US20240026784A1

US20240026784A1 - System and method for rapid well log validation

Info

Publication number: US20240026784A1
Application number: US17/814,447
Authority: US
Inventors: Chicheng Xu; Mohamed Larbi Zeghlache; Tao Lin; Yuchen Jin; Weichang Li
Original assignee: Aramco Services Co
Current assignee: Saudi Arabian Oil Co
Priority date: 2022-07-22
Filing date: 2022-07-22
Publication date: 2024-01-25

Abstract

A method to perform a field operation with rapid well log validation is disclosed. The method includes generating, by performing well logging of a wellbore penetrating a subterranean formation in a field, a well log data file including a number of data channels, each data channel including a series of measurement data records representing a downhole property along a depth in the wellbore, analyzing, by a computer processor, the data channels to determine a quality level of said each data channel, categorizing, by the computer processor, the data channels according to respective values of the quality level to generate a validation summary of the well log data file, presenting, using a graphical user interface, the validation summary to a user, and facilitating, based on a user input in response to presenting the validation summary, the field operation.

Description

BACKGROUND

The term “well log” refers to measurement versus depth of physical properties in or around a well. The term comes from the word “log” used in the sense of a record or a note. Wireline logs are obtained downhole and transmitted through a wireline to surface and recorded. Similarly, measurements-while-drilling (MWD) and logging while drilling (LWD) logs are also obtained downhole. Well logs are either transmitted to surface by mud pulses, or recorded downhole and retrieved later when the logging instrument is brought to surface. Mud logs that describe samples of drilled cuttings are taken and recorded on surface.

SUMMARY

In general, in one aspect, the invention relates to a method to perform a field operation with rapid well log validation. The method includes generating, by performing well logging of a wellbore penetrating a subterranean formation in a field, a well log data file comprising a plurality of data channels, each data channel comprising a series of measurement data records representing a downhole property along a depth in the wellbore, analyzing, by a computer processor, the plurality of data channels to determine a quality level of said each data channel, categorizing, by the computer processor, the plurality of data channels according to respective values of the quality level to generate a validation summary of the well log data file, presenting, using a graphical user interface, the validation summary to a user, and facilitating, based on a user input in response to presenting the validation summary, the field operation.
In general, in one aspect, the invention relates to a data gathering and analysis system. The data gathering and analysis system includes a computer processor, and memory storing instructions, when executed, causing the computer processor to generate, by performing well logging of a wellbore penetrating a subterranean formation in a field, a well log data file comprising a plurality of data channels, each data channel comparing a series of measurement data records representing a downhole property along a depth in the wellbore, analyze the plurality of data channels to determine a quality level of said each data channel, categorize the plurality of data channels according to respective values of the quality level to generate a validation summary of the well log data file, present, using a graphical user interface, the validation summary to a user, and facilitate, based on a user input in response to presenting the validation summary, the field operation.
In general, in one aspect, the invention relates to a system that includes a wellsite having a wellbore penetrating a subterranean formation in a field, and a data gathering and analysis system comprising functionality for generating, by performing well logging of the wellbore, a well log data file comprising a plurality of data channels, each data channel comparing a series of measurement data records representing a downhole property along a depth in the wellbore, analyzing, by a computer processor, the plurality of data channels to determine a quality level of said each data channel, categorizing, by the compute processor, the plurality of data channels according to respective values of the quality level to generate a validation summary of the well log data file, presenting, using a graphical user interface, the validation summary to a user, and facilitating, based on a user input in response to presenting the validation summary, the field operation.
Other aspects and advantages of the claimed subject matter will be apparent from the following description and the appended claims.

BRIEF DESCRIPTION OF DRAWINGS

Specific embodiments of the disclosed technology will now be described in detail with reference to the accompanying figures. Like elements in the various figures are denoted by like reference numerals for consistency.

FIGS. 1A-1B show a system in accordance with one or more embodiments.

FIG. 2 shows a method flowchart in accordance with one or more embodiments.

FIGS. 3A-3G show an example in accordance with one or more embodiments.

FIG. 4 shows a computing system in accordance with one or more embodiments.

