Patent Description:
The following documents describe known automatic well log depth matching methods: <CIT>; <CIT>; <CIT>; <CIT>; <CIT>; <NPL> ; <NPL>; <NPL>; <NPL>; and<NPL>.

The present invention resides in a method as defined in claim <NUM> and a computing system as defined in claim <NUM>.

The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the description of the invention and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term "and/or" as used herein refers to and encompasses any possible combinations of one or more of the associated listed items. It will be further understood that the terms "includes," "including," "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Further, as used herein, the term "if" may be construed to mean "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context.

<FIG> illustrate simplified, schematic views of oilfield <NUM> having subterranean formation <NUM> containing reservoir <NUM> therein in accordance with implementations of various technologies and techniques described herein. <FIG> illustrates a survey operation being performed by a survey tool, such as seismic truck <NUM>, to measure properties of the subterranean formation. The survey operation is a seismic survey operation for producing sound vibrations. In <FIG>, one such sound vibration, e.g., sound vibration <NUM> generated by source <NUM>, reflects off horizons <NUM> in earth formation <NUM>. A set of sound vibrations is received by sensors, such as geophone-receivers <NUM>, situated on the earth's surface. The data received <NUM> is provided as input data to a computer <NUM> of a seismic truck <NUM>, and responsive to the input data, computer <NUM> generates seismic data output <NUM>. This seismic data output may be stored, transmitted or further processed as desired, for example, by data reduction.

<FIG> illustrates a drilling operation being performed by drilling tools <NUM> suspended by rig <NUM> and advanced into subterranean formations <NUM> to form wellbore <NUM>. Mud pit <NUM> is used to draw drilling mud into the drilling tools via flow line <NUM> for circulating drilling mud down through the drilling tools, then up wellbore <NUM> and back to the surface. The drilling mud is typically filtered and returned to the mud pit. A circulating system may be used for storing, controlling, or filtering the flowing drilling mud. The drilling tools are advanced into subterranean formations <NUM> to reach reservoir <NUM>. Each well may target one or more reservoirs. The drilling tools are adapted for measuring downhole properties using logging while drilling tools. The logging while drilling tools may also be adapted for taking core sample <NUM> as shown.

Typically, the wellbore is drilled according to a drilling plan that is established prior to drilling. The drilling plan typically sets forth equipment, pressures, trajectories and/or other parameters that define the drilling process for the wellsite. The drilling operation may then be performed according to the drilling plan. However, as information is gathered, the drilling operation may need to deviate from the drilling plan. Additionally, as drilling or other operations are performed, the subsurface conditions may change. The earth model may also need adjustment as new information is collected.

Surface unit <NUM> may include transceiver <NUM> to allow communications between surface unit <NUM> and various portions of the oilfield <NUM> or other locations. Surface unit <NUM> may also be provided with or functionally connected to one or more controllers (not shown) for actuating mechanisms at oilfield <NUM>. Surface unit <NUM> may then send command signals to oilfield <NUM> in response to data received. Surface unit <NUM> may receive commands via transceiver <NUM> or may itself execute commands to the controller. A processor may be provided to analyze the data (locally or remotely), make the decisions and/or actuate the controller. In this manner, oilfield <NUM> may be selectively adjusted based on the data collected. This technique may be used to optimize (or improve) portions of the field operation, such as controlling drilling, weight on bit, pump rates, or other parameters. These adjustments may be made automatically based on computer protocol, and/or manually by an operator. In some cases, well plans may be adjusted to select optimum (or improved) operating conditions, or to avoid problems.

As shown, the sensor (S) may be positioned in production tool <NUM> or associated equipment, such as Christmas tree <NUM>, gathering network <NUM>, surface facility <NUM>, and/or the production facility, to measure fluid parameters, such as fluid composition, flow rates, pressures, temperatures, and/or other parameters of the production operation.

Data plots <NUM>-<NUM> are examples of static data plots that may be generated by data acquisition tools <NUM>-<NUM>, respectively; however, it should be understood that data plots <NUM>-<NUM> may also be data plots that are updated in real time. These measurements may be analyzed to better define the properties of the formation(s) and/or determine the accuracy of the measurements and/or for checking for errors. The plots of each of the respective measurements may be aligned and scaled for comparison and verification of the properties.

Static data plot <NUM> is a seismic two-way response over a period of time. Static plot <NUM> is core sample data measured from a core sample of the formation <NUM>. The core sample may be used to provide data, such as a graph of the density, porosity, permeability, or some other physical property of the core sample over the length of the core. Tests for density and viscosity may be performed on the fluids in the core at varying pressures and temperatures. Static data plot <NUM> is a logging trace that typically provides a resistivity or other measurement of the formation at various depths.

A production decline curve or graph <NUM> is a dynamic data plot of the fluid flow rate over time. The production decline curve typically provides the production rate as a function of time. As the fluid flows through the wellbore, measurements are taken of fluid properties, such as flow rates, pressures, composition, etc..

While a specific subterranean formation with specific geological structures is depicted, it will be appreciated that oilfield <NUM> may contain a variety of geological structures and/or formations, sometimes having extreme complexity. In some locations, typically below the water line, fluid may occupy pore spaces of the formations. Each of the measurement devices may be used to measure properties of the formations and/or its geological features. While each acquisition tool is shown as being in specific locations in oilfield <NUM>, it will be appreciated that one or more types of measurement may be taken at one or more locations across one or more fields or other locations for comparison and/or analysis.

The data collected from various sources, such as the data acquisition tools of <FIG>, may then be processed and/or evaluated. Typically, seismic data displayed in static data plot <NUM> from data acquisition tool <NUM> is used by a geophysicist to determine characteristics of the subterranean formations and features. The core data shown in static plot <NUM> and/or log data from well log <NUM> are typically used by a geologist to determine various characteristics of the subterranean formation. The production data from graph <NUM> is typically used by the reservoir engineer to determine fluid flow reservoir characteristics. The data analyzed by the geologist, geophysicist and the reservoir engineer may be analyzed using modeling techniques.

