Time-Lapse Monitoring of Well Casings

The present technology pertains to determining metal loss of one or more well casings.

A well system comprises a well-drilling system to form the well and a well-pumping system to retrieve materials from the well. A well-drilling system is a setup of equipment and machinery designed to extract natural resources, such as water, oil, or gas, from the ground. The system typically includes a drilling rig, which is used to bore a hole into the earth's crust, a casing, which can be a steel pipe that lines the well and cementation between casing and the wall of well which prevents the walls from collapsing. The drilling process begins with the placement of a drill bit at the end of a drill string. The drill bit is then rotated, using a motor or a manual mechanism, to create a hole in the ground. As the hole is drilled, the drill string is gradually lengthened by adding more sections of pipe and cementation outside the pipe. The process continues until the desired depth is reached.

Once the drilling is complete, a casing is installed into the well to protect it from collapse and prevent contamination of the extracted resources. The casing is typically cemented into place to seal off any potential pathways for groundwater to enter the well. Once the well is prepared, a well-pumping system is installed to extract the resources from the well.

Certain aspects of this disclosure are provided below. Some of these aspects may be applied independently and some of them may be applied in combination as would be apparent to those of skill in the art. In the following description, for the purposes of explanation, specific details are set forth in order to provide a thorough understanding of aspects of the application. However, it will be apparent that various aspects may be practiced without these specific details. The figures and descriptions are not intended to be restrictive.

The ensuing description provides example aspects only and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the example aspects will provide those skilled in the art with an enabling description for implementing an example aspect. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the application as set forth in the appended claims.

The terms “exemplary” and/or “example” are used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” and/or “example” is not necessarily to be construed as preferred or advantageous over other aspects. Likewise, the term “aspects of the disclosure” does not require that all aspects of the disclosure include the discussed feature, advantage or mode of operation.

The present disclosure includes a method, system, and apparatus for estimating metal loss of a casing wall. The present disclosure includes acquiring at least two electromagnetic measurement data sets that are taken at two or more different times. In at least one example, the present disclosure includes aligning one or more depths across the at least two electromagnetic measurement data sets; computing a thickness of a plurality of downhole pipes, which at least partially overlap, based upon an applied inversion algorithm to each of the at least two electromagnetic measurement data sets. The present disclosure can also include determining a location of one or more metal loss locations based upon a change in thickness for a given one of the plurality of downhole pipes. Additionally, the present disclosure can include estimating one or more parameters of metal loss based upon the applied inversion algorithm.

Additional details and aspects of the present disclosure are described in more detail below with respect to the figures.

is a diagram of an example wireline environment having tubulars in accordance with various aspects of the disclosure. In some aspects, an example systemis depicted for conducting downhole measurements after at least a portion of a wellbore has been drilled and the drill string removed from the well. A downhole tool is shown having a tool bodyto perform logging, measurements, and/or other operations. For example, a wireline conveyancemay be implemented.

The tool bodymay be lowered into the wellboreby wireline conveyance. The wireline conveyancemay be anchored in the drill rigor by a portable device such as a truck. The wireline conveyancemay include one or more wires, slicklines, cables, and/or the like, as well as tubular conveyances such as coiled tubing, joint tubing, or other tubulars.

The wireline conveyanceprovides power and support for the tool, as well as enabling communication between processing systemson the surface. In some examples, the wireline conveyancemay include electrical and/or fiber optic cabling for performing any communications. The wireline conveyanceis sufficiently strong and flexible to tether the tool bodythrough the wellbore, while also permitting communication through the wireline conveyanceto one or more of the processing systems, which may include local and/or remote processors. Additionally, the processing systemscan be coupled to a first communication systemthat can communicate via wireless and/or satellite connections. Additionally, a local communication devicecan be included. The local communication devicecan communicate with other devices near the site. In some cases, power may be supplied via the wireline conveyanceto meet the power requirements of the tool. For slickline or coiled tubing configurations, power may be supplied downhole with a battery or via a downhole generator.