DETAILED DESCRIPTION

In the following detailed description of embodiments of the disclosure, numerous specific details are set forth in order to provide a more thorough understanding of the disclosure. However, it will be apparent to one of ordinary skill in the art that the disclosure may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description.
Throughout the application, ordinal numbers (for example, first, second, third) may be used as an adjective for an element (that is, any noun in the application). The use of ordinal numbers is not to imply or create any particular ordering of the elements nor to limit any element to being only a single element unless expressly disclosed, such as using the terms “before”, “after”, “single”, and other such terminology. Rather, the use of ordinal numbers is to distinguish between the elements. By way of an example, a first element is distinct from a second element, and the first element may encompass more than one element and succeed (or precede) the second element in an ordering of elements.
In general, embodiments of the disclosure include systems and methods for performing a field operation as facilitated by rapid well log validation. The field operation refers to physical activities performed in the field, such as an oil or gas field. By performing well logging of a wellbore penetrating a subterranean formation in a field, a well log data file is generated that includes a large number of data channels, each data channel having a series of measurement data records representing a downhole property (e.g., irradiation, density, electrical and acoustic properties, etc.) along a depth in the wellbore. Using a computer processor, the data channels are analyzed to determine a quality level of each data channel. Accordingly, the data channels are categorized according to respective values of the quality level to generate a validation summary of the well log data file. The validation summary is presented using a graphical user interface (GUI) to a user. The GUI may be displayed on a computing device such as that described below in FIG. 4 . The field operation (e.g., well production operation, well drilling operation, well completion operation, well maintenance operation, reservoir monitoring, assessment and development operation, etc.) is then advantageously performed based on a user input in response to presenting the validation summary.
FIG. 1A shows a schematic diagram of a well environment in accordance with one or more embodiments. In one or more embodiments, one or more of the modules and/or elements shown in FIG. 1A may be omitted, repeated, and/or substituted. Accordingly, embodiments disclosed herein should not be considered limited to the specific arrangements of modules and/or elements shown in FIG. 1A.
As shown in FIG. 1A, a well environment (100) includes a subterranean formation (“formation”) (104) and a well system (106). The formation (104) may include a porous or fractured rock formation that resides underground, beneath the earth's surface (“surface”) (108). The formation (104) may include different layers of rock having varying characteristics, such as varying degrees of permeability, porosity, capillary pressure, and resistivity. In the case of the well system (106) being a hydrocarbon well, the formation (104) may include a hydrocarbon-bearing reservoir (102). In the case of the well system (106) being operated as a production well, the well system (106) may facilitate the extraction of hydrocarbons (or “production”) from the reservoir (102).
In some embodiments disclosed herein, the well system (106) includes a rig (101), a wellbore (120), a data gathering and analysis system (160), and a well control system (“control system”) (126). The well control system (126) may control various operations of the well system (106), such as well production operations, well drilling operation, well completion operations, well maintenance operations, and reservoir monitoring, assessment and development operations. In some embodiments, the well control system (126) includes a computer system.
The rig (101) is the machine used to drill a borehole to form the wellbore (120). Major components of the rig (101) include the drilling fluid tanks, the drilling fluid pumps (e.g., rig mixing pumps), the derrick or mast, the draw works, the rotary table or top drive, the drill string, the power generation equipment and auxiliary equipment. Drilling fluid, also referred to as “drilling mud” or simply “mud,” is used to facilitate drilling boreholes into the earth, such as drilling oil and natural gas wells.
In some embodiments, a bottom hole assembly (BHA) (151) is attached to the drill string (150) to suspend into the wellbore (120) for performing the well drilling operation. The bottom hole assembly (BHA) is the lowest part of the drill string (150) and includes the drill bit, drill collar, stabilizer, mud motor, etc.
The wellbore (120) includes a bored hole (i.e., borehole) that extends from the surface (108) towards a target zone of the formation (104), such as the reservoir (102). The wellbore (120) may be drilled for exploration, development and production purposes. The wellbore (120) may facilitate the circulation of drilling fluids during drilling operations for the wellbore (120) to extend towards the target zone of the formation (104) (e.g., the reservoir (102)), facilitate the flow of hydrocarbon production (e.g., oil and gas) from the reservoir (102) to the surface (108) during production operations, facilitate the injection of substances (e.g., water) into the hydrocarbon-bearing formation (104) or the reservoir (102) during injection operations, or facilitate the communication of logging tools lowered into the formation (104) or the reservoir (102) during logging operations. The wellbore (120) may be logged by lowering a combination of physical sensors downhole to acquire data that measures various rock and fluid properties, such as irradiation, density, electrical and acoustic properties. The acquired data may be organized in a log format and referred to as well logs or well log data.