<FIG> illustrates an oilfield <NUM> for performing production operations in accordance with implementations of various technologies and techniques described herein. As shown, the oilfield has a plurality of wellsites <NUM> operatively connected to central processing facility <NUM>. The oilfield configuration of <FIG> is not intended to limit the scope of the oilfield application system. Part, or all, of the oilfield may be on land and/or sea. Also, while a single oilfield with a single processing facility and a plurality of wellsites is depicted, any combination of one or more oilfields, one or more processing facilities and one or more wellsites may be present.

Attention is now directed to <FIG>, which illustrates a side view of a marine-based survey <NUM> of a subterranean subsurface <NUM> in accordance with one or more implementations of various techniques described herein. Subsurface <NUM> includes seafloor surface <NUM>. Seismic sources <NUM> may include marine sources such as vibroseis or airguns, which may propagate seismic waves <NUM> (e.g., energy signals) into the Earth over an extended period of time or at a nearly instantaneous energy provided by impulsive sources. The seismic waves may be propagated by marine sources as a frequency sweep signal. For example, marine sources of the vibroseis type may initially emit a seismic wave at a low frequency (e.g., <NUM>) and increase the seismic wave to a high frequency (e.g., <NUM>-<NUM>) over time.

The component(s) of the seismic waves <NUM> may be reflected and converted by seafloor surface <NUM> (i.e., reflector), and seismic wave reflections <NUM> may be received by a plurality of seismic receivers <NUM>. Seismic receivers <NUM> may be disposed on a plurality of streamers (i.e., streamer array <NUM>). The seismic receivers <NUM> may generate electrical signals representative of the received seismic wave reflections <NUM>. The electrical signals may be embedded with information regarding the subsurface <NUM> and captured as a record of seismic data.

In one implementation, seismic wave reflections <NUM> may travel upward and reach the water/air interface at the water surface <NUM>, a portion of reflections <NUM> may then reflect downward again (i.e., sea-surface ghost waves <NUM>) and be received by the plurality of seismic receivers <NUM>. The sea-surface ghost waves <NUM> may be referred to as surface multiples. The point on the water surface <NUM> at which the wave is reflected downward is generally referred to as the downward reflection point.

The electrical signals may be transmitted to a vessel <NUM> via transmission cables, wireless communication or the like. The vessel <NUM> may then transmit the electrical signals to a data processing center. Alternatively, the vessel <NUM> may include an onboard computer capable of processing the electrical signals (i.e., seismic data). Those skilled in the art having the benefit of this disclosure will appreciate that this illustration is highly idealized. For instance, surveys may be of formations deep beneath the surface. The formations may typically include multiple reflectors, some of which may include dipping events, and may generate multiple reflections (including wave conversion) for receipt by the seismic receivers <NUM>. In one implementation, the seismic data may be processed to generate a seismic image of the subsurface <NUM>.

Marine seismic acquisition systems tow each streamer in streamer array <NUM> at the same depth (e.g., <NUM>-<NUM>). However, marine based survey <NUM> may tow each streamer in streamer array <NUM> at different depths such that seismic data may be acquired and processed in a manner that avoids the effects of destructive interference due to sea-surface ghost waves. For instance, marine-based survey <NUM> of <FIG> illustrates eight streamers towed by vessel <NUM> at eight different depths. The depth of each streamer may be controlled and maintained using the birds disposed on each streamer.

<FIG> illustrates a flowchart of a method <NUM> for pre-processing wellbore data, according to an embodiment. The method <NUM> may include receiving a well log, as at <NUM>. The well log may include one or more signals that represent measurements taken by sensors in the well. The method <NUM> may also include identifying and removing one or more constants (e.g., straight-lines) from the signal in the well log, as at <NUM>. The method <NUM> may also include identifying and removing inconsistent and/or noisy portions from the signal in the well log, as at <NUM>. Thus, the systems and methods disclosed herein may provide a unified framework that detects and/or removes constants, inconsistent data, noisy data, or a combination thereof from the well log.

<FIG> illustrates a flowchart of a method <NUM> for detecting and/or removing statistically aberrant signal regions in a well log, according to an embodiment. The method <NUM> is illustrated with reference to <FIG>, <FIG>, and <FIG> and <FIG>. Different portions of the method <NUM> are illustrated on different well logs (e.g., different signals) for clarity. More particularly, the portion of the method <NUM> directed to the detection and removal of inconsistent measurements is illustrated in <FIG> and <FIG>, and the portion of the method <NUM> directed to the detection and removal of constants (e.g., straight lines) is illustrated in <FIG>, <FIG> and <FIG>. However, in another embodiment, one or more portions of the method <NUM> may also or instead be performed with respect to a single well log (e.g., a single signal).

<FIG> illustrates an example of a well log 600A including a signal 610A that has inconsistent and/or noisy data, according to an embodiment. The well log 600A may be or include a gamma ray log, a resistivity log, a sonic log, a neutron log, a density log, a pressure log, a temperature log, or the like. The signal 610A in the well log 600A may represent measurements taken using one or more sensors configured to measure gamma rays, resistivity, etc. Such measurement data (and thus the signal 610A) thus provide data representing one or more subsurface rock properties. The signal 610A includes a plurality of samples (e.g., discrete points).

The method <NUM> may be used to detect and/or remove inconsistent data, noisy data, constants (e.g., straight-lines), or a combination thereof. More particularly, referring now to <FIG> and <FIG>, the method <NUM> may be used to detect and/or remove inconsistent and/or noisy data in a first (e.g., beginning) portion 602A and/or a second (e.g., end) portion 604A of the signal 610A. An illustrative order of the method <NUM> is provided below; however, one or more portions of the method <NUM> may be performed in a different order, performed simultaneously, repeated, or omitted.

The method <NUM> may include receiving a well log 600A, as at <NUM>. The well log 600A may be captured in a wellbore by a downhole tool, such as any of the downhole tools <NUM>-<NUM> and/or the downhole tools <NUM>-<NUM> described above.