As illustrated, the tool can be located within a casingthat can be coupled to the formation by cementthat is located within an annulus formed between the casingand the formation.

is a close up view of a toolwithin one or more casingsof a well bore. As illustrated the casingscan include a first casing, a second casing, a third casing, and a fourth casing. While the illustrated example includes four casings, the present disclosure is operable from two to dozens of casings. As illustrated, in a portion of the well bore the casingsoverlap such that a given depth two or more casingscan be positioned within the well bore. In at least one example, the casingscan be a plurality of downhole pipes. The plurality of downhole pipes includes a nested casing arrangement in which multiple pipes of the plurality of downhole pipes are arranged in a well bore. In the illustrated example of, the casingshave been truncated for illustration purposes and can extend much longer relative distances.

The toolcan include a transmitter, a first receiver, a second receiver, a third receiver, a fourth receiver, a fifth receiver, and sixth receiver. The toolcan be implemented for electromagnetic (EM) techniques. One example of an EM technique is eddy current effect. The toolcan be used to characterize the casingaround the well bore. Another technique is to use frequency domain eddy current techniques. In this arrangement the transmitteris provided a continuous sinusoidal signal, producing primary field that illuminate the casings. The primary fields produce eddy currents in the casings. The eddy currents produce secondary fields that can be sensed along with the primary field by the receiver. Each of the receivercan be placed a predetermined distance away from the transmitter. As illustrated, the first receiveris closer to the transmitterthan the remainder of the receivers. The second receivercan be placed next. The third receivercan be further away from the transmitterthan the first receiverand the second receiver. The fourth receivercan be located still further away from the transmitteras compared to the third receiver. The fifth receivercan be next followed by the sixth receiver, which can be located the furthest from the transmitter. While six receiversare illustrated, the present technology can be implemented with two to twelve receivers.

In one example, the transmittercan have a core with a relative permeability of 75. In at least one example, the transmittercan have a core with a relative permeability ranging from about 30 to about 300. The receiverscan be implemented without a core. The measurements can be performed at frequencies ranging from 0.1 Hz to 1000 Hz.

illustrates an example methodin accordance with various aspects of the disclosure. The example methodillustrated is an automated alignment of time lapsed measurement. As illustrated in, a window-based alignment technique is presented to align at least two electromagnetic measurement data sets that are taken at two or more different times. The electromagnetic measurement data set can be taken with the toolas described herein or other tool that allows for electromagnetic measurement data. In at least one example, the toolcan be excited with continuous-wave signal. In at least one example, the continuous-wave signal can be a frequency-domain excitation. In at least one or more other examples, the toolcan be excited with a pulsed signal. In at least one example, the pulsed signal can be time-domain excitation. The methodcan begin, at block, by dividing time lapsed electromagnetic measurements using overlapping windows. The overlapping windows can include a plurality of windows that overlap in a time based and/or depth based orientation.

The methodcan continue by finding window pairs with a maximum correlation at block. The window pairs with maximum correlation can be selected from the plurality of windows such that the portion that overlaps and has a maximum correlation can be used.

The methodcan also include identifying a depth shift on every window center at block. The depth shift is the shift between the two window pairs with maximum correlation. Once the depth shift is determined it is applied across the other windows at a center of the windows between the at least two electromagnetic measurement data sets.

The methodcan also include selecting high quality shift points at block. This is the selection of the shift points for the at least two electromagnetic measurement data sets based on the quality of data around the desired shift points.

The methodcan interpolate and extrapolate shift values for the remaining depth points at block. The methodcan use those remaining depth points to apply a depth correlation to the misaligned at least two electromagnetic measurement data sets to arrive at a depth correlated set of at least two electromagnetic measurement data sets at block.

illustrates an example methodin accordance with various aspects of the disclosure. The methodas illustrated is an edge-based alignment technique. The methodcan include identifying significant features in time lapsed electromagnetic measurement data sets at block. The features that can be identified include one or more changes in the number of casings, a metal loss portion of a casing, and/or other changes in the casing. Metal loss as used herein can refer to corrosion and other types of metal loss such as impact events, flaking, oxidation, degradation, erosion, and the like.