In some embodiments, the data gathering and analysis system (160) includes hardware and/or software with functionality for facilitating operations of the well system (106), such as well production operations, well drilling operation, well completion operations, well maintenance operations, and reservoir monitoring, assessment and development operations. For example, the data gathering and analysis system (160) may store drilling data records of drilling the wellbore (120) and well log data records of logging the wellbore (120). The data gathering and analysis system (160) may validate and analyze the well log data records to generate recommendations to facilitate various operations of the well system (106). In particular, the well log data records are validated before analysis. Once validated, a reservoir simulator may be used to further analyze the validated well log data and/or other types of data to generate and/or update reservoir models. The validation aspect of the data gathering and analysis system (160) is referred to as a well log validation system. While the data gathering and analysis system (160) is shown at a well site, embodiments are contemplated where at least a portion of the data gathering and analysis system (160) is located away from well sites. In some embodiments, the data gathering and analysis system (160) may include a computer system that is similar to the computer system (400) described below with regard to FIG. 4 and the accompanying description.
FIG. 1B shows details of the data gathering and analysis system (160) depicted in FIG. 1A above in accordance with one or more embodiments disclosed herein. In one or more embodiments, one or more of the modules and/or elements shown in FIG. 1B may be omitted, repeated, and/or substituted. Accordingly, embodiments disclosed herein should not be considered limited to the specific arrangements of modules and/or elements shown in FIG. 1B.
As shown in FIG. 1B, the data gathering and analysis system (160) has multiple components, including, for example, a buffer (114), a validation configuration engine (111), a validation check engine (112), and a validation display engine (113). Each of these components is discussed below.
In one or more embodiments, the buffer (114) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. The buffer (114) is configured to store input data, output results, and intermediate data of the validation configuration engine (111), the validation check engine (112), and the validation display engine (113). In one or more embodiments, the buffer (114) stores well log data files (115), validation configuration file (116), validation summary (117), quality score (118), interactive validation display (119), and validation heat map (120). The well log data files (115) include wireline logs, MWD logs, LWD logs, mud logs, etc. of one or more wells in a field. In one or more embodiments, the well log data files (115) are archived in DLIS (Digital Log Information Standard) or LAS (Log ASCII Standard) files as deliverables from a logging service provider to an operating entity of the field, such as a drilling company, an oil/gas production company, etc. generally referred to as the operating company.
The validation configuration file (116) is a configuration file that specifies various criteria of categorizing the well log data files. In one or more embodiments, the criteria describe all required data channels with corresponding measurement units. For each data channel, the criteria describe the range of acceptable measurement values, the maximum allowable noise level in the measurement values, expected trend of measurement values with respect to depth, etc. In addition, the criteria describe, for each data channel, the condition for measurement values to be considered as good, invalid, or missing. An example criterion for a data channel to be considered as good is that more than 95% of measurement values of the data channel are within the acceptable range with the correct units, an example criterion for a data channel to be considered as invalid is that less than 75% of measurement values of the data channel are within the acceptable range with the correct units, and an example criterion for a data channel to be considered as missing is that more than 10% of measurement values of the data channel are missing (empty, null or out of range . . . etc.). An example criterion for a data channel to be considered as good is that signal-to-noise ratio (SNR) is above an acceptable ratio, example above 10, with the correct units, an example criterion for a data channel to be considered as invalid is that signal-to-noise ratio (SNR) is below an acceptable ratio, example below 10, with the correct units. An example criterion for a data channel to be considered as good is that values are either increasing or decreasing with depth, with the correct units, an example criterion for a data channel to be considered as invalid is that values are arbitrarily changing with depth and following a desired trend, with the correct units. Another example criterion for a time-dependent decay array signal has to be monotonically decreasing with time.
The validation summary (116) is a summary of validation results of the well log data files (115). In one or more embodiments, the validation summary (116) includes an overall score and a statistical profile of all data channels of each DLIS/LAS well log data file. For example, the overall score may be a percentage of good data channels within the DLIS/LAS file and stored as the quality score (118). The statis statistical profile may include a pie chart, a histogram, and/or other percentage representation of the numbers of good, invalid, and missing data channels in the corresponding DLIS/LAS well log data file.