The method <NUM> may also include selecting a first (e.g., beginning) portion 602A of the signal 610A in the well log 600A, as at <NUM>. This may include selecting a first n samples (e.g., <NUM> samples) of the signal 610A. As shown, the beginning portion 602A may represent a depth range (e.g., from about <NUM> to about <NUM>). In another embodiment, the beginning portion 602A may represent a time range (e.g., from about <NUM> minutes to about <NUM> minutes).

The method <NUM> may also include identifying a first change point 640A in the signal 610A, as at <NUM>. The first change point 640A may be identified in the beginning portion 602A of the signal 610A. As may be seen in <FIG>, the first change point 640A may demarcate a first signal region 620A before/above the first change point 640A and a second signal region 630A after/below the first change point 640A. In this particular example, the first signal region 620A represents a depth from about <NUM> to about <NUM>, the change point 640A exists at a depth of about <NUM>, and the second signal region 630A represents a depth from about <NUM> to about <NUM>.

In at least one embodiment, the first change point 640A may be determined using a change point detection algorithm. The change point detection algorithm estimates the point(s) (e.g., point 640A) in the signal 610A at which the statistical properties of a sequence of observations change (e.g., a mean or a variance). In other words, the change point 640A may be or include the point where the signal 610A jumps (e.g., in amplitude) by a predetermined amount. For example, the amplitude of the signal in the first signal region 620A (e.g., before the change point 640A) is from about <NUM> to about <NUM>. The amplitude of the signal 610A then jumps at the change point 640A to from about <NUM> to about <NUM> in the second signal region 630A (e.g., after the change point 640A).

Examples of change point detection algorithms include a binary segmentation algorithm, a segment neighborhood algorithm, and the Pruned Exact Linear Time (PELT) algorithm. One existing challenge in applying a change point detection algorithm to a signal is estimating the number of change points to identify. In one embodiment, the method <NUM> may use/determine a single change point (e.g., not multiple change points) for the beginning portion 602A of the signal 610A, and a single change point for the end portion of the signal 610A. An example of applying a change point detection algorithm to the beginning portion 602A of the signal 610A to determine the first change point 640A is provided below.

A log measurement sequence of the signal 610A may be defined as follows: <MAT> where y is the signal 610A, and n is a user input that represents the size of the log measurement(s) to consider (e.g., the n-first samples or the n-last samples). The change point detection algorithm may be used to select a segmentation index k (<NUM> < k < n) where k represents the change point 640A between <NUM> (or <NUM>) and n. The signal 610A may be split at the change point 640A according to a quantitative criterion V(k,y): <MAT> where V is a cost function to be optimized (e.g., minimized), and c is a cost function that measures a goodness-of-fit of a subset of the signal 610A. Thus, the position k may be found where V is the minimum. The cost function c may measure the "homogeneity" of a subsequence. The quadratic error loss cost function may be defined as follows: <MAT> where y<NUM>:k is the empirical mean of the sub-signal from <NUM> to k. To perform the segmentation, the quantitative criterion V(k,y) may be minimized. The k* optimal index is the one that minimizes the quantitative criteria: <MAT> Where k* is an optimum position where V is the minimum. Thus, k* is considered to be the change point.

The method <NUM> may also include determining that the first signal region 620A is inconsistent in comparison with the second signal region 630A, as at <NUM>. In at least one embodiment, this may also or instead include determining that the first signal region 620A is noisy (e.g., in comparison with the second signal region 630A).

In at least one embodiment, determining whether the first signal region 620A is inconsistent in comparison to the second signal region 630A may include determining a mean 622A of the first signal region 620A (y<NUM>:k) and a mean 632A of the second signal region 630A (yk*:n), as shown below: <MAT>.

The first signal region 620A (samples <NUM> to k* in the signal 610A) is determined to be inconsistent in comparison to the second signal region 630A (samples k* to n) in response to the mean 622A of the first signal region 620A being out of bounds, as shown by one or both equations below: <MAT> <MAT> where m is a user input (e.g., which may be set by default to <NUM>) representing where the signal is rejected in a Gaussian distribution, and σ(yk*:n) is the empirical standard deviation of the sub signal yk*:n, which may yield the upper and lower bounds 634A, 636A. In one example, if m is set to <NUM>, there may be <NUM>% of the samples that verify the condition of Equation <NUM>.

In other words, Equation <NUM> states that the first signal region 620A is inconsistent in response to the mean 622A of the first signal region 620A being less than the mean 632A of the second signal region 630A minus a product. The product is the user input m (e.g., <NUM>) multiplied by the empirical standard deviation of the second signal region 630A. Equation <NUM> states that the first signal region 620A is inconsistent in response to the mean 622A of the first signal region 620A being greater than the mean 632A of the second signal region 630A plus the product.

In at least one embodiment, if the mean 622A of the signal 610A in the first signal region 620A is not between the bounds 634A, 636A, the first signal region 620A may be determined to be inconsistent in comparison to the second signal region 630A (e.g., an anomaly is detected in the first signal region 620A). In another embodiment, if a predetermined portion (e.g., <NUM>%) of the signal 610A in the first signal region 620A is not between the bounds 634A, 636A, the first signal region 620A may be determined to be inconsistent in comparison to the second signal region 630A (e.g., an anomaly is detected in the first signal region 620A).

In at least one embodiment, this approach may also be used to identify a change point in two or more (e.g., simultaneous) signals. For example, the following may be used: <MAT> where y takes value in <MAT>, and <MAT> is the inverse of the covariance matrix of the signal 610A, and d is the number of signals (e.g., two or more signals).

<FIG> illustrates an example of a well log <NUM> including beginning portions <NUM> of two (e.g., simultaneous) signals 710A, 710B, according to an embodiment. The first signal region <NUM> is from about <NUM> to about <NUM>, the change point <NUM> exists at about <NUM>, and the second signal region <NUM> is from about <NUM> to about <NUM>.

The method <NUM> may also include producing a modified well log, as at <NUM>. <FIG> illustrates a modified well log 800A (e.g., a modified version of the well log 600A in <FIG>), according to an embodiment. In one embodiment, the modified well log 800A may be produced by removing the first signal region 620A from the signal 610A in response to determining that the first signal region 620A is inconsistent in comparison to the second signal region 630A. In the modified well log 800A, the first signal region 620A of the signal 610A (e.g., from a depth of about <NUM> to about <NUM>) has been removed.

