WO2021087509A1

WO2021087509A1 - Automated kick and loss detection

Info

Publication number: WO2021087509A1
Application number: PCT/US2020/070700
Authority: WO
Inventors: Aurore Lafond
Original assignee: Schlumberger Technology Corporation; Schlumberger Canada Limited; Services Petroliers Schlumberger; Geoquest Systems B.V.
Priority date: 2019-10-31
Filing date: 2020-10-27
Publication date: 2021-05-06
Also published as: EP4051865A4; CN114846220A; EP4051865A1; US20220397008A1

Abstract

A method for monitoring and controlling a mud flow system in a drilling rig includes measuring an active mud volume in an active mud pit and an inactive mud volume in an inactive mud pit, modeling a modeled active mud volume in the active mud pit, determining a mud volume balance by calculating a difference between the measurement of the active mud volume and the modeled active mud volume, detecting a transfer of mud from the inactive mud pit to the active mud pit based on a combination of a change in the measurement of the inactive mud volume in the inactive mud pit and a change in the mud volume balance, and detecting downhole gains and losses automatically based on the mud volume balance.

Description

AUTOMATED KICK AND LOSS DETECTION

Cross-Reference to Related Applications

[0001] This application claims priority to U.S. Provisional Patent Application having Serial No. 62/929064, which was filed on October 31, 2019 and is incorporated herein by reference in its entirety.

Background

[0002] Downhole fluid gain and loss detection provides data related to the safety and integrity of drilling activities. One way such detection is accomplished is by monitoring flow and using flow models to deduce the downhole gain and loss status. However, such monitoring and modeling can be expensive to implement, as it may rely on measurements that are not readily available. Other ways to monitor fluid gain and loss rely on pit-volume measurements (i.e., mud volume/level in an active mud pit) or flow paddle measurements. While pit-volume methods are generally easier to deploy, they may provide less efficient and less reliable kick detection capabilities. In particular, there may be a relatively long delay between a downhole mud gain/loss event and a responsive change in pit mud level. Such delays occur in part because surface equipment acts as a buffer between the pit and the well, slowing pulses in mud flow that eventually change the pit mud level. [0003] Furthermore, pit-volume monitoring may be relatively inflexible. For example, a pump stop may be fingerprinted and used as a baseline reference to infer whether subsequently observed active pit mud volume variations are normal. If the flow conditions in subsequent time periods differ from those present in the comparison sample, no reliable conclusion on the gain and loss status can be drawn from mud volume variations. Further, this technique relies on the periods of interest actually reflecting normal operation; if a period of abnormal operation is considered as the baseline or normal operation, then subsequent abnormalities may be missed or normal activity may be incorrectly labeled as abnormal.

[0004] Additionally, pit-volume monitoring techniques may interpret normal surface events such as transfers between pits as a downhole gain or loss, resulting in a false determination of a downhole event (e.g., a false kick alarm). To account for such surface events, current practice calls for operators on the rig site to record real-time comments on mud logging reports when they become aware, e.g., of a transfer, after discussion with the mud engineers. Thus, upon confirming that a transfer to the active system occurred, the operator can deactivate the gain alarm. However, this practice relies on human users to make observations and manually enter error-free information into a log in a timely manner. Moreover, the reaction of the operator may take time, as the operators may be responsible for multiple other tasks concurrently, leading to delays and thus potentially long false kick alarm periods.

Summary

[0005] This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.

[0006] Embodiments of the disclosure provide a method for monitoring and controlling a mud flow system in a drilling rig that includes measuring an active mud volume in an active mud pit and an inactive mud volume in an inactive mud pit, modeling a modeled active mud volume in the active mud pit, determining a mud volume balance by calculating a difference between the measurement of the active mud volume and the modeled active mud volume, detecting a transfer of mud from the inactive mud pit to the active mud pit based on a combination of a change in the measurement of the inactive mud volume in the inactive mud pit and a change in the mud volume balance, and detecting downhole gains and losses automatically based on the mud volume balance. [0007] Embodiments of the disclosure also provide a computing system including one or more processors and a memory system including one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations. The operations include measuring an active mud volume in an active mud pit and an inactive mud volume in an inactive mud pit, modeling a modeled active mud volume in the active mud pit, determining a mud volume balance by calculating a difference between the measurement of the active mud volume and the modeled active mud volume, detecting a transfer of mud from the inactive mud pit to the active mud pit based on a combination of a change in the measurement of the inactive mud volume in the inactive mud pit and a change in the mud volume balance, and detecting downhole gains and losses automatically based on the mud volume balance.

[0008] Embodiments of the disclosure further provide a non-transitory computer-readable medium storing instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations. The operations include measuring an active mud volume in an active mud pit and an inactive mud volume in an inactive mud pit, modeling a modeled active mud volume in the active mud pit, determining a mud volume balance by calculating a difference between the measurement of the active mud volume and the modeled active mud volume, detecting a transfer of mud from the inactive mud pit to the active mud pit based on a combination of a change in the measurement of the inactive mud volume in the inactive mud pit and a change in the mud volume balance, and detecting downhole gains and losses automatically based on the mud volume balance.

Brief Description of the Drawings

[0009] The present disclosure is best understood from the following detailed description when read with the accompanying Figures. It is emphasized that, in accordance with the standard practice in the industry, various features are not drawn to scale. In fact, the dimensions of the various features may be arbitrarily increased or reduced for clarity of discussion.

[0010] Figure 1 illustrates a schematic view of an example of a drilling system, according to an embodiment.

[0011] Figure 2 illustrates a control block diagram for a mud system of the drilling system, according to an embodiment.