The methodcan compute a depth shift in each feature pairs at block. The methodcan produce a table of all possible shifts that can produce the given feature shifts across the at least two electromagnetic measurement data sets.

The methodcan identify the set of shifts to maximize the correlations across all possible shifts that are tried at block. The number of all possible shifts can be across every single possible shift or the number of shifts that are computed can be based upon particular identified features and the resultant of shifts regarding those particular features.

The methodcan interpolate and extrapolate the remaining depth shifts at the remaining depth points in at least two electromagnetic measurement data sets until all of the remaining depth shifts are computed at block.

The methodcan apply a depth correlation to misaligned at least two electromagnetic measurement data sets to obtain an aligned at least two electromagnetic measurement data sets at block.

illustrates an example methodin accordance with various aspects of the disclosure. The method includes obtaining an electromagnetic measurement data setand a time lapsed electromagnetic measurement data set. While only a single time lapsed electromagnetic measurement data setis shown, a plurality of time lapsed electromagnetic measurement data setscan be obtained. Therefore, the methodoperates with at least two electromagnetic measurement data sets. The time lapsed electromagnetic measurement data set can be obtained at a time that is later than the electromagnetic measurement data set. The at least two electromagnetic measurement data sets can be obtained using a tool such as the one described herein or with another tool that operates using electromagnetic measurements.

The methodcan include applying an unbounded inversion algorithmto the at least two electromagnetic measurement data sets after an automated alignment algorithmhas been performed for the time lapsed electromagnetic measurement data set. The automated alignment algorithmcan be one or more of the alignment algorithms described herein above.

The methodcan generate a thickness estimation. The thickness estimation can be compared with the upper bounded inversionto arrive at a metal loss estimation. Implementation can further be described in relation tobelow.

In order to illustrate examples of the data sets and alignment thereof,are presented herein.illustrates a graph of a plot of data in accordance with various aspects of the disclosure. As illustrated,includes a plot between a first electromagnetic measurement data set taken in 2019 compared to a second electromagnetic measurement data set taken in 2021. The measurements are recorded at a depth in unites of milli-Ohms (mΩ). As can be seen there are some changes in the electromagnetic measurement set that appear to be shifted compared to each other. The present disclosure applies the shift to align the two electromagnetic measurement data sets to be as shown in.

illustrates a graph of a plot of data in accordance with various aspects of the disclosure featuring more complex features as compared to. As illustrated,includes a plot between a first electromagnetic measurement data set taken in 2019 compared to a second electromagnetic measurement data set taken in 2021. The present disclosure applies the shift to align the two electromagnetic measurement data sets to be as shown in. As noted, the differences between the at least two electromagnetic measurement data sets inare impossible to align for a human. Rather the algorithms that are implemented allow for the alignment automatically.

illustrates a graph of a plot of data in accordance with various aspects of the disclosure to plot a pseudo thickness or a thickness. Again the plot is of data from at least two electromagnetic measurement data sets with one taken in 2019 and the other in 2021. The present disclosure is used to create an alignment of the thickness to arrive at the plot of. As illustrated in, there is an upper bounded constraint that is calculated as well. The upper bounded constraint on the pipe thickness coincides with the oldest thickness measurement because the pipe does not gain metal, but only loses metal overtime. While described in terms of thickness herein, the thickness refers to a continuous thickness rather than a portion of the pipe that has been subjected to metal loss including corrosion and other features described herein that can result in an outside diameter measurement that is larger than a previous measurement.

illustrates a graph of a plot of data in accordance with various aspects of the disclosure to plot a pseudo thickness or a thickness. Again the plot is of data from at least two electromagnetic measurement data sets with one taken in 2019 and the other in 2021. The present disclosure is used to create an alignment of the thickness to arrive at the plot of. As illustrated in, there is an upper bounded constraint that is calculated as well.

is a diagram illustrating a methodof estimating metal loss of a casing wall in a well bore. At block, the methodacquires at least two electromagnetic measurement data sets that are taken at two or more different times. In at least one example, the two or more different times can span at least a month. Furthermore, the two or more different times can span at least a year. The at least two electromagnetic measurement data sets includes one or more of the following data sets: an electromagnetic induction measurement data set acquired in a time domain or a frequency domain, and/or a magnetic flux leakage measurement data set.