To illustrate this portion of the method <NUM>, <FIG> illustrates another well log 600B including another (e.g., different) signal 610B, and <FIG> illustrates a derivative signal 610C (e.g., a derivative of the signal 610B), according to an embodiment. However, as mentioned above, this portion of the method <NUM> may also or instead be performed on the signal 610A in the well log 600A.

The method <NUM> may also include producing a derivative signal 610C by calculating a derivative of at least a portion of the signal 610B, as at <NUM>. The method <NUM> may also include identifying a second change point 640C in the derivative signal 610C, as at <NUM>. The second change point 640C may be identified in a beginning portion 602C of the of the derivative signal 610C. The second change point 640C may demarcate a third signal region 620C before/above the second change point 640C and a fourth signal region 630C after/below the second change point 640C. In this example, the third signal region 620C may represent a depth from about <NUM> to about <NUM>, the second change point 640C may represent a depth of about <NUM>, and the fourth signal region 630C may represent a depth from a depth from about <NUM> to about <NUM>. The second change point 640C may be determined using a change point detection algorithm (e.g., the same algorithm used above).

The method <NUM> may also include determining that the third signal region 620C has a value of substantially zero, as at <NUM>. The value that is substantially zero may be or include the amplitude (e.g., on the Y-axis). For example, as used herein, the term "substantially zero" may refer to an amplitude that is within the range of -<NUM> and <NUM> or within the range of -<NUM> and <NUM>. The value that is substantially zero may also or instead be the slope. Thus, as shown in <FIG>, the third signal region 620C may be substantially horizontal. In at least one embodiment, the third signal region 620C of the derivative signal 610C may include a value of substantially zero in response to the following: <MAT> where <MAT> is the empirical standard deviation of the third signal region 620C in the derivative signal 610C (e.g., from <NUM> to k*), and ε is a user input scalar (e.g., set to a small value such as 1e-<NUM> or 1e-<NUM>). The third signal region 620C of the derivative signal 610C having a value of substantially zero may indicate that the corresponding third signal region 620B (e.g., from a depth of about <NUM> to about <NUM>) in the original signal 610B (see <FIG>) includes a constant (e.g., straight-line) 622B. This is because the derivative of a constant is zero. The third signal region 620B of the original signal 610B including the constant (e.g., straight-line) 622B may indicate that the third signal region 620B of the original signal 610B contains an anomaly or is otherwise inaccurate.

The method <NUM> may also include producing a modified well log, as at <NUM>. <FIG> illustrates a modified well log 800B (e.g., a modified version of the well log 600B in <FIG>), according to an embodiment. In one embodiment, the modified well log 800B may be produced by removing the third signal region 620B (e.g., from about <NUM> to about <NUM>) from the signal 610B in response to determining that the third signal region 620C of the derivative signal 610C has a value of substantially zero. As mentioned above, this portion of the method <NUM> is illustrated using a different well log 600B and a different modified well log 800B for clarity; however, in other embodiments, this portion of the method <NUM> may also or instead be performed using the well log 600A and/or the modified well log 800A. Thus, this step may also or instead be directed to adjusting the modified well log 800A.

Referring back to <FIG> and <FIG>, one or more portions of the method <NUM> may be repeated for the second (e.g., end) portion 604A of the signal 610A. For example, the method <NUM> may also include selecting the second (e.g., end) portion 604A of the signal 610A in the well log 600A, as at <NUM>. This may include selecting the last n samples (e.g., the last <NUM> samples) of the signal 610A. Referring again to <FIG>, the end portion 604A may represent a depth range (e.g., from about <NUM> to about <NUM>). In an example, the samples may be spaced apart by about <NUM>.

The method <NUM> may also include identifying a third change point 670A in the signal 610A, as at <NUM>. The third change point 670A may be identified in the end portion 604A of the signal 610A. As may be seen in <FIG>, the third change point 670A may demarcate a fifth signal region 650A before/above the third change point 670A and a sixth signal region 660A after/below the third change point 670A. In this particular example, the fifth signal region 650A represents a depth from about <NUM> to about <NUM>, the third change point 670A represents a depth of about <NUM>, and the sixth signal region 660A represents a depth from about <NUM> to about <NUM>. In at least one embodiment, the third change point 670A may be determined using a change point detection algorithm (e.g., the same algorithm discussed above).

The method <NUM> may also include determining that the sixth signal region 660A is inconsistent in comparison with the fifth signal region 650A, as at <NUM>. This may also or instead include determining that the sixth signal region 660A is noisy in comparison to the fifth signal region 650A.

The sixth signal region 660A (e.g., samples k* to n in the signal 610A) is determined to be inconsistent with respect to the fifth signal region 650A (e.g., samples from <NUM> to k* in the signal 610A) in response to one or both of the following: <MAT> <MAT>.

In other words, Equation <NUM> states that the sixth signal region 660A is inconsistent in response to a mean 662A of the sixth signal region 660A being less than a mean 632A of the fifth signal region 650A minus a product. The product is the user input (e.g., <NUM>) multiplied by the empirical standard deviation of the fifth signal region 650A. Equation <NUM> states that the sixth signal region 660A is inconsistent in response to the mean 662A of the sixth signal region 660A being less than the mean 632A of the fifth signal region 650A plus the product.

The method <NUM> may also include adjusting the modified well log 800A, as at <NUM>. In one embodiment, the modified well log <NUM> may be adjusted by removing the sixth signal region 660A from the signal 610A in response to determining that the sixth signal region 660A is inconsistent in comparison to the fifth signal region 650A.

