Changes

At the customer's request, digital wireline data can be transmitted from the logging truck's computer directly to (1) the client, (2) other partners, and/or (3) the logging company's main computer for immediate processing, retransmission, or rerecording for delivery to the client. When digital data are read into a computer by a LAP, they are automatically converted to the LAP's internal data format for storage and use.

At the customer's request, digital wireline data can be transmitted from the logging truck's computer directly to (1) the client, (2) other partners, and/or (3) the logging company's main computer for immediate processing, retransmission, or rerecording for delivery to the client. When digital data are read into a computer by a LAP, they are automatically converted to the LAP's internal data format for storage and use.

''Analog data'' include all data presented on paper or films:

''Analog data'' include all data presented on paper or films:

Traceplots can be converted to digital data through manual digitizing or optical scanning. Most LAPs include log digitizing software. Many commercial data firms also sell digitizing services and may even have digital libraries for sale. Numerical listings include core and geochemical data. Both are usually sampled somewhat sporadically and thus have varying sample increments. Text information includes descriptions, explanations, formation tops, and test results. This information is extremely useful when annotating graphics. Both numerical listings and text information are well suited for keyboard entry into the database.

Traceplots can be converted to digital data through manual digitizing or optical scanning. Most LAPs include log digitizing software. Many commercial data firms also sell digitizing services and may even have digital libraries for sale. Numerical listings include core and geochemical data. Both are usually sampled somewhat sporadically and thus have varying sample increments. Text information includes descriptions, explanations, formation tops, and test results. This information is extremely useful when annotating graphics. Both numerical listings and text information are well suited for keyboard entry into the database.

==Data editing==

==Data editing==

[[file:log-analysis-applications_fig1.png|left|thumb|{{figure number|1}}Interactive depth shifting. The user marks correlating inflection points and shifts off-depth traces to base trace depths.]]

[[file:log-analysis-applications_fig3.png|left|thumb|{{figure number|3}}A histogram display of a traces value range. Frequency nodes in a trace's data values (''x''₁, and ''x''₂) within a given formation are related to geology. Node values are usually consistent and mappable for that interval if observed in multiple wells in an area. If node values are atypical for a given well due to tool miscalibration, a correct distribution and range can be determined and the trace normalized.]]

 

[[file:log-analysis-applications_fig2.png|thumb|{{figure number|2}}Interactive spontaneous potential (SP) baseline flattening. The user selects points on the raw SP curve, which represent zero deflection (that is, baseline = 100% shale). By projecting the baseline between two consecutive points, SP deflections are calculated and redisplayed as a baselined (or “static”) SP.]]

Options for editing of the data include the following:

Options for editing of the data include the following:

* Merge various traces into a single trace.

* Merge various traces into a single trace.

:<math>y = ax + b</math>

:<math>y = ax + b</math>

where

where

* Select consistent parameters for detailed log analysis calculations.

* Select consistent parameters for detailed log analysis calculations.

* Visually correlate all geological, core, wireline, geophysical, and engineering data both within each well and from well to well.

* Visually correlate all geological, core, wireline, geophysical, and engineering data both within each well and from well to well.

Visual examination of a specific formation across a broad area does the following:

Visual examination of a specific formation across a broad area does the following:

===Traceplots===

===Traceplots===

''Traceplots'' (''TPLTs'') visually relate data values to ''depth''. When planning any TPLT display, careful use of display variables (including scales, intervals, grids, track quantifies and widths, number of curves, line types and weights, colors, symbols, spacing, shading, and annotation) can be used to convey an immense amount of information without overwhelming an observer (Figure 4). Some of the more powerful LAPs allow interactive TPLT display, correlation, and database storage of formation tops from one or more wells displayed simultaneously on the screen.

''Traceplots'' (''TPLTs'') visually relate data values to ''depth''. When planning any TPLT display, careful use of display variables (including scales, intervals, grids, track quantifies and widths, number of curves, line types and weights, colors, symbols, spacing, shading, and annotation) can be used to convey an immense amount of information without overwhelming an observer ([[:file:log-analysis-applications_fig4.png|Figure 4]]). Some of the more powerful LAPs allow interactive TPLT display, correlation, and database storage of formation tops from one or more wells displayed simultaneously on the screen.

===Crossplots===

[[file:log-analysis-applications_fig5.png|left|thumb|{{figure number|5}}A Pickett plot allow users to interactively draw a line intersecting water wet points (''S''_w = 100%). This line identifies the cementation exponent (''m'') and the product of a × ''R''_''w'' (empirical constant × formation water resistivity) and relates water saturation (''S''_w) to porosity and true resistivity.]]

''Crossplots'' (''XPLTs'') relate two or more different trace values to each other at the same depth, such as core [[porosity]] and bulk density. Each type of wireline tool measures a different rock property. By studying the same XPLT in many wells, distinctive data plot patterns related to these rock properties allow users to identify lithologies, porosities, parameters, and other geological and/or engineering relationships.