The interactive validation display (119) is a graphical display for a user to interactively viewing selected validation results. In one or more embodiments, the interactive validation display (119) includes a selection menu of the data channels in a well log data file and one or more graphical representations of a selected data channel. A user selection from the selection menu determines a particular data channel to display the validity result for user viewing. In particular, the validity result incudes one or more tallies of the measurement data records of the selected data channel according to a validity designation of each data record. For example, the tallies may be displayed as a pie chart, a histogram, and/or other percentage representation. For example, each data measurement may be designated as good, NAN, out of bound, or wrong unit. Specifically, a data measurement with a valid number of correct unit within the acceptable range is considered as a good data measurement.
The validation heat map (120) is a two-dimensional representation of measurement data validity designations where the validity designations (e.g., good, NAN, out of bound, wrong unit) are represented by colors or highlight patterns. Within the validation heat map (120), the X-axis and Y-axis correspond to the data channel identifier (i.e., tag) and depth, respectively.
In one or more embodiments, the validation configuration engine (111) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. The validation configuration engine (111) is configured to generate, select, and/or revise the validation configuration file (116) based on user input. For example, the user input may be received via a graphical user interface (GUI), more specifically via selection or data entry fields of the GUI. An example of receiving user input via the GUI is described in reference to FIG. 3A below.
In one or more embodiments, the validation check engine (112) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. The validation check engine (112) is configured to analyze the well log data files (115) to generate the validation summary (116), quality score (118), interactive validation display (119), and validation heat map (120).
In one or more embodiments, the validation display engine (113) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. The validation display engine (113) is configured to display the validation summary (116), quality score (118), interactive validation display (119), and validation heat map (120).
In one or more embodiments, the validation configuration engine (111), the validation check engine (112), and the validation display engine (113) collectively perform the functionalities described above using the method described in reference to FIG. 2 below.
Although the data gathering and analysis system (160) is shown as having four components (111, 112, 113, 114), in other embodiments, the data gathering and analysis system (160) may have more or fewer components. Further, the functionality of each component described above may be split across multiple components. Further still, each component (111, 112, 113, 114) may be utilized multiple times to carry out an iterative operation.
FIG. 2 shows a flowchart in accordance with one or more embodiments disclosed herein. One or more of the steps in FIG. 2 may be performed by the components of the well environment (100), in particular the data gathering and analysis system (160), discussed above in reference to FIGS. 1A-1B. In one or more embodiments, one or more of the steps shown in FIG. 2 may be omitted, repeated, and/or performed in a different order than the order shown in FIG. 2 . Accordingly, the scope of the disclosure should not be considered limited to the specific arrangement of steps shown in FIG. 2 .
Referring to FIG. 2 , initially in Step 200, a validation configuration file and the well log data files are loaded into a data gathering and analysis system. Each log data file may be a single compressed file containing a large number of data channels arranged in DLIS, LAS, LIS, or other formats. The validation configuration file contains a set of rules such as the expected value range for valid data unit and other criteria. The data sets to be loaded may be located in a local folder of the data gathering and analysis system or retrieved from a remote data server. Previously loaded configuration file and data file cache may also be removed (i.e., flushed) or updated. An example of the user interface and validation configuration file is described in reference to FIG. 3A and TABLE 1 below.
In Step 202, an automatic data validity check is performed. The data validity check (i.e., validation) may be initiated for a selected well log data file, or for the entire set of well log data files in a batch mode. In one or more embodiments, performing the automatic data validity check starts with evaluating each measurement data record of each data channel in the well log data file to determine a validity designation. The validity designation may include good, NAN, out of bound, or wrong unit. Specifically, a data measurement with a valid number of correct unit within the acceptable range is considered as a good data measurement. The measurement data records in each validity designation (e.g., good, NAN, out of bound, or wrong unit) within a data channel are tallied to determine a quality level of the data channel. For example, the data channel is considered as good quality level if more than 90% of the measurement data records have the validity designation “good.” Accordingly, the overall quality level of the well log data file is determined based on the percentage of the contained data channels that have the good quality level. In ne or more embodiments, the good quality level is considered as the highest value of the quality level.
In Step 204, after the validation process in Step 202 is completed, a validation summary is generated and displayed, which includes a summary of the data set information, the characterization of detected type of invalid data including the interval, missing channels, channels with incorrect units, out of bound or undefined (e.g., not-a-number (NaN)) values. A quality score is computed and displayed, e.g., with a score card highlighted in color or a hash pattern according to the quality score. For example, the quality score may be computed to be “good” representing the highest value of the quality level, while the “NaN” corresponds to the lowest value of the quality level. In addition, a pie chart may also be generated and displayed to show the quality composition including the percentage of data channels that are good, invalid or missing. An example result of Step 204 is described in reference to FIG. 3B below.
