by the magnetic field amplitude data is judged based on the lithology identification plate and standard.

[0084] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art who can easily conceive of changes or substitutions within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for identifying lithology, characterized in that: The method comprises: Obtaining magnetic field amplitude data obtained by inversion of natural electromagnetic fields; preprocessing the magnetic field amplitude data; The pre-processed magnetic field amplitude data is subjected to square wave layering processing and the values are taken layer by layer; Extract magnetic field lithologic sensitive parameters based on magnetic field amplitude data after square wave processing; Establishing a lithology identification chart and standard based on the magnetic field lithology sensitivity parameter and the resistivity lithology sensitivity parameter; the resistivity lithology sensitivity parameter is obtained from well logging data; The lithology distribution at different depths is identified based on the lithology identification plate and standards.

2. The method according to claim 1, characterized in that The pre-processing of the magnetic field amplitude data comprises: filtering out random interference signals in the magnetic field amplitude data; Taking the well bypass as the benchmark, the difference between the main frequency values of the amplitude histogram of each channel and the benchmark channel in the marker layer is analyzed; Correcting the temporal inconsistency of the magnetic field intensity of the natural electromagnetic field incident on the formation based on the difference; Compare the logging depth and electromagnetic frequency of the marker interval and convert the frequency domain magnetic field amplitude data into depth domain magnetic field amplitude data; A plurality of key layers are selected between any two marker layers, and the depth of the depth-domain magnetic field amplitude data is adjusted based on the logging depth.

3. The method according to claim 1, characterized in that The performing square wave layered processing on the pre-processed magnetic field amplitude data and obtaining values layer by layer comprises: Comparison of small layer distribution characteristics in well logging data with resistivity log curves; The arithmetic mean of the intra-layer amplitudes with a confidence level greater than or equal to the reference value is used as the amplitude value of each small layer in the logging data.

4. The method according to claim 1, wherein The magnetic field lithology sensitive parameters satisfy: Among them, β is the lithologic sensitivity parameter of the natural electromagnetic field amplitude curve, expressed as a decimal; AH is the amplitude characteristic value of the small layer in the natural magnetic field amplitude data, the unit is nT; AH min AH is the minimum amplitude characteristic value of each small layer in the natural magnetic field amplitude data within any depth segment, in nT; max The maximum amplitude characteristic value of each small layer in the natural magnetic field amplitude data within any depth segment, in nT.

5. The method according to claim 1, characterized in that The resistivity lithology sensitive parameters satisfy: Wherein, α is the resistivity lithologic sensitivity parameter, expressed as a decimal; RT is the resistivity characteristic value of the sublayer in the logging data, expressed in Ω·m; RTmin is the minimum resistivity characteristic value of each sublayer in the logging data within any depth segment, expressed in Ω·m; RTmax is the maximum resistivity characteristic value of each sublayer in the logging data within any depth segment, expressed in Ω·m.

6. The method according to claim 1 or 4, characterized in that The magnetic field lithology sensitive parameters satisfy: When β>0.4, the lithology is sandstone; When β≤0.2, the lithology is mudstone; When 0.2<β≤0.4, the lithology is muddy sandstone / sandy mudstone.

7. The method according to claim 1 or 2, characterized in that In the process of filtering out random interference signals in the magnetic field amplitude data, the filter half-window length is related to the vertical resolution capability of the natural electromagnetic field and the minimum thickness for lithology identification.

8. The method according to claim 3, characterized in that The reference value is greater than or equal to 95%.

9. The method according to claim 3, characterized in that The distribution characteristics of the small layers in the logging data of the comparative resistivity logging curve include: the processing window length and / or activity cutoff value of each small layer in the logging data of the comparative resistivity logging curve.

10. A system for identifying lithology, characterized in that: The system comprises: A sampling module is configured to obtain magnetic field amplitude data obtained by inverting a natural electromagnetic field; a preprocessing module, configured to preprocess the magnetic field amplitude data; A layering module is configured to perform square wave layering processing on the pre-processed magnetic field amplitude data and obtain values layer by layer; an extraction module configured to extract magnetic field lithology sensitive parameters based on the amplitude data after square wave processing; The mapping module is configured to establish a lithology identification chart and standard based on the magnetic field lithology sensitivity parameters and the resistivity lithology sensitivity parameters; the resistivity lithology sensitivity parameters are obtained from well logging data.

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