The method <NUM> may also include identifying a fourth change point 670C in the derivative signal 610C, as at <NUM>. As shown in <FIG>, the fourth change point 670C may be identified in an end portion 604C of the of the derivative signal 610C. The fourth change point 670C may demarcate a seventh signal region 650C before/above the fourth change point 670C and an eighth signal region 660C after/below the fourth change point 670C. In this particular example, the seventh signal region 650C represents a depth from about <NUM> to about <NUM>, the fourth change point 670C exists at a depth of about <NUM>, and the eighth signal region 660C represents a depth from about <NUM> to about <NUM>. In at least one embodiment, the fourth change point 670C may be determined using a change point detection algorithm (e.g., the same algorithm discussed above).

The method <NUM> may also include determining that the eighth signal region 660C has a value of substantially zero, as at <NUM>. The eighth signal region 660C is determined to have a value of substantially zero in response to the following: <MAT> where <MAT> is the empirical standard deviation of the eighth signal region 660C of the derivative signal 610C (e.g., from k* to n). The eighth signal region 660C of the derivative signal 610C having a value of substantially zero may indicate that the corresponding eighth signal region 6b0B (e.g., from a depth of about <NUM> to about <NUM>) in the original signal 610B (see <FIG>) includes a constant (e.g., straight-line) 662B. This is because the derivative of a constant is zero. The eighth signal region 660B of the original signal 610B including the constant (e.g., straight-line) 662B may indicate that the eighth signal region 660B of the original signal 610B contains an anomaly or is otherwise inaccurate.

The method <NUM> may also include adjusting the modified well log 800B, as at <NUM>. In one embodiment, the modified well log 800B may adjusted by removing the eighth signal region 660B (e.g., from about <NUM> to about <NUM>) from the signal 610B in response to determining that the eighth signal region 660C of the derivative signal 610C has a value that is substantially zero.

In response to the modified well log 800A, 800B, one or more wellsite actions may occur. In one embodiment, the wellsite actions may be or include varying a drilling plan for the current wellbore or future wellbores. The drilling plan may be or include the location and/or trajectory. The wellsite action may also or instead include transmitting a signal (e.g., from the computing system) to steer the downhole tool, vary the weight on the bit (WOB), vary the drilling fluids pumped into the wellbore, vary the composition of the drilling fluids pumped into the wellbore, or a combination thereof.

<FIG> illustrates an example of a first well log 900A and a second well log 900B, according to an embodiment. Although not shown, in at least one embodiment, the first well log 900A and/or the second well log 900B may be or include the well log 600A described above (e.g., either before or after the method <NUM> has been performed).

The first and second well logs 900A, 900B may be captured by any of the tools <NUM>-<NUM> and/or the tools <NUM>-<NUM> described above. The first and second well logs 900A, 900B may be captured in the same wellbore or in two different wellbores. The first and second well logs 900A, 900B may be captured in the same run or in two different runs. The first well log 900A may be captured before, simultaneously with, or after the second well log 900B. The first and second well logs 900A, 900B may be the same type of well log or different types of well logs. For example, the first well log 900A, the second well log 900B, or both may be or include gamma ray logs, resistivity logs, sonic logs, neutron logs, density logs, pressure logs, temperature logs, or the like.

In the embodiment shown, the first and second well logs 900A, 900B may include similar data (e.g., signals) 910A, 910B; however, the signals 910A, 910B in the first and second well logs 900A, 900B may be at least partially offset from one another with respect to depth. As an illustrative example, the first and second signals 910A, 910B may each include peaks 912A, 912B that correspond to the same portion of the subterranean formation (e.g., the same reservoir or fault); however, the peaks 912A, 912B are shown at different depths.

<FIG> illustrates a flowchart of a method <NUM> for aligning (e.g., depth-matching) the signals 910A, 910B in the first and second well logs 900A, 900B, according to an embodiment. not encompassed by the wording of the claims. An illustrative order of the method <NUM> is provided below; however, one or more portions of the method <NUM> may be performed in a different order, performed simultaneously, repeated, or omitted. In at least one embodiment, the method <NUM> may be applied to one or both of the well logs 900A, 900B prior to one or more portions of the method <NUM> being performed. In another embodiment, the method <NUM> may be applied to one or both of the well logs 900A, 900B after one or more portions of the method <NUM> are performed.

The method <NUM> may include receiving the first well log 900A and the second well log 900B, as at <NUM>. If the first well log 900A has already been received (e.g., at <NUM>), this may include receiving the second well log 900B. In this method <NUM>, the second well log 900B may be modified to become aligned with the first well log 900A. For example, the second well log 900B may be modified such that the peaks (e.g., peak 912B) become located at the same depth as the corresponding peaks (e.g., peak 912A) in the first well log 900A. Thus, the first well log 900A may serve as a reference well log.

The method <NUM> may also include identifying one or more change points (also referred to as anchors) in the first well log 900A and one or more change points in the second well log 900B, as at <NUM>. As shown in <FIG>, the signal 910A in the first well log 900A includes one or more change points (three are shown: 914A-916A), and the signal 910B in the second well log 900B includes one or more corresponding change points (three are shown: 914B-916B).

In one embodiment, a change point detection algorithm may be applied to the first well log 900A and the second well log 900B to identify the change points 914A-916A, 914B-916B. The change point detection algorithm may be the same algorithm described above with reference to <FIG>, or it may be a different algorithm. By using the change point detection algorithm (e.g., a binary segmentation algorithm), a predetermined number of change points 914A-916A, 914B-916B may be identified. A plurality of change points 914A-916A, 914B-916B may be identified to avoid large stretches of the signal.

The change points 914A, 914B may correspond to the same portion of the subterranean formation (e.g., a change in the subterranean formation), the change points 915A, 915B may correspond to the same portion of the subterranean formation (e.g., the same reservoir or fault), and the change points 916A, 916B may correspond to the same portion of the subterranean formation (e.g., the same reservoir or fault). As may be seen, the change points 916A, 916B are located at substantially the same depth; however, the change points 914A, 914B and the change points 915A, 915B are located at different depths. The following portions of the method <NUM> may thus include modifying the signal 910B in the second well log 900B so that the change points 914B-916B in the signal 910B in the second well log 900B become aligned with the change points 914A-916A in the signal 910A in the first well log 900A.