At block, the methodaligns one or more depths across the at least two electromagnetic measurement data sets. Aligning one or more depths across the at least two electromagnetic measurement data sets includes aligning a plurality of features across the at least two electromagnetic data sets. The depth aligning includes performing a comparison of the at least two electromagnetic measurement data sets using a machine learning model to estimate a shift between the at least two electromagnetic measurement data sets. The depth aligning includes one or more of the following: a window-based correlation, an edge-based matching, and/or a dynamic time warping. Additionally, the aligning can include analyzing the at least two electromagnetic measurement data sets for patterns and aligning a positioning of one or more distinct points of the pattern within the at least two electromagnetic measurement data sets.

At block, the methodcomputes a thickness of a plurality of downhole pipes, which at least partially overlap, based upon an applied inversion algorithm to each of the at least two electromagnetic measurement data sets. The plurality of downhole pipes includes a nested casing arrangement in which multiple pipes of the plurality of downhole pipes are arranged in a well bore. The applied inversion algorithm can be a model-based inversion algorithm. The applied inversion algorithm can implement one or more different examples of a inversion cost function. An example of the cost function can be as presented below:

Different quantities in the cost function are defined as follows:

Solving the inverse problem involves finding the model parameters that minimize the cost function in Eq. (1). This is accomplished using an iterative, non-linear numerical optimization algorithm. Before proceeding with the numerical optimization, other non-model parameters in the cost function need to be determined. These are referred to as “hyperparameters” as they need to be determined once for a given pipe zone, then used to define the cost function that will be used to invert for pointwise model parameters within that zone. Table 1 lists the hyperparameters and the algorithms used to determine each.

The corresponding workflow to determine the hyperparameters can be described in terms of a method by taking measurements and generating a final inversion result. The method can include a Mu/Sigma Estimation (MSEA). The method can also include a multi-zone correction (MZCA). The method can also include a calibration (CA). Furthermore, the method can include a channel quality assessment (CQAA). Additionally, the method can include an initial guess estimation (IGEA). The method can also include a regularization parameter estimation (RPEA). The method can also include an inversion (IA). The method can also include post-processing, which can in turn generate the final inversion result. In at least one implementation of the method the order of the steps can be described in the order presented herein. In other examples, the order of the method can vary. In at least one example, the method can include additional steps and/or omit one or more steps. The pipe material properties are estimated at the very beginning through the algorithm MSEA. The calibration constants Ware calculated through the algorithms MZCA and CA. The weight matrices W, Ware determined using the algorithm CQAA. The initial guess thickness is calculated through IGEA where only metal loss is allowed. The regularization parameters Ware automatically determined using the algorithm RPEA. All these hyperparameters are then passed into the cost function for inversion. Finally, the inverted results are post-processed to remove artifacts. The details of algorithms for calculating the hyperparameters are described in the following section.

The model-based inversion algorithm calculates one or more estimated pipe attributes including but not limited to material property, thickness, and the like. The computing the thickness of the plurality of downhole pipes further includes a machine learning model. In at least one example, the model-based inversion can be replaced by a machine learning-based model to computer pipe thickness.

At block, the methoddetermines a location of one or more metal loss locations based upon a change in thickness for a given one of the plurality of downhole pipes.

At block, the methodestimates one or more parameters of metal loss based upon the applied inversion algorithm.