In Step 206, detailed validation results are produced and displayed where the user may interactively select whether to show all the data, or specific type of data that are good, missing or invalid. The user may also select a particular data channel to visualize in a log track, a histogram, and/or a pie chart. The visualized data channel may be highlighted, e.g., color coded, with the validation results. A detailed data table may also be generated and displayed, e.g., including the keys, the units, the upper and lower bounds of the values, the mean as well as the description for each data channel. The user may choose to show this information for all the data channels, or only the data channels with “good”, “missing” or “invalid” scores. Thus, the results may be customized or filtered as desired by the user. An example of the results produced in Step 206 is described in reference to FIG. 3C and FIG. 3D below.
In Step 208, a heatmap is generated to represent the validity designation across the well log data file. The heatmap is displayed that contains all data channels in the log track format and highlighted (e.g., color-coded) according to the validity designation, e.g., good, invalid, missing or NAN. The heatmap allows user to quickly identify the distribution of the identified problematic data in which data channels and at what depth intervals. An example of the heatmap generated in Step 208 is described in reference to FIG. 3E below.
In Step 210, the error flag file and validation report are generated and exported, e.g., as a LAS, DLIS, or CSV file. The exported file and report may be organized as a detail report or a summary report. An example of the validation report generated in Step 210 is described in reference to FIG. 3F and FIG. 3G below.
FIGS. 3A-3G show an implementation example in accordance with one or more embodiments. The implementation example shown in FIGS. 3A-3G is based on the system and method flowchart described in reference to FIGS. 1A, 1B, and 2 above. In one or more embodiments, one or more of the modules and/or elements shown in FIGS. 3A-3G may be omitted, repeated, and/or substituted. Accordingly, embodiments disclosed herein should not be considered limited to the specific arrangements of modules and/or elements shown in FIGS. 3A-3G.
DLIS or LAS well log data files have to pass data quality validation before going into an operating company's database. This validation process is tedious and usually takes very long time. One DLIS or LAS file may contain hundreds or thousands of data channels that are difficult to be visualized and validated manually. From time to time, multiple iterations of communication between the logging service provider and the operating company are required to achieve a final valid data deliverable. When this tedious task is performed by a human expert using a well log interpretation software, the expert needs to visualize and check all data channels one by one for its validity before summarizing all issues in a report provided to the logging service provider as feedback before the well log files are finalized for delivering to the operating company. Furthermore, the list of data channels is often tool specific and varies significantly among different tools. Therefore, it is not efficient and not consistent to rely on human expert to complete this task.
FIGS. 3A-3G show an example of systematically tackling the issue of validating data in DLIS or LAS deliverables in an automatic and rapid manner that covers various types of log measurements. The example is based on an automated software system and workflow that allows (i) flexible logging data tool/format support, such as DLIS, LAS, LIS, etc., (ii) unified data management, (iii) customizable data validation rules, (iv) data visualization and validation with interactive user interface, such as tables, log track, histograms, pie chart, etc., (v) data quality indicator, such as heat map for problematic channels and depth, and (vi) validation summary report in various format, such as HTML, PDF, etc. For example, the automated software system and workflow reduce the time to validate one DLIS file that has 100 data channels from hours to just several minutes, and may be automated to process a large quantities of logs with minimal human intervention.
FIG. 3A shows an example user interface panel (310) for uploading DLIS/LAS files and validation configuration file(s). As shown in FIG. 3A, the example user interface panel (310) includes an upload section (310 a), a delete section (310 b), and a display section (310 c). The upload section (310 a) provides input fields for the user to upload a validation configuration file and/or a DLIS file. The delete section (310 b) provides input fields for the user to delete (e.g., to flush cached data) previously uploaded validation configuration file and/or DLIS file. The display section (310 c) provides input fields for the user to select uploaded validation configuration file and/or DLIS file to be displayed or exported. An example validation configuration file is shown in TABLE 1 below that includes units and valid data value ranges for data channels. For example, the data channel XYZ corresponds to data measured in the unit of Kv (kilo-volt) and valid value range from 2 Kv to 4 Kv, the data channel XYZ1 corresponds to data measured in the unit of v (volt) and valid value range from 2000v to 4000v, and the data channel XYZ2 corresponds to data measured in the unit of mV (milli-volt) and valid value range from 2000000 mV to 4000000 mV. The example user interface panel (310) may be used to perform Step 200 depicted in FIG. 2 above.