''Crossplots'' (''XPLTs'') relate two or more different trace values to each other at the same depth, such as core [[porosity]] and bulk density. Each type of wireline tool measures a different rock property. By studying the same XPLT in many wells, distinctive data plot patterns related to these rock properties allow users to identify lithologies, porosities, parameters, and other geological and/or engineering relationships.

Several interactive graphic XPLT techniques and other features have been developed that make crossplots even more useful and powerful:

Several interactive graphic XPLT techniques and other features have been developed that make crossplots even more useful and powerful:

* Pickett plots, which are log-log plots of resistivity versus porosity (Figure 5) allow interactive parameter identification of m (the cementation exponent) and the product (''a'' × ''R''_''w'') (empirical constant × formation water resistivity), as well as visually displaying water saturation (S_w).

* Pickett plots, which are log-log plots of resistivity versus porosity ([[:file:log-analysis-applications_fig5.png|Figure 5]]) allow interactive parameter identification of m (the cementation exponent) and the product (''a'' × ''R''_''w'') (empirical constant × formation water resistivity), as well as visually displaying water saturation (S_w).

* Polygon isolators drawn on the screen around patterns recognized by the user (left side of Figure 6) identify the enclosed data in the database for future reference. A dual XPLT/TPLT screen display of the same data (Figure 6) allows XPLT pattern recognition and isolation, and TPLT depth identification (usually with tic marks or color shading at the corresponding TPLT depths). The reverse procedure (TPLT depth interval isolation and XPLT identification) is also useful. Storage and redisplay of the same polygon (using the same XPLT) on another well's data reinforces previously recognized patterns.

* Polygon isolators drawn on the screen around patterns recognized by the user (left side of [[:file:log-analysis-applications_fig6.png|Figure 6]]) identify the enclosed data in the database for future reference. A dual XPLT/TPLT screen display of the same data (Figure 6) allows XPLT pattern recognition and isolation, and TPLT depth identification (usually with tic marks or color shading at the corresponding TPLT depths). The reverse procedure (TPLT depth interval isolation and XPLT identification) is also useful. Storage and redisplay of the same polygon (using the same XPLT) on another well's data reinforces previously recognized patterns.

* Chart overlays (only available for certain data combinations), relating wireline data to known lithologies and total porosity.

* Chart overlays (only available for certain data combinations), relating wireline data to known lithologies and total porosity.

* Statistical and user-drawn best fit lines and/or curves.

* Statistical and user-drawn best fit lines and/or curves.

* Three-dimensional plots, allowing rotation of the XPLT around the ''x, y'', and ''z'' axes. This usually requires specialized high performance graphics hardware.

* Three-dimensional plots, allowing rotation of the XPLT around the ''x, y'', and ''z'' axes. This usually requires specialized high performance graphics hardware.

[[file:log-analysis-applications_fig5.png|thumb|{{figure number|5}}A Pickett plot allow users to interactively draw a line intersecting water wet points (''S''_w = 100%). This line identifies the cementation exponent (''m'') and the product of a × ''R''_''w'' (empirical constant × formation water resistivity) and relates water saturation (''S''_w) to porosity and true resistivity.]]

[[file:log-analysis-applications_fig7.png|left|thumb|{{figure number|7}}A two-well histogram allows users to compare data interactively from one well to another by shifting the second well's data across the base well on the screen. A visual best fit is usually satisfactory for determining the amount of normalization required.]]

 

[[file:log-analysis-applications_fig6.png|thumb|{{figure number|6}}Dual plot contains crosspiot (featuring data isolator polygon) and traceplot. User interactively draws polygon on the screen, which identifies the enclosed data in the database. Corresponding depths are immediately marked on the traceplot, in this case with tic marks.]]

===Histograms===

===Histograms===

''Histograms'' (''HISTs'') plot a trace's data values against their frequency of occurrence (Figure 3), showing the distribution of data across its range of values. A display of data from two wells on the same HIST (Figure 7) allows users to observe significant data node shifts between the two. Exact values of shifts can be determined by interactively moving data from one well across the other until a visual “best fit” is achieved.

''Histograms'' (''HISTs'') plot a trace's data values against their frequency of occurrence ([[:file:log-analysis-applications_fig3.png|Figure 3]]), showing the distribution of data across its range of values. A display of data from two wells on the same HIST ([[:file:log-analysis-applications_fig7.png|Figure 7]]) allows users to observe significant data node shifts between the two. Exact values of shifts can be determined by interactively moving data from one well across the other until a visual “best fit” is achieved.

 

The ability to combine data from many wells into a single composite XPLT or HIST allows the user to see at a glance the entire range and distribution of the data for any trace. Annotations on TPLTs, XPLTs, and HISTs are extremely useful when preparing displays for presentation and reports.

The ability to combine data from many wells into a single composite XPLT or HIST allows the user to see at a glance the entire range and distribution of the data for any trace. Annotations on TPLTs, XPLTs, and HISTs are extremely useful when preparing displays for presentation and reports.