Additionally, the method can include generating a pseudo-thickness of each pipe of the multiple pipes using at least one algorithm. The method can also include determining a change in pseudo-thickness of one or more of the multiple pipes. The location of the one or more metal loss locations is compared with the change in pseudo-thickness of the one or more of the multiple pipes.

The method can also include setting an upper bound of the thickness of the plurality of downhole pipes based one the calculated thickness from one or more former electromagnetic measurement data sets.

is a diagram illustrating an example of a system for implementing certain aspects of the present technology in accordance with some aspects of the disclosure. In particular,illustrates an example of computing system, which may be for example any computing device making up an internal computing system, a remote computing system, a sensor, or any component thereof in which the components of the system are in communication with each other using connection. Connectionmay be a physical connection using a bus, or a direct connection into processor, such as in a chipset architecture. Connectionmay also be a virtual connection, networked connection, or logical connection.

In some aspects, computing systemis a distributed system in which the functions described in this disclosure may be distributed within a datacenter, multiple data centers, a peer network, etc. In some aspects, one or more of the described system components represents many such components each performing some or all of the function for which the component is described. In some aspects, the components may be physical or virtual devices.

Example computing systemincludes at least one processing unit (CPU or processor)and connectionthat couples various system components including system memory, such as ROMand RAMto processor. Computing systemmay include a cacheof high-speed memory connected directly with, in close proximity to, or integrated as part of processor.

Processormay include any general purpose processor and a hardware service or software service, such as services,, andstored in storage device, configured to control processoras well as a special-purpose processor where software instructions are incorporated into the actual processor design. Processormay essentially be a completely self-contained computing system, containing multiple cores or processors, a bus, memory controller, cache, etc. A multi-core processor may be symmetric or asymmetric.

To enable user interaction, computing systemincludes an input device, which may represent any number of input mechanisms, such as a microphone for speech, a touch-sensitive screen for gesture or graphical input, keyboard, mouse, motion input, speech, etc. Computing systemmay also include output device, which may be one or more of a number of output mechanisms. In some instances, multimodal systems may enable a user to provide multiple types of input/output to communicate with computing system. Computing systemmay include communications interface, which may generally govern and manage the user input and system output. The communication interface may perform or facilitate receipt and/or transmission wired or wireless communications using wired and/or wireless transceivers, including those making use of an audio jack/plug, a microphone jack/plug, a universal serial bus (USB) port/plug, an Apple® Lightning® port/plug, an Ethernet port/plug, a fiber optic port/plug, a proprietary wired port/plug, a Bluetooth® wireless signal transfer, a BLE wireless signal transfer, an IBEACON® wireless signal transfer, an RFID wireless signal transfer, near-field communications (NFC) wireless signal transfer, dedicated short range communication (DSRC) wireless signal transfer, 802.11 WiFi wireless signal transfer, WLAN signal transfer, Visible Light Communication (VLC), Worldwide Interoperability for Microwave Access (WiMAX), IR communication wireless signal transfer, Public Switched Telephone Network (PSTN) signal transfer, Integrated Services Digital Network (ISDN) signal transfer, 3G/4G/5G/LTE cellular data network wireless signal transfer, ad-hoc network signal transfer, lamb wave signal transfer, microwave signal transfer, infrared signal transfer, visible light signal transfer, ultraviolet light signal transfer, wireless signal transfer along the electromagnetic spectrum, or some combination thereof. The communications interfacemay also include one or more Global Navigation Satellite System (GNSS) receivers or transceivers that are used to determine a location of the computing systembased on receipt of one or more signals from one or more satellites associated with one or more GNSS systems. GNSS systems include, but are not limited to, the US-based GPS, the Russia-based Global Navigation Satellite System (GLONASS), the China-based BeiDou Navigation Satellite System (BDS), and the Europe-based Galileo GNSS. There is no restriction on operating on any particular hardware arrangement, and therefore the basic features here may easily be substituted for improved hardware or firmware arrangements as they are developed.