TABLE 1

Name List	Unit List	Min value	Max value

XYZ, XYZ1,	Kv, v,	2, 2000,	4, 4000,
XYZ2, . . .	mV	2000000	4000000

FIG. 3B shows an example summary report (320) that describes how much data is valid in the DLIS/LAS well log data file. Within the example summary report (320), the summary scorecard (320 a) shows a score “80%” representing the percentage of well logs without any defects (i.e., good well logs), the pie chart (320 b) shows that the remaining well logs include a 13.3% sector of invalid well logs and a 6.67% sector of well logs with missing data in addition to the 80% sector of good well logs, and the dataset information (320 c) describes the DLIS/LAS well log data file that is validated. Each sector of the pie chart (320 b) may be highlighted (e.g., using hash patterns, colors, etc.) according to the legend (321). The summary report (320) is an example of the validation summary table generated by performing Step 204 depicted in FIG. 2 above.
FIG. 3C shows an example interactive visualization of data channels (330 a) in a DLIS/LAS well log data file. Within the list of data channels (330 a), each row corresponds to a particular data channel where the user can select to be displayed as a log track (330 b), a histogram (330 c), and a pie chart (330 d). Each of the log track (330 b), histogram (330 c), and pie chart (330 d) presents corresponding quality statistics with highlights (e.g., via hash patterns, colors, etc.) according to respective legends (331 b), (331 c), and (331 d). The example interactive visualization of the DLIS/LAS well log data file may be generated by performing Step 206 depicted in FIG. 2 above.
FIG. 3D shows an example validation data table (340) of a DLIS/LAS well log data file. Within the example validation data table (340), each row corresponds to a particular data channel where the user can browse various information such as the key, unit, minimum, maximum, mean values and description of the measurement data. The example data table (340) may be generated by performing Step 206 depicted in FIG. 2 above.
FIG. 3E shows an example heat map (350). Within the example heat map (350), each column corresponds to a particular data channel where quality score of each individual depth range is highlighted according to the legend (350 a). For example, the good quality score is considered as the highest value of the quality level. Specifically, the X-axis and Y-axis of the example heat map (350) correspond to the data channel identifier (i.e., tag) and depth, respectively. Additional data channels outside of the Y-axis display range of the heat map (350) may be scrolled horizontally into the Y-axis display range using the scroll bar (350 b). The example heat map (350) may be generated by performing Step 208 depicted in FIG. 2 above.
FIG. 3F shows an example validation report (360), which is a summary report (e.g., in HTML or PDF format) that archives the data validation results of all data channels. As shown in FIG. 3F, the example validation report (360) includes the summary report (360 a), the data table (360 b), and the heat map (360 c). For example, the summary report (360 a), the data table (360 b), and the heat map (360 c) may be organized in a similar format as the summary report (320), the data table (340), and the heat map (350) depicted in FIG. 3B, FIG. 3D, and FIG. 3E, respectively. The example validation report (360) may be generated by performing Step 210 depicted in FIG. 2 above.
FIG. 3G shows an example validation report (370), which is a detail summary report (e.g., in HTML or PDF format) for a selected data channel. As shown in FIG. 3G, the example validation report (370) includes a data table (370 a), a log track (370 b), a histogram (370 c), and a pie chart (370 d) that are specific to a particular data channel. For example, the data table (370 a), the log track (370 b), the histogram (370 c), and the pie chart (370 d) may be organized in a similar format as the data table (340), the log track (330 b), the histogram (330 c), and the pie chart (330 d) depicted in FIG. 3C and FIG. 3D above. The example validation report (370) may be generated by performing Step 210 depicted in FIG. 2 above.