[0012] Figure 3 illustrates a conceptual view of the mud system, according to an embodiment. [0013] Figure 4 illustrates a flowchart of a process for modeling mud flow in the mud system, according to an embodiment.

[0014] Figure 5 illustrates plots of flow rate and active volume (based on mud volume in an active pit), according to an embodiment.

[0015] Figure 6 illustrates a conceptual view of an embodiment of the mud system that includes a downlinker.

[0016] Figure 7 illustrates plots of inactive mud volume, flow, active mud volume, and mud volume balance as a function of time, according to an embodiment.

[0017] Figure 8 illustrates a flowchart of a process for detecting and accounting for mud transfers, according to an embodiment.

[0018] Figure 9 illustrates a flowchart of a method for controlling a mud system, according to an embodiment.

[0019] Figure 10 illustrates plots of measured and theoretical (calculated/modeled) active mud volume, and real-time and adjusted mud volume balances, according to an embodiment. [0020] Figure 11 illustrates a schematic view of a computing system, according to an embodiment.

Detailed Description

[0021] Illustrative examples of the subject matter claimed below will now be disclosed. In the interest of clarity, not all features of an actual implementation are described in this specification. It will be appreciated that in the development of any such actual implementation, numerous implementation-specific decisions may be made to achieve the developers’ specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another. Moreover, it will be appreciated that such a development effort, even if complex and time-consuming, would be a routine undertaking for those of ordinary skill in the art having the benefit of this disclosure.

[0022] Further, as used herein, the article “a” is intended to have its ordinary meaning in the patent arts, namely “one or more.” Herein, the term “about” when applied to a value generally means within the tolerance range of the equipment used to produce the value, or in some examples, means plus or minus 10%, or plus or minus 5%, or plus or minus 1%, unless otherwise expressly specified. Further, herein the term “substantially” as used herein means a majority, or almost all, or all, or an amount with a range of about 51% to about 100%, for example. Moreover, examples herein are intended to be illustrative only and are presented for discussion purposes and not by way of limitation. Any use of the term “or” is meant to be non-exclusive, e.g., “A or B” means A, B, or both A and B.

[0023] Figure 1 illustrates a schematic view of an example of a drilling system 100, according to an embodiment. The drilling system 100 may be provided at a wellsite which may be an onshore or offshore wellsite, and the drilling system 100 may include any combination of the various elements described herein.

[0024] The drilling system 100 may form a borehole 11 in a subsurface formation by rotary drilling with a drill string 12 suspended within the borehole 11. The drilling system 100 may include a platform and derrick assembly 10 positioned over the borehole 11. The platform and derrick assembly 10 may include drilling equipment, such as a rotary table 16, a kelly 17, a hook 18, and/or a rotary swivel 19. The drill string 12 may be rotated by the rotary table 16, which engages the kelly 17 at the upper end of the drill string 12. The drill string 12 may be suspended from the hook 18, attached to a traveling block, through the kelly 17 and the rotary swivel 19, which permits rotation of the drill string 12 relative to the hook 18. In another embodiment, a top drive system may be utilized instead of the rotary table 16 and/or the kelly 17 to rotate the drill string 12 from the surface above the borehole 11. The drill string 12 may be assembled from a plurality of segments 125 that may be or include pipe and/or collars.

[0025] The drilling system 100 may also include a BHA 120 connected to a lower end of the drill string 12. The BHA 120 may include a logging-while-drilling (hereinafter “LWD”) tool 130, a measuring-while-drilling (hereinafter “MWD”) tool 140, a motor 150, a drill bit 122, or a combination thereof. The drilling system 100 may further include drilling fluid or “mud” 26 stored in an active pit 27A formed at the wellsite. It will be appreciated that a pit can be a structure that is dug into the ground and, e.g., lined as appropriate to prevent leakage. In other embodiments, a pit can be a separate containment structure, such as a tank or other vessel.

[0026] A pump 29 of the drilling system 100 may deliver the mud 26 from the active pit 27 A to an interior of the drill string 12 extending into the borehole 11 via a port in the rotary swivel 19, which may cause the mud 26 to flow downwardly through the drill string 12 and the BHA 120, as indicated by the arrow 8. The mud 26 may exit via ports in the drill bit 122, and then circulate upwardly through an annulus between an outside of the drill string 12 and a wall of the borehole 11, as indicated by arrows 9. The mud 26 may lubricate the drill bit 122 and/or may carry formation cuttings up to the surface adjacent to the borehole 11. The mud 26 may by returned to the active pit 27A for cleaning and recirculation.

[0027] The drilling system 100 may also include one or more inactive pits 27B. The inactive pits 27B may contain a reserve of the mud 26, which may be supplied (“transferred”) to the active pits 27A periodically, on demand, etc. For example, formation permeability, surface losses, and/or downhole events may slowly reduce the amount of mud 26 in the active pit 27A, and thus mud 26 from the inactive pit 27B may be supplied to the active pit 27A (e.g., via one or more transfer pumps) to resupply the active pit 27A. Further, in some situations, the composition of the mud 26 may be modified by transferring mud 26 from the inactive pit 27B to the active pit 27A.

[0028] The drilling system 100 may include one or more shakers 155. The shakers 155 may receive the mud that has been circulated up from the borehole 11, and may remove large cuttings therefrom. The shakers 155 may also remove a portion of the drilling mud 26 as well, e.g., as a film on the cuttings. From the shakers 155, the mud 26 may return to the active pit 27A, or may be otherwise conditioned and prepared for recirculation through the borehole 11. [0029] In some embodiments, the drilling system 100 may also include a downlinker 160. The downlinker 160 may form a part of a flowpath that bypasses the borehole 11 and the drill string 12, and returns the drilling mud from the pump 29 directly back to the active pit 27A. The downlinker 160 may be employed for bi-directional communications with various aspects of the BHA 120.