The method <NUM> may also include selecting a second change point 914B of the one or more change points 914B-916B in the second well log 900B based at least partially upon a proximity in depth to a first change point 914A of the one or more change points 914A-916A in the first well log 900A, as at <NUM>. In one embodiment, the phrase "based at least partially upon a proximity in depth" may refer to being the closest in depth. For example, the change point 914B is closer in depth than the change points 915B, 916B to the change point 914A. In at least one embodiment, portion of the method <NUM> may be performed in reverse by identifying a first change point 914A of the one or more change points 914A-916A in the first well log 900A based at least partially upon a proximity in depth to a second change point 914B of the one or more change points 914B-916B in the second well log 900B.

This may be done for each of the change points 914A-916A in the first well log 900A. This may also or instead be done for each of the change points 914B-916B in the second well log 900B. For example, the change point 914B in the second well log 900B is determined to be closest in depth to the change point 914A in the first well log 900A, the change point 915B in the second well log 900B is determined to be closest in depth to the change point 915A in the first well log 900A, and the change point 916B in the second well log 900B determined to be closest in depth to the change point 916A in the first well log 900A.

The method <NUM> may also include positioning a first window 920A at a first location within the first well log 900A, as at <NUM>. <FIG> illustrates a first window 920A in the first well log 900A, and a second window 920B in the second well log 900B, according to an embodiment. The windows 920A, 920B in the example in <FIG> are positioned proximate to the change points 914A, 914B, respectively. The size (e.g., depth) of the windows 920A, 920B may be selected by a user. For example, the size of the windows 920A, 920B may be <NUM> meters.

The change point 914A may be within the first window 920A when the first window 920A is positioned at the first location. For example, the change point 914A may be centered within the first window 920A when the first window 920A is positioned at the first location.

The method <NUM> may also include positioning a second window 920B at a second location within the second well log 900B, as at <NUM>. The second location may be based at least partially upon the change point 914B.

The method <NUM> may also include determining a first similarity value between the signal 910A in the first window 920A at the first location and the signal 910B in the second window 920B at the second location, as at <NUM>. In other words, the first window 920A may be positioned at the first location during the determination of the similarity values, and the second window 920B may be positioned at the second location during the determination of the first similarity value.

The method <NUM> may also include repositioning the second window 920B at a third location within the second well log 900B, as at <NUM>. Thus, the second window 920B may be a sliding window that may be moved up and/or down to determine the location with the highest similarity value, as described below. The third location may be based at least partially upon the change point 914B. The different locations (e.g., the second location, the third location, etc.) may be or include different depths. The second location may be above or below the third location. The second window 920B in the second location may at least partially overlap the second window 920B in the third location, or there may be no overlap. The different locations (e.g., different depths) may be within a predetermined range determined by a user. For example, the second window 920B may move up and/or down +/- <NUM> with respect to the change point 914B.

In one embodiment, the change point 914B may be within the second window 920B when the second window 920B is positioned at one or more of the plurality of different locations. For example, the change point 914B may be centered within the second window 920B at a first of the locations, and the change point 914B may be in an upper portion (or lower portion) of the second window 920B at a second of the locations. In another embodiment, the change point 914B may be outside of the second window 920B when the second window 920B is positioned at one or more of the plurality of different locations.

The method <NUM> may also include determining a second similarity value between the signal 910A in the first window 920A at the first location and the signal 910B in the second window 920B at the third location, as at <NUM>. In other words, the first window 920A may remain positioned at the first location during the determination of the similarity values, and the second window 920B may be positioned at the third location during the determination of the second similarity value. The similarity values may be determined by comparing a subsequence of n samples (e.g., <NUM> samples) of the portion of the signal 910A in the first window 920A to a subsequence of n samples of the portion of the signal 910B in the second window 920B. As will be appreciated, the second window 920B may be positioned at more than two locations, and in this instance, more than two similarity values may be determined.

The method <NUM> may also include selecting the second location or the third location of the second window 920B, as at <NUM>. The selected location may be based at least partially upon the similarity values. For example, this may include selecting the location of the second window 920B having the highest similarity value. In <FIG>, the line 934B represents a center of the second window 920B when the second window 920B is at the location with the highest similarity value. In other words, at this location, the signal 910B in the second window 920B is most similar to the signal 910A in the first window 920A.

The method <NUM> may also include determining a modified second change point 934B, as at <NUM>. The modified second change point 934B may also or instead be referred to as an anchor because it may not be determined using a change point algorithm. The modified second change point <NUM> may be determined based at least partially upon one or more of the similarity values (e.g., determined at <NUM> and <NUM>), the selected location (e.g., determined at <NUM>), or a combination thereof. The modified second change point <NUM> may correspond to the first change point 914A better than the second change point 914B corresponds to the first change point 914A.

The method <NUM> may also include producing a modified second well log 1200B, as at <NUM>. <FIG> illustrates the first well log 900A, the second well log 900B, and the modified second well log 1200B, according to an embodiment. The modified second well log 1200B may be produced based at least partially upon one or more of the similarity values (e.g., determined at <NUM> and <NUM>), the selected location (e.g., determined at <NUM>), the modified second change point 934B (e.g., determined at <NUM>), or a combination thereof.

In one embodiment, modifying the second well log 900B to produce the modified second well log 1200B may include determining differences between the depths in the first well log 900A and the corresponding depths in the second well log 900B and/or the modified second well log 1200B, and then applying an outlier detection algorithm to remove the possible aberrant depth shifts therebetween. Thus, modifying the second well log 900B may include shifting one or more portions of the second well log 900B (e.g., the signal 910B) up or down. Modifying the second well log 900B may also or instead include stretching or compressing one or more portions of the second well log 900B (e.g., the signal 910B). As may be seen, the modified second well log 1200B is better aligned with the first well log 900A than the second well log 900B is with the first well log 900A.

Table <NUM> below provides an example of modified change points. More particularly, the left column represents the depth of the change points (e.g., change points 914A-916A) in the first (i.e., reference) well log 900A. The middle column represents the depth of the modified change points (e.g., modified change point 934B). The right column represents the difference in depth between the left column and the middle column. The repeated values of the depth difference provide confidence in the alignment of the change points in the first well log 900A and the corresponding modified second well log 1200B.