Embodiments disclosed herein may be implemented on virtually any type of computing system, regardless of the platform being used. For example, the computing system may be one or more mobile devices (e.g., laptop computer, smart phone, personal digital assistant, tablet computer, or other mobile device), desktop computers, servers, blades in a server chassis, or any other type of computing device or devices that includes at least the minimum processing power, memory, and input and output device(s) to perform one or more embodiments. For example, as shown in FIG. 4 , the computing system (400) may include one or more computer processor(s) (402), associated memory (404) (e.g., random access memory (RAM), cache memory, flash memory, etc.), one or more storage device(s) (406) (e.g., a hard disk, an optical drive such as a compact disk (CD) drive or digital versatile disk (DVD) drive, a flash memory stick, etc.), and numerous other elements and functionalities. The computer processor(s) (402) may be an integrated circuit for processing instructions. For example, the computer processor(s) may be one or more cores, or micro-cores of a processor. The computing system (400) may also include one or more input device(s) (410), such as a touchscreen, keyboard, mouse, microphone, touchpad, electronic pen, or any other type of input device. Further, the computing system (400) may include one or more output device(s) (408), such as a screen (e.g., a liquid crystal display (LCD), a plasma display, touchscreen, cathode ray tube (CRT) monitor, projector, or other display device), a printer, external storage, or any other output device. One or more of the output device(s) may be the same or different from the input device(s). The computing system (400) may be connected to a network (412) (e.g., a local area network (LAN), a wide area network (WAN) such as the Internet, mobile network, or any other type of network) via a network interface connection (not shown). The input and output device(s) may be locally or remotely (e.g., via the network (412)) connected to the computer processor(s) (402), memory (404), and storage device(s) (406). Many different types of computing systems exist, and the aforementioned input and output device(s) may take other forms.
Software instructions in the form of computer readable program code to perform embodiments of the disclosure may be stored, in whole or in part, temporarily or permanently, on a non-transitory computer readable medium such as a CD, DVD, storage device, a diskette, a tape, flash memory, physical memory, or any other computer readable storage medium. Specifically, the software instructions may correspond to computer readable program code that when executed by a processor(s), is configured to perform embodiments disclosed herein.
Further, one or more elements of the aforementioned computing system (400) may be located at a remote location and be connected to the other elements over a network (412). Further, one or more embodiments may be implemented on a distributed system having a plurality of nodes, where each portion of the disclosure may be located on a different node within the distributed system. In one embodiment, the node corresponds to a distinct computing device. Alternatively, the node may correspond to a computer processor with associated physical memory. The node may alternatively correspond to a computer processor or micro-core of a computer processor with shared memory and/or resources.
While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this disclosure, will appreciate that other embodiments can be devised which do not depart from the scope of the disclosure as disclosed herein. Accordingly, the scope of the disclosure should be limited only by the attached claims.