[0030] Turning now to the processing methods and control over at least a portion of the drilling system 100, particularly the mud systems thereof, embodiments of the present disclosure may combine two techniques for mud-flow monitoring and control. In particular, embodiments may model the mud flow through the surface equipment and automatically identify and track mud transfers between pits.

[0031] Modeling the surface equipment facilitates making predictions that account for transient mud volumes. Transient mud volumes may be observed when mud flow changes, such as during connections (e.g., because the pumps are stopped and started). The model may employ an on-the- fly recalibration strategy that allows the model to adapt to changing mud properties. This recalibration is controlled to avoid training the model with abnormal conditions data. The process of automatic recalibration works in parallel with the process of using the model to detect mud volume balance anomalies in real-time. This prediction is then compared to the measured volume to determine a mud volume balance, from which mug gains or losses may be determined.

[0032] Automatically detecting mud transfers between pits may proceed by monitoring the inactive mud pits and applying a segmentation algorithm to identify periods of change in the mud levels measured therein. Changes in the trend of mud volume in the inactive pits may be identified and may be correlated to a transfer to or from the active pit, based on the variations of the mud volume balance. The measured active volume may be automatically adjusted in real-time in response to a detected transfer between the inactive and active pits. As the term is used here, “real time” refers to something occurring without a delay that is easily perceived by a human user, with the goal being for “real-time” to be without any appreciable delay.

[0033] Figure 2 illustrates a control block diagram for a mud control system 200, according to an embodiment. The mud control system 200 may be implemented using one or more computing devices of a computing system, which may be local to (e.g., a physical component of) the drilling system 100, or located remotely therefrom and communicative therewith via an internet connection, for example. [0001] As indicated at 202, the mud control system 200 may take, e.g., in real-time, mud measurements in the drilling system 100, particularly in the active and inactive mud pits and the pump, as discussed above with reference to Figure 1. In particular, the volume of mud in the pits may be measured as a function of time. These measurements may be employed to efficiently control the physical mud system (i.e., the mud-handling components of the drilling system 100). For example, the measurements may be provided to a transient flow modeling module 204. The transient flow modeling module 204 may model mud flow (including losses) during a transient stage of flow in the drilling system 100, e.g., when the pump is first turned on or after it is turned off.

[0002] The output of the transient flow modeling module 204 may be provided to a mud volume balance module 206 and employed to calculate a mud volume balance. The mud volume balance may be an output of a model configured to model mud flow in the mud system, and thereby predict the fluid levels in the active pit. In particular, the mud volume balance is the difference between the measured volume of mud in the active pit and the volume of the mud that is predicted by the model to be in the active pit at the same time. The active pit may be a convenient place to project mud volume, because the volume of the mud in the active pit (and in the inactive pits, as will be discussed below) may be readily measured, thereby providing a calibration measurement for a model upon which the mud volume balance module 206 operates. The model may take into consideration the various components of the mud flow system, gains and losses in fluid therefrom, time delays, etc., and project an expected amount of mud in the active mud pits.

[0034] Referring now to Figure 3, there is shown a conceptual view of a mud system 300 of the drilling system 100, according to an embodiment. This view of the mud system 300 will be referred to for a further understanding of the operation of the transient flow modeling module 204 and the mud volume balance module 206, as part of the mud control system 200 of Figure 2.

[0035] When the mud leaves a well 302, it includes drill cuttings suspended therein. The mud flows through a flowline 304 (e.g., a pipe) and arrives at shakers 306. The shakers 306 provide screens that filter the mud, such that cuttings 307 are separated from the mud slurry and the “cleaned” mud is returned to one or more active pits 308. The mud is then pumped out of the active pit 308 and back to the well 302, beginning a new cycle. At the shakers 306, some mud 309 is also removed or “lost” with the cuttings 307, e.g., as a mud film around the cuttings 307. [0036] The mud volume in the active pits 308 may spike (up or down) at pump stop and start, e.g., because of a buffering effect in surface equipment (e.g., at the shakers 306). This behavior can be theoretically reproduced by modeling the shakers 306 as a permeable media.

[0037] During steady-state pump flow, the mud volume in the active pits 308 decreases due to the cuttings and mud losses at the shakers 306. The cuttings loss can be deduced from the cuttings flow, which can be measured at the outlet of the shakers 306. However, the mud loss associated with a given amount of cuttings flow may be variable based on several factors, and thus may be calibrated.

[0038] Thus, to compute a theoretical mud volume in the active pits 308 at a given point in time, losses during transient flow periods and steady-state flow periods may be modeled. To do so, two coefficients may be estimated: a surface loss coefficient b (e.g., from the shaker 306) and a permeability coefficient k (representing the subterranean formation through which the well 304 extends). For example, the permeability coefficient k predominately influences the mud volume in the active pit 308 during transient flow periods, e.g., pump start up and pump stop. On the other hand, the surface loss coefficient b influences the mud volume in the active pit 308 during periods of steady-state flow.

[0039] Accordingly, the calibration strategy may likewise be separated into two phases. Referring now to Figure 4, there is shown a flowchart of a calibration process 400, according to an embodiment. The process 400 may include calculating a permeability coefficient during a transient period of mud flow, as at 402. Specifically, the permeability coefficient k may be calibrated during the transient period. Pump start may be selected to provide the transient period. Although pump stoppage may also provide a transient flow period, and thus some embodiments may use pump stoppage as the transient flow period, there may be a higher risk for abnormal activity (e.g., a kick) during pump stoppage.

[0040] For the second stage of calibration, as at 404, a steady-state flow period may be selected to calibrate the surface loss coefficient b. The steady-state flow period may be experienced after pump start (e.g., after a duration during which mud begins to flow) and before pump stoppage. For purposes of calibration, a first steady-state flow period may be selected, i.e., between the first pump start and the first pump stoppage, because it may carry the lowest risk for abnormal activities that impact mud flow; however, in other embodiments, other periods of steady-state flow may be selected. Accordingly, in at least some situations, the surface loss coefficient b may not be recalibrated during a second steady-state flow period (e.g., after the second pump start and before the second pump stoppage).

[0041] The mud flow in the mud system 300 may then be modeled based at least in part on the calculated surface mud loss coefficient b and the permeability coefficient k, as at 406. For example, to calculate these coefficients and, thus produce an accurate model of mud flow, the modules 204, 206 may begin by considering a mass conservation equation in the shaker 306.

[0042] The volumetric flow rate of cleaned mud flowing out the shakers 306 can be expressed using Darcy’s law. That is, the shakers 306 may be behave analogously to a porous media with a given permeability, area, and thickness. The height of the cleaned mud accumulating over the shaker screens is expressed as Ah.

[0043] As a first approximation, flowline effects may be ignored. For example, the flowline is assumed mainly to create a delay in mud flow due to the wave propagation. Some dampening effects may also occur, but their influence may be included in the porosity modeling of the shaker screens. Dampening and porosity effects can be approximated by a first order system. Thus, the flow rates at the exit of the flowline can be approximated. Another approximation is that the mud density has small variations over each section.

[0044] The mass conservation equation in the active pits may then be determined. The mud at the exit of the well is a two-phase medium, with the cleaned mud and the drilled cuttings, which may permit determination of a density of the mud as a function of time. Further, the cuttings may be considered to have a generally constant density, and thus the remaining unknown is the density of the cleaned mud, which may be related to a difference between the density of the mud and the density of the removed cuttings.

[0045] The mud shaker volume generally is not measured, but its calculation is intermediary data useful for the final computation of the active volume. Although the computed shaker volume may not be compared against actual measurements for validation, some physical conditions can be used to control its computation. For example, its global behavior fits with a first order system.

[0046] The shaker volume in a pump start is easier to solve from a physical point of view, compared to the pump stop. If the time between the previous pump stop and the pump start is large enough, the shaker volume may be considered close to zero at the beginning of the pump start, since the mud above the shaker may have drained through the shaker screens while the pumps were off. Thus, in practice, the initial conditions for the shaker may be known for a pump start, e.g., the shaker volume is at rest. [0047] The computed shaker volume at the end of a pump stop may not reach zero, but trends towards zero. Specifically, the computed shaker volume follows a first order response which asymptotically approaches a steady state value (zero for a pump stop). Thus, at the beginning of the next pump start, the initial computed shaker volume is not zero (but approaches zero), even if the time between the last pump stop and the pump start is long enough (depending on the time constant t).

[0048] Further, this first order model can introduce error accumulation in other times, as well. Accordingly, the process 400 may include determining when to recalibrate either or both coefficients, as at 408. The computation of the active volume is based on an iterative method. Thus, to reduce the error propagation, recalibration or adjustment of the global shaker constant K may be performed during each pump start, and the shaker volume may be reset to zero at the beginning of every pump start if the pump off is long enough. If the permeability coefficient k is calibrated once, the theoretical mud volume in the active pit drifts away from the measured volume because of the first order assumption.

[0049] Figure 5 illustrates plots of active volume (i.e., mud volume in an active pit) and flow rate in a mud system, both as a function of time, according to an embodiment. In this illustration, there are three transient flow calibration periods brought on by pump start up. These sections are labeled as sections 501, 502, 503, and represent transient flow regimes in the mud system. The permeability coefficient k can be calibrated during each section 501-503. By contrast, during normal conditions, the surface loss coefficient b may not change, as it is linked to mud losses in the surface equipment and along with the filtered cuttings, as mentioned above. Over the period of calibration, the permeability coefficient k may be computed to ensure fitting between the measured active volume and the computed volume. Moreover, the calibration of coefficient b may occur after the first calibration of the global shaker constant K.

[0050] Because the surface loss coefficient b is linked to equipment configuration, it may be constant during normal conditions. However, the surface loss coefficient b may change when one or more screens of the shaker 306 are blocked, since this reduces the cuttings filtering and increases the mud buffering above the shakers 306. Further, the surface loss coefficient b may change when the cuttings flow changes because cuttings flow change may induce a modification of the mud coating conditions. The cuttings flow change can be automatically identified by the mud volume balance model, and the mud losses coefficient recalibration automatically triggered without any operator input. The shaker screen blockage may be difficult to predict, however. As such, an operator may still be called upon to take preventive actions to clean the strainer or recalibrate manually surface loss coefficient b.

[0051] Figure 6 illustrates another embodiment of the mud system 300. In this embodiment, in addition to the other components discussed above, the mud system 300 includes a downlinker 600, e.g., as shown in and discussed above with reference to Figure 1. The provision of a downlinker 600 may result in a modified mud volume model. In particular, with inclusion of the downlinker 600, the volume of the active pit(s) may be expressed at least partially as a function of the flowrate diverted by the downlinker 600.

[0052] Returning to Figure 2, the transient flow modeling module 204 is used to calibrate the mud volume balance module 206, as described above. The mud control system 200 may also include a transfer identification module 208 and a transfer compensation module 210, as shown. The measurements taken at 202 may be provided to the transfer compensation module 210 and the transfer identification module 208, which may modify the mud volume balance calculated in the module 206.

[0053] The transfer identification module 208 may proceed by monitoring the mud volumes in both the inactive pits and the active pits for changes, e.g., using a change-point or any suitable segmentation algorithm. The change-point algorithm can be set with an appropriate threshold, e.g., 1 cubic meter, to eliminate false positives caused by noise. Further, “segments”, e.g., changes in volume, can be considered “significant” if the segment length is greater than twice the pit volume noise.

[0054] Accordingly, the transfer identification module 208 may be generally passive, monitoring the levels of the mud in the pits until a decrease or increase or both are detected, e.g., by reference to the mud volume balance from module 206. At this point, a determination is made as to whether the decrease or increase is impacting the fluid level in another pit, e.g., by checking the mud volumes in the various pits for a corresponding change in fluid level. For example, if a level of mud in one inactive pit decreases, a transfer to another inactive pit may be expected to result in a corresponding increase in the level of fluid in another inactive pit, and such transfer may not impact the active system. By contrast, a transfer of mud from an inactive pit to an active pit may be marked by a reduction in the mud volume in at least one of the inactive pits, an increase in the volume in the active pit, and may impact the mud volume in the mud flow system. [0055] The mud volume balance may be used to cross-check the transfer. The mud volume balance is computed as the difference between the measured active volume and the theoretical active volume. The mud volume balance is compensated for transient effects, as discussed above, and has a more stable behavior than the raw measured active volume, e.g., in the active pit. Thus, when a transfer to the active pit occurs during a pump flow change, it may be difficult to identify solely based on observation of the mud volume in the active pit. However, the transfer is much easier to observe on the mud volume balance. As such, the mud balance is used as a reference for the transfer cross-check.

[0056] Figure 7 illustrates graphs of mud volume in an inactive pit 701, mud flow rate 702 (e.g., by the pump), mud volume in the active pit 703, and the mud balance 704 (difference between actual and theoretical mud volume in the active pit) during a common period of time. As can be seen, the mud volume in the inactive pit 701 may be relatively stable until a transfer event indicated at 705. The transfer event 705 is represented by a measured decrease in the volume of the fluid in the inactive pit; however, it may not represent an increase in the mud volume in the mud system, unless there is a corresponding and delayed increase in fluid volume in the active pit.

[0057] Moreover, as shown in graph of mud flow rate 702, the mud flow rate 702 may not be stable at the time of the transfer event 705. In 702, the pump has been shut down and turned on, shut down again, and is in a transient stage at the time the transfer event 705 begins. Thus, as can be seen in graph 703, a change in fluid level has occurred, but it is unclear whether that was caused by the transient flow in the pump or a transfer of fluid from the inactive pit, and as can be seen earlier in time, the transient flow has caused increases in the fluid level in the active pit. However, the mud volume balance removes at least some of the effects of transient flow from the active pit volume. If the mud volume balance is off by more than a threshold, as indicated by the relatively sharp rise during the transfer event 705, it represents a mud gain event for the active pit. Coupled with the decrease in mud volume in the inactive pit, it may be inferred that a transfer, rather than a downhole mud gain event (kick) has occurred. As such, there is a two-factor test to establish the existence of a transfer and distinguish a transfer from a downhole gain/loss event: a change in mud volume in the inactive pit, and an increase in the mud volume balance in the active pit.

[0058] The volume of mud in the active pit may then be adjusted to compensate for the transfer. This is illustrated by the summation in Figure 2, between the transfer compensation module 210 and the mud volume balance module 206. The compensation uses the mud volume balance variation. Indeed, the mud volume balance is free of transient effects, e.g., from the pump flow changes, from the cuttings withdrawal impact at the shaker, from the surface losses. Thus, variations in the mud balance during a transfer may represent the amount of mud transferred from or to another pit.

[0059] Figure 8 illustrates a flowchart of a process 800 for detecting a transfer in a mud system, such as the mud system 300, as part of the operation of a mud control system, such as the mud control system 200, according to an embodiment. The process 800 may include monitoring the mud volumes in the inactive pit(s), as at 802. For example, a change point analysis or other segmentation technique may be applied thereto, e.g., in a continuous manner.

[0060] At some point, the monitoring activity at 802 may indicate that there is a change in the mud level in one of the inactive pits (or the inactive pit, if the mud system 300 includes a single inactive pit), as at 804. As discussed above, the change in mud level may be over a threshold, e.g., to account for noise in the measurement. The change in mud level may be an increase or a decrease in the level of mud in the inactive pit. As such, the level of mud in the inactive pit is the first trigger for determining whether a transfer has occurred. If such mud level changes in the inactive pit do not precede a change in mud level in the active pit, then the change in mud level in the active pit may be attributed to a downhole gain/loss event or another event not caused by a transfer.

[0061] Once a change in mud level in the inactive pit(s) is identified at 804, the process 800 may proceed to determining whether there is a corresponding change in the mud level in another inactive pit, as at 806. For example, in some situations, there may be more than one inactive pit, and there may be cause to transfer fluid between these inactive pits, e.g., to change composition, balance levels, etc. Accordingly, if the volume in one inactive pit changes, the process 800 checks to see if the mud volume in another inactive pit accounts for this change, which would maintain the mud outside of the active system and thus not affect the active mud volume. If another inactive pit mud level changes to account for the change in the first mud pit, the process 800 proceeds to 808, where the boundaries (baseline level) of the inactive pit is changed, and the process 800 returns to monitoring mud levels in the active pit(s) at 802.

[0062] If there are no corresponding changes in other inactive pits (or if there are no other inactive pits, or if the change in the inactive pits does not fully account for the change in the inactive pit identified at 802), the process 800 may proceed to determining if there is a corresponding change in the mud volume of the active pit, as at 810. As explained above, this may be evaluated based on the mud volume balance, i.e., comparing a predicted mud volume in the active pit with the measured value, rather than or in addition to comparing the raw change in volume in the active pit. If there is not a corresponding change in the level of the active pit detected at 810, there may be some other event occurring in the system or in the well, which may be separately addressed. [0063] If there is a corresponding change in the active pit (e.g., as evidenced by the mud volume balance), then a mud transfer from an inactive pit to an active pit is determined to have occurred. Accordingly, a kick alarm may not be appropriate. As such, if the kick alarm has been activated, it may be deactivated, as at 812, or otherwise not activated. The process 800 may then proceed to changing the boundary of the active pit mud volume 814, so as to bring the modeled mud volume back into agreement with the measured mud volume (e.g., recalibrating the model so the mud balance is or is nearly zero).

[0064] Figure 9 illustrates a flowchart of a method 900 for monitoring and/or controlling a mud system of a drilling rig, according to an embodiment. The method 900 may include pumping mud in the mud system, as at 902. Further, the method 900 may include modeling mud losses during a transient flow period, as at 904. Transient flow periods may occur immediately after pump start and pump stop. In an embodiment, mud loss during transient flow periods may be predominately due to formation permeability, and such losses may be modeled as discussed above, e.g., using a permeability coefficient k.

[0065] Further, the method 900 may include modeling mud losses during steady-state flow periods, as at 906. Mud losses during steady-state flow periods may be predominately attributed to surface mud losses, e.g., from the shaker, along with the drill cuttings. In some embodiments, the mud losses during stead-state flow periods may be modeled based on a surface loss coefficient b, as discussed above.

[0066] The method 900 may also include monitoring (e.g., continuously or periodically measuring) mud volume levels in active and inactive pits of the mud system, as at 908. Active pits are those pits through which mud is circulated during normal pumping operations. Inactive pits may store reserves of mud, and mud may be transferred from the inactive pits to the active pits for use in the mud system. As such, fluid is not continuously circulated through the inactive pits and into/out of the well during normal pumping operations.

[0067] During the operation of the mud system, and based partially on the mud losses, and also on other factors such as mud flow rate, surface equipment, downlinker operation, etc., the method 900 may include calculating a mud balance for the active mud pits, as at 910. The mud balance for the active pits may be a difference between a measured mud volume in the active pit(s) and a mud volume predicted by the model. [0068] The method 900 may periodically (re)calibrate the model for either or both of the transient losses and/or the steady-state losses, as at 912 The calibration of these losses is discussed above. In some embodiments, the steady-state losses may be calibrated during a first steady-state flow period, and then recalibrated when surface or flow conditions change, e.g., when a shaker screen is blocked. The transient state losses may be recalibrated after a first pump start, or after each pump start, or the like.

[0069] The method 900 may also include detecting a mud transfer from an inactive pit to the active pit based on a combination of the mud volume in the inactive pit and the mud balance, as at 914 As discussed above, the detection of a transfer may be a two-part (at least) determination. First, a change in mud volume in one of the inactive pits is detected. If there is no change in the mud volume in the inactive pit, then there is no transfer to/from an inactive pit, and thus any changes in the mud volume in the active pit may be attributed to other circumstances, such as downhole mud gain or loss.

[0070] Once a change in mud volume in one of the inactive pits is detected, it is then determined if there is a corresponding change in mud volume in another inactive pit (indicating no transfer between the inactive pits and the active pit) or in the mud volume of the active pit. However, as discussed above, the mud volume in the active pit may not be static, given that it is circulating into and out of the well, e.g., transient flow conditions can make identification of a change in the active mud pit volume difficult to identify.

[0071] Accordingly, the method 900 may base the detection of the mud transfer on the mud volume balance deviating by a certain amount, e.g., corresponding to (or roughly the same as) the change in the mud volume of the inactive pit. If the deviation of the mud volume balance corresponds to the change in the mud volume in the inactive pit(s), then the method 900 may determine that a transfer, rather than a downhole gain/loss event, has occurred, and any kick alarms or the like may be deactivated (or otherwise not activated). Further, the method 900 may include adjusting the model (e.g., the modeled mud volume in the active pit) to account for the transfer, as at 916 The mud volume balance may thus be prepared to form the basis for a detection of a gain/loss event downhole, e.g., by accurately modeling “normal” mud losses in the system (e.g., through the shaker or based on formation permeability) and accounting for transfers in the mud volume balance, so as to permit downhole mud loss/gains to be distinguished from normal operation and transfers. [0072] Figure 10 illustrates two plots 1000 and 1002 illustrating the operation of the method 900, according to an embodiment. In the first plot 1000, measured active mud volume 1004 (i.e., volume circulating through the mud system, e.g., as measured at the active mud pit(s)) is compared with theoretical (calculated based on a model) active mud volume 1006. In the second plot 1002, a real time mud volume balance (difference between measured and active mud volume) 1008 and an “adjusted” mud volume balance 1010, which accounts for transfers, are shown.

[0073] As can be seen, the trend for theoretical volume 1006 in the first plot 1000 is generally decreasing. The measured mud volume 1004 tracks this, until an event 1020 occurs. The event 1020 leads to the measured mud volume 1004 sharply increasing over the theoretical volume 1006. Generally, this is indicative of a downhole mud gain (e.g., a kick), which may be a hazardous condition, or a transfer of mud from one or more inactive pits to the active pit, which is not a hazardous condition.

[0074] The second plot 1002 shows how the detection of the event 1020 affects the mud volume balance. As would be expected from the difference between the lines 1004, 1006, the mud volume balance spikes beginning at the event 1020.

[0075] In response to the event 1020, in at least some embodiments, an alarm may be activated, and at least one task of the method 900 may be to determine if the alarm is justified (e.g., a kick has occurred/is occurring) or not. To do this, the method 900 determines if there was also a transfer, e.g., by reference to the mud volume balance and the inactive much volume, as discussed above. The transfer determination may occur in parallel to the monitoring of the mud volume, or may occur in response to an alarm being activated. The transfer determination is discussed in detail above. If a transfer is determined, the alarm may be deactivated.

[0076] In another embodiment, an alarm may not be immediately activated in response to detection of the event 1020. Rather, a flag or warning may be set in response to the event 1020, and the method 900 may determine whether an alarm should be activated. In order to do this, the method 900 may check for the occurrence of a transfer, as discussed above. If a transfer occurred, the method 900 refrains from activating the alarm, and otherwise actives the alarm.

[0077] If a transfer is determined, the model of mud in the active system may be updated, which may serve to “revise” the mud balance to take into account the transfer of mud. As can be seen in the second plot 1002, the real time mud balance 1008 is adjusted such that it is nearly zero, reflecting that the mud model is accurately predicting the active mud volume, now that the transfer is taken into consideration. [0078] The revision may be prospective from the point of view of the user. For example, there may be a delay or buffer in the delivery of the mud measurements to the user, such that a transfer may be detected and accommodated in the model and the mud volume balance revised before the user receives the measurements. Alternatively, the mud volume balance can be revised, in a backward-looking fashion, when the mud transfer is determined. In either case, an alarm may initially be activated and then deactivated if a transfer is detected, or it may be decided whether to activate or refrain from activating such an alarm before it is activated based on whether a transfer is detected.

[0079] Thus, it will be seen that the present system and methods have several practical applications. For example, a kick alarm, which may be initiated automatically in response to an increase in the mud balance and/or an increase in the active pit volume, may be quickly and efficiently verified or identified as being false and deactivated. In particular, embodiments of the present disclosure may make a robust determination, which considers mud losses both at the surface and in the well, as well as transfers of fluid between the inactive and active pits. This may facilitate the control and operation of the mud system, which is used to circulate mud through the well, e.g., via pumping the mud from the active pit into the well and back into the active pit. [0080] In some embodiments, the methods of the present disclosure may be executed by a computing system. Figure 11 illustrates an example of such a computing system 1100, in accordance with some embodiments. The computing system 1100 may include a computer or computer system 1101 A, which may be an individual computer system 1101 A or an arrangement of distributed computer systems. The computer system 1101 A includes one or more analysis modules 1102 that are 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 1102 executes independently, or in coordination with, one or more processors 1104, which is (or are) connected to one or more storage media 1106. The processor(s) 1104 is (or are) also connected to a network interface 1107 to allow the computer system 1101 A to communicate over a data network 1109 with one or more additional computer systems and/or computing systems, such as 1101B, 1101C, and/or 1101D (note that computer systems 1101B, 1101C and/or 1101D may or may not share the same architecture as computer system 1101 A, and may be located in different physical locations, e.g., computer systems 1101 A and 1101B may be located in a processing facility, while in communication with one or more computer systems such as 1101C and/or 110 ID that are located in one or more data centers, and/or located in varying countries on different continents). [0081] A processor may include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.

[0082] The storage media 1106 may be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of Figure 11 storage media 1106 is depicted as within computer system 1101 A, in some embodiments, storage media 1106 may be distributed within and/or across multiple internal and/or external enclosures of computing system 1101 A and/or additional computing systems. Storage media 1106 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 may be provided on one computer-readable or machine-readable storage medium, or may 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). An article or article of manufacture may refer to any manufactured single component or multiple components. The storage medium or media may be located either in the machine running the machine-readable instructions, or located at a remote site from which machine- readable instructions may be downloaded over a network for execution.

[0083] In some embodiments, computing system 1100 contains one or more mud control module(s) 1108. In the example of computing system 1100, computer system 1101 A includes the mud control module 1108. In some embodiments, a single mud control module may be used to perform some aspects of one or more embodiments of the methods disclosed herein. In other embodiments, a plurality of mud control modules may be used to perform some aspects of methods herein.

[0084] It should be appreciated that computing system 1100 is merely one example of a computing system, and that computing system 1100 may have more or fewer components than shown, may combine additional components not depicted in the example embodiment of Figure 11, and/or computing system 1100 may have a different configuration or arrangement of the components depicted in Figure 11. The various components shown in Figure 11 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.

[0085] Further, the steps in the processing methods described herein may be implemented by running one or more functional modules in information processing apparatus such as general purpose processors or application specific chips, such as ASICs, FPGAs, PLDs, or other appropriate devices. These modules, combinations of these modules, and/or their combination with general hardware are included within the scope of the present disclosure.

[0086] Computational interpretations, models, and/or other interpretation aids may be refined in an iterative fashion; this concept is applicable to the methods discussed herein. This may include use of feedback loops executed on an algorithmic basis, such as at a computing device (e.g., computing system 1100, Figure 11), 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 subsurface three-dimensional geologic formation under consideration.

[0087] The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or limiting to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. Moreover, the order in which the elements of the methods described herein are illustrate and described may be re-arranged, and/or two or more elements may occur simultaneously. The embodiments were chosen and described in order to best explain the principles of the disclosure and its practical applications, to thereby enable others skilled in the art to best utilize the disclosed embodiments and various embodiments with various modifications as are suited to the particular use contemplated.

Claims

CLAIMS What is claimed is:

1. A method for monitoring and controlling a mud flow system in a drilling rig, comprising: measuring an active mud volume in an active mud pit and an inactive mud volume in an inactive mud pit; modeling a modeled active mud volume in the active mud pit; determining a mud volume balance by calculating a difference between the measurement of the active mud volume and the modeled active mud volume; detecting a transfer of mud from the inactive mud pit to the active mud pit based on a combination of a change in the measurement of the inactive mud volume in the inactive mud pit and a change in the mud volume balance; and detecting downhole gains and losses automatically based on the mud volume balance.

2. The method of claim 1, further comprising revising the mud volume balance to account for the transfer, in response to detecting the transfer.

3. The method of claim 1, wherein modeling the modeled active mud volume comprises: determining a permeability loss coefficient during transient flow periods; and determining a surface loss coefficient during steady-state periods, wherein the modeled active mud volume is modeled based on a combination of the permeability loss coefficient and the surface loss coefficient.

4. The method of claim 3, wherein the permeability loss coefficient is related to mud flow into or out of a subterranean formation, and wherein surface loss coefficient is related at least in part to mud flow out of a shaker of a drilling system.

5. The method of claim 3, further comprising recalibrating the surface loss coefficient during a steady-state flow period after a first pump start and before a first pump stoppage, wherein the surface loss coefficient is not recalibrated after the first pump stoppage and before a second pump stoppage.

6. The method of claim 3, further comprising recalibrating the permeability loss coefficient during a pump start, before reaching a steady-state flow period after the pump start.

7. The method of claim 1, wherein detecting the transfer of mud comprises: determining that the inactive mud volume has changed by more than a threshold amount; and in response to determining that the inactive mud volume has changed, determining that the mud volume balance has changed to compensate for the inactive mud volume changing.

8. The method of claim 7, wherein detecting the transfer of mud further comprises determining that a mud volume in another inactive mud pit has not changed to compensate for the change in the inactive mud volume, wherein determining that the mud volume balance has changed to compensate for the inactive mud volume changing is also in response to determining that the mud volume in the other inactive mud pit has not changed to compensate.

9. The method of claim 1, further comprising deactivating or refraining from activating a kick alarm in response to detecting the transfer of mud.

10. The method of claim 1, further comprising pumping mud into a well using the mud flow system, wherein the mud is circulated through the active mud pit.

11. A computing system, comprising: one or more processors; and a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising: measuring an active mud volume in an active mud pit and an inactive mud volume in an inactive mud pit; modeling a modeled active mud volume in the active mud pit; determining a mud volume balance by calculating a difference between the measurement of the active mud volume and the modeled active mud volume; detecting a transfer of mud from the inactive mud pit to the active mud pit based on a combination of a change in the measurement of the inactive mud volume in the inactive mud pit and a change in the mud volume balance; and detecting downhole gains and losses automatically based on the mud volume balance.

12. The computing system of claim 11, wherein the operations further comprise revising the mud volume balance to account for the transfer, in response to detecting the transfer.

13. The computing system of claim 11, wherein modeling the modeled active mud volume comprises: determining a permeability loss coefficient during transient flow periods; and determining a surface loss coefficient during steady-state periods, wherein the modeled active mud volume is modeled based on a combination of the permeability loss coefficient and the surface loss coefficient.

14. The computing system of claim 13, wherein the permeability loss coefficient is related to mud flow into or out of a subterranean formation, and wherein surface loss coefficient is related at least in part to mud flow out of a shaker of a drilling system.

15. The computing system of claim 13, wherein the operations further comprise recalibrating the surface loss coefficient during a steady-state flow period after a first pump start and before a first pump stoppage, wherein the surface loss coefficient is not recalibrated after the first pump stoppage and before a second pump stoppage.

16. The computing system of claim 13, wherein the operations further comprise recalibrating the permeability loss coefficient during a pump start, before reaching a steady-state flow period after the pump start.

17. The computing system of claim 11, wherein detecting the transfer of mud comprises: determining that the inactive mud volume has changed by more than a threshold amount; and in response to determining that the inactive mud volume has changed, determining that the mud volume balance has changed to compensate for the inactive mud volume changing.

18. The computing system of claim 17, wherein detecting the transfer of mud further comprises determining that a mud volume in another inactive mud pit has not changed to compensate for the change in the inactive mud volume, wherein determining that the mud volume balance has changed to compensate for the inactive mud volume changing is also in response to determining that the mud volume in the other inactive mud pit has not changed to compensate.

19. A computing system, comprising: one or more processors; and a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising: measuring an active mud volume in an active mud pit and an inactive mud volume in an inactive mud pit; modeling a modeled active mud volume in the active mud pit; determining a mud volume balance by calculating a difference between the measurement of the active mud volume and the modeled active mud volume; detecting a transfer of mud from the inactive mud pit to the active mud pit based on a combination of a change in the measurement of the inactive mud volume in the inactive mud pit and a change in the mud volume balance; and detecting downhole gains and losses automatically based on the mud volume balance.

20. The computing system of claim 19, wherein the operations further comprise revising the mud volume balance to account for the transfer, in response to detecting the transfer, and wherein modeling the modeled active mud volume comprises: determining a permeability loss coefficient during transient flow periods; and determining a surface loss coefficient during steady-state periods, wherein the modeled active mud volume is modeled based on a combination of the permeability loss coefficient and the surface loss coefficient.