One or more portions (e.g., <NUM>-<NUM>) of the method <NUM> may be repeated (e.g., for each change point 915B, 916B, etc.) in the second well log 900B to adjust the modified second well log 1200B.

In response to the modified second well log 1200B, one or more wellsite actions may occur. In one embodiment, the wellsite actions may be or include varying a drilling plan for the current wellbore or future wellbores. The drilling plan may be or include the location and/or trajectory. The wellsite action may also or instead include transmitting a signal (e.g., from the computing system) to steer the downhole tool, vary the weight on the bit (WOB), vary the drilling fluids pumped into the wellbore, vary the composition of the drilling fluids pumped into the wellbore, or a combination thereof.

<FIG> illustrates a flowchart of a method <NUM>, according to an embodiment. An illustrative order of the method <NUM> is provided below; however, one or more portions of the method <NUM> may be performed in a different order, performed simultaneously, repeated, or omitted.

The method <NUM> may include receiving a first well log that includes a first signal, and a second well log that includes a second signal, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include identifying in the first signal a first change point that demarcates a first signal region and a second signal region, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include determining that the first signal region of the first signal is inconsistent in comparison to the second signal region, as at <NUM> (e.g., <FIG>, <NUM>).

Determining that the first signal region of the first signal is inconsistent may include determining that a mean of the first signal region is less than a mean of the second signal region minus a product, as at <NUM>.

Determining that the first signal region of the first signal is inconsistent may include determining that a mean of the first signal region is greater than a mean of the second signal region plus a product, as at <NUM>.

Determining that the first signal region is inconsistent may include determining an upper bound and a lower bound, and determining that a mean of the first signal region is not between the upper and lower bounds, as at <NUM>.

Determining that the first signal region is inconsistent may include determining an empirical standard deviation of the second signal region, as at <NUM>.

The method <NUM> may also include producing a derivative signal by calculating a derivative of at least a portion of the first signal, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include removing the first signal region from the signal prior to producing the derivative signal, as at <NUM>.

The method <NUM> may also include identifying in the derivative signal a second change point that demarcates a third signal region and a fourth signal region, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include removing the first signal region from the signal prior to determining the second change point, as at <NUM>.

The method <NUM> may also include determining that the third signal region of the derivative signal has a value that is substantially zero, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include producing a modified first well log, as at <NUM> (e.g., <FIG>, <NUM>, <NUM>).

The method <NUM> may also include identifying in a second portion of the signal a third change point that demarcates a fifth signal region and a sixth signal region, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include determining that the sixth signal region of the signal is inconsistent in comparison to the fifth signal region, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include adjusting the modified well log by removing the sixth signal region from the signal, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include identifying in a second portion of the derivative signal a fourth change point that demarcates a seventh signal region and an eighth signal region, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include determining that the eighth signal region of the derivative signal has a value that is substantially zero, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include adjusting the modified well log by removing the eighth signal region from the signal, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include selecting a fifth change point in the modified first well log and a sixth change point in the second well log, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include positioning a first window within the modified first well log based at least in part on the fifth change point, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include positioning a second window at a first location within the second well log based at least in part on the sixth change point, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include determining a first similarity value between the first signal in the first window and the second signal in the second window at the first location, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include repositioning the second window at a second location within the second well log based at least in part on the sixth change point, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include determining a second similarity value between the first signal in the first window and the second signal in the second window at the second location, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include selecting the first location or the second location of the second window based at least partially upon the first and second similarity values, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include determining a modified fourth change point based at least partially upon the selected first location or second location of the second window, as at <NUM> (e.g., <FIG>, <NUM>).

The method <NUM> may also include producing a modified second well log based at least partially upon the selected first location or second location of the second window, as at <NUM> (e.g., <FIG>, <NUM>).

Producing the modified second well log may include determining a difference between the depth represented by the first change point and a depth represented by the modified second change point, and applying an outlier detection algorithm to remove the difference, as at <NUM>.

One or more portions of the method(s) <NUM>, <NUM>, <NUM>, <NUM> disclosed herein may be performed by a computing system, in order to improve the functioning of the computing system (e.g., for seismic processing purposes). In one embodiment, the computing system may include a processor and a memory system including a non-transitory computer-readable medium storing instructions that, when executed by the processor, cause the computing system to perform operations. The operations may include receiving a first well log having a first signal, and a second well log having a second signal. The operations may also include identifying in the first signal a first change point that demarcates a first signal region and a second signal region. The operations may also include determining that the first signal region of the first signal is inconsistent in comparison to the second signal region. The operations may also include producing a derivative signal by calculating a derivative of at least a portion of the first signal. The operations may also include identifying in the derivative signal a second change point that demarcates a third signal region and a fourth signal region. The operations may also include determining that the third signal region of the derivative signal has a value that is substantially zero. The operations may also include producing a modified first well log by removing the first signal region from the first signal in response to determining that the first signal region of the signal is inconsistent in comparison to the second signal region, and by removing the third signal region from the first signal in response to determining that the third signal region of the derivative signal has the value that is substantially zero. The operations may also include selecting a third change point in the modified first well log and a fourth change point in the second well log. The operations may also include positioning a first window within the modified first well log based at least in part on the third change point. The operations may also include positioning a second window at a first location within the second well log based at least in part on the fourth change point. The operations may also include determining a first similarity value between the first signal in the first window and the second signal in the second window at the first location. The operations may also include repositioning the second window at a second location within the second well log based at least in part on the fourth change point. The operations may also include determining a second similarity value between the first signal in the first window and the second signal in the second window at the second location. The operations may also include selecting the first location or the second location of the second window based at least partially upon the first and second similarity values. The operations may also include producing a modified second well log based at least partially upon the selected first location or second location of the second window.

Embodiments of the present disclosure may also provide another computing system. The computing system may include a processor and a memory system including a non-transitory computer-readable medium storing instructions that, when executed by the processor, cause the computing system to perform operations. The operations may include receiving a well log having a signal. The operations may also include identifying in the signal a first change point that demarcates a first signal region and a second signal region. The operations may also include determining that the first signal region is inconsistent in comparison to the second signal region. The operations may also include producing a modified well log by removing the first signal region from the signal in response to determining that the first signal region is inconsistent in comparison to the second signal region.

Embodiments of the present disclosure may also provide another computing system. The computing system may include a processor and a memory system including a non-transitory computer-readable medium storing instructions that, when executed by the processor, cause the computing system to perform operations. The operations may include receiving a first well log and a second well log. The first well log includes a first signal, and the second well log includes a second signal. The operations may also include selecting a second change point in the second well log. The second change point represents a depth in the second well log. The second change point is selected based on a proximity to a depth represented by a first change point in the first well log. The operations may also include positioning a first window in the first well log based at least in part on the first change point. The operations may also include positioning a second window at a first location in the second well log based at least in part on the second change point. The operations may also include determining a first similarity value between the first signal in the first window and the second signal in the second window at the first location. The operations may also include repositioning the second window at a second location in the second well log based at least in part on the second change point. The operations may also include determining a second similarity value between the first signal in the first window and the second signal in the second window at the second location. The operations may also include selecting the first location or the second location of the second window based at least partially upon the first and second similarity values. The operations may also include determining a modified second change point based at least partially upon the selected first location or second location of the second window. The operations may also include producing a modified second well log based at least partially upon the modified second change point.

In some embodiments, any of the methods <NUM>, <NUM>, <NUM>, <NUM> of the present disclosure may be executed by a computing system. <FIG> illustrates an example of such a computing system <NUM>, in accordance with some embodiments. The computing system <NUM> may include a computer or computer system 1401A, which may be an individual computer system 1401A or an arrangement of distributed computer systems. The computer system 1401A includes one or more analysis module(s) <NUM> configured to perform various tasks according to some embodiments, such as one or more methods disclosed herein. To perform these various tasks, the analysis module <NUM> executes independently, or in coordination with, one or more processors <NUM>, which is (or are) connected to one or more storage media <NUM>. The processor(s) <NUM> is (or are) also connected to a network interface <NUM> to allow the computer system 1401A to communicate over a data network <NUM> with one or more additional computer systems and/or computing systems, such as 1401B, 1401C, and/or 1401D (note that computer systems 1401B, 1401C and/or 1401D may or may not share the same architecture as computer system 1401A, and may be located in different physical locations, e.g., computer systems 1401A and 1401B may be located in a processing facility, while in communication with one or more computer systems such as 1401C and/or 1401D that are located in one or more data centers, and/or located in varying countries on different continents).

The storage media <NUM> can be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of <FIG> storage media <NUM> is depicted as within computer system 1401A, in some embodiments, storage media <NUM> may be distributed within and/or across multiple internal and/or external enclosures of computing system 1401A and/or additional computing systems. Storage media <NUM> may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories, magnetic disks such as fixed, floppy and removable disks, other magnetic media including tape, optical media such as compact disks (CDs) or digital video disks (DVDs), BLURAY® disks, or other types of optical storage, or other types of storage devices. Note that the instructions discussed above can be provided on one computer-readable or machine-readable storage medium, or alternatively, can be provided on multiple computer-readable or machine-readable storage media distributed in a large system having possibly plural nodes. Such computer-readable or machine-readable storage medium or media is (are) considered to be part of an article (or article of manufacture). The storage medium or media can be located either in the machine running the machine-readable instructions, or located at a remote site from which machine-readable instructions can be downloaded over a network for execution.

In some embodiments, computing system <NUM> contains one or more well log module(s) <NUM> that may perform at least a portion of one or more of the method(s) <NUM>, <NUM>, <NUM> described above. It should be appreciated that computing system <NUM> is only one example of a computing system, and that computing system <NUM> may have more or fewer components than shown, may combine additional components not depicted in the example embodiment of <FIG>, and/or computing system <NUM> may have a different configuration or arrangement of the components depicted in <FIG>. The various components shown in <FIG> may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application specific integrated circuits.

Geologic interpretations, models and/or other interpretation aids may be refined in an iterative fashion; this concept is applicable to embodiments of the present methods discussed herein. This can include use of feedback loops executed on an algorithmic basis, such as at a computing device (e.g., computing system <NUM>, <FIG>), and/or through manual control by a user who may make determinations regarding whether a given step, action, template, model, or set of curves has become sufficiently accurate for the evaluation of the subterranean three-dimensional geologic formation under consideration.

Claim 1:
A computer-implemented method, comprising:
receiving (<NUM>) a measured well log (600A) comprising a signal (610A);
identifying (<NUM>) in the signal (610A) a first change point (640A) that demarcates a first signal region (620A) and a second signal region (630A);
determining (<NUM>) that the first signal region 620A is inconsistent in comparison to the second signal region (630A);
producing (<NUM>) a modified well log (800A) by removing the first signal region (620A) from the signal (610A) in response to determining that the first signal region (620A) is inconsistent in comparison to the second signal region (630A);
producing (<NUM>) a derivative signal (610C) by calculating a derivative of at least a portion of the signal (610A);
identifying (<NUM>) in the derivative signal (610C) a second change point (640C) that demarcates a third signal region (620C) and a fourth signal region (630C);
determining (<NUM>) that the third signal region (620C) of the derivative signal (610C) has a value of substantially zero; and
adjusting (<NUM>) the modified well log (800B) by removing the third signal region (620C) from the signal (610A) in response to determining that the third signal region (620C) of the derivative signal (610C) has a value that is substantially zero;
wherein the first change point (640A) is identified in a predetermined portion (602A) of the signal (610A) using a change point detection algorithm,
wherein the second change point (640C) is identified in a predetermined portion (602C) of the derivative signal (610C) using the change point detection algorithm,
wherein the predetermined portion (602A) of the signal (610A) at least partially overlaps with the predetermined portion (602C) of the derivative signal (610C), and
wherein the change point detection algorithm is selected from the group consisting of a binary segmentation algorithm, a segment neighborhood algorithm, and a pruned exact linear time (PELT) algorithm.