Claims

What is claimed:

1. A method to perform a field operation with rapid well log validation, comprising:

generating, by performing well logging of a wellbore penetrating a subterranean formation in a field, a well log data file comprising a plurality of data channels, each data channel comprising a series of measurement data records representing a downhole property along a depth in the wellbore;

analyzing, by a computer processor, the plurality of data channels to determine a quality level of said each data channel;

categorizing, by the computer processor, the plurality of data channels according to respective values of the quality level to generate a validation summary of the well log data file;

presenting, using a graphical user interface, the validation summary to a user; and

facilitating, based on a user input in response to presenting the validation summary, the field operation.

2. The method of claim 1, further comprising:

obtaining, using the graphical user interface, a validation configuration file,

wherein determining the quality level of said each data channel is based on the validation configuration file.

3. The method of claim 1,

wherein generating the validation summary comprises generating a quality score corresponding to a percentage of the plurality of data channels having a highest value of the quality level.

4. The method of claim 1,

wherein analyzing the plurality of data channels comprising generating a validity designation of each measurement data record of said each data channel, and

wherein determining the quality level of each data channel comprises tallying the measurement data records of said each data channel according to the validity designation.

5. The method of claim 4, further comprising:

generating an interactive validation display that comprises:

a selection menu of the plurality of data channels, and

a pre-determined graphical representation of a selected data channel;

receiving a user selection from the selection menu to determine the selected data channel; and

generating the pre-determined graphical representation to represent one or more tallies of the measurement data records of the selected data channel according to the validity designation.

6. The method of claim 4, further comprising:

generating a validation heat map to represent the validity designation across the well log data file,

wherein an X-axis and a Y-axis correspond to a data channel identifier and the depth, respectively.

7. The method of claim 6,

wherein the validation summary comprises the validation heat map.

8. A data gathering and analysis system, comprising:

a computer processor; and

memory storing instructions, when executed, causing the computer processor to:

generate, by performing well logging of a wellbore penetrating a subterranean formation in a field, a well log data file comprising a plurality of data channels, each data channel comparing a series of measurement data records representing a downhole property along a depth in the wellbore;

analyze the plurality of data channels to determine a quality level of said each data channel;

categorize the plurality of data channels according to respective values of the quality level to generate a validation summary of the well log data file;

present, using a graphical user interface, the validation summary to a user; and

facilitate, based on a user input in response to presenting the validation summary, the field operation.

9. The data gathering and analysis system of claim 8, the instructions, when executed, further causing the computer processor to:

obtain, using the graphical user interface, a validation configuration file,

10. The data gathering and analysis system of claim 8,

11. The data gathering and analysis system of claim 8,

wherein determine the quality level of said each data channel comprises tallying the measurement data records of said each data channel according to the validity designation.

12. The data gathering and analysis system of claim 11, the instructions, when executed, further causing the computer processor to:

generate an interactive validation display that comprises:

a selection menu of the plurality of data channels, and

a pre-determined graphical representation of a selected data channel;

receive a user selection from the selection menu to determine the selected data channel; and

generate the pre-determined graphical representation to represent one or more tallies of the measurement data records of the selected data channel according to the validity designation.

13. The data gathering and analysis system of claim 11, the instructions, when executed, further causing the computer processor to:

generate a validation heat map to represent the validity designation across the well log data file,

14. The data gathering and analysis system of claim 13,

wherein the validation summary comprises the validation heat map.

15. A system comprising:

a wellsite having a wellbore penetrating a subterranean formation in a field; and

a data gathering and analysis system comprising functionality for:

generating, by performing well logging of the wellbore, a well log data file comprising a plurality of data channels, each data channel comparing a series of measurement data records representing a downhole property along a depth in the wellbore;

categorizing, by the compute processor, the plurality of data channels according to respective values of the quality level to generate a validation summary of the well log data file;

16. The system of claim 15, the data gathering and analysis system further comprising functionality for:

obtaining, using the graphical user interface, a validation configuration file,

17. The system of claim 15,

18. The system of claim 15,

19. The system of claim 18, the data gathering and analysis system further comprising functionality for:

generating an interactive validation display that comprises:

a selection menu of the plurality of data channels, and

a pre-determined graphical representation of a selected data channel;

20. The system of claim 18, the data gathering and analysis system further comprising functionality for: