how to measure mud pump efficiency made in china

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Rig pump output, normally in volume per stroke, of mud pumps on the rig is  one of important figures that we really need to know because we will use pump out put figures to calculate many parameters such as bottom up strokes,  wash out depth, tracking drilling fluid, etc. In this post, you will learn how to calculate pump out put for triplex pump and duplex pump in bothOilfield and Metric Unit.

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The mud pump piston is a key part for providing mud circulation, but its sealing performance often fails under complex working conditions, which shorten its service life. Inspired by the ring segment structure of earthworms, the bionic striped structure on surfaces of the mud pump piston (BW-160) was designed and machined, and the sealing performances of the bionic striped piston and the standard piston were tested on a sealing performance testing bench. It was found the bionic striped structure efficiently enhanced the sealing performance of the mud pump piston, while the stripe depth and the angle between the stripes and lateral of the piston both significantly affected the sealing performance. The structure with a stripe depth of 2 mm and angle of 90° showed the best sealing performance, which was 90.79% higher than the standard piston. The sealing mechanism showed the striped structure increased the breadth and area of contact sealing between the piston and the cylinder liner. Meanwhile, the striped structure significantly intercepted the early leaked liquid and led to the refluxing rotation of the leaked liquid at the striped structure, reducing the leakage rate.

Mud pumps are key facilities to compress low-pressure mud into high-pressure mud and are widely used in industrial manufacture, geological exploration, and energy power owing to their generality [1–4]. Mud pumps are the most important power machinery of the hydraulic pond-digging set during reclamation [5] and are major facilities to transport dense mud during river dredging [6]. During oil drilling, mud pumps are the core of the drilling liquid circulation system and the drilling facilities, as they transport the drilling wash fluids (e.g., mud and water) downhole to wash the drills and discharge the drilling liquids [7–9]. The key part of a mud pump that ensures mud circulation is the piston [10, 11]. However, the sealing of the piston will fail very easily under complex and harsh working conditions, and consequently, the abrasive mud easily enters the kinematic pair of the cylinder liner, abrading the piston surfaces and reducing its service life and drilling efficiency. Thus, it is necessary to improve the contact sealing performance of the mud pump piston.

As reported, nonsmooth surface structures can improve the mechanical sealing performance, while structures with radial labyrinth-like or honeycomb-like surfaces can effectively enhance the performance of gap sealing [12–14]. The use of nonsmooth structures into the cylinder liner friction pair of the engine piston can effectively prolong the service life and improve work efficiency of the cylinder liner [15–17]. The application of nonsmooth grooved structures into the plunger can improve the performance of the sealing parts [18, 19]. The nonsmooth structures and sizes considerably affect the sealing performance [20]. Machining a groove-shaped multilevel structure on the magnetic pole would intercept the magnetic fluid step-by-step and slow down the passing velocity, thus generating the sealing effect [21–23]. Sealed structures with two levels or above have also been confirmed to protect the sealing parts from hard damage [24]. The sealing performance of the high-pressure centrifugal pump can be improved by adding groove structures onto the joint mouth circumference [25]. The convex, pitted, and grooved structures of dung beetles, lizards, and shells are responsible for the high wear-resistance, resistance reduction, and sealing performance [26–28]. Earthworms are endowed by wavy nonsmooth surface structures with high resistance reduction and wear-resistance ability [29]. The movement of earthworms in the living environment is very similar to the working mode of the mud pump piston. The groove-shaped bionic piston was designed, and the effects of groove breadth and groove spacing on the endurance and wear-resistance of the piston were investigated [30]. Thus, in this study, based on the nonsmooth surface of earthworms, we designed and processed a nonsmooth striped structure on the surface of the mud pump piston and tested the sealing performance and mechanism. This study offers a novel method for prolonging the service life of the mud pump piston from the perspective of piston sealing performance.

The BW-160 mud pump with long-range flow and pressure, small volume, low weight, and long-service life was used here. The dimensions and parameters of its piston are shown in Figure 1.

A striped structure was designed and processed on the contact surface between the piston cup and the cylinder liner. The striped structure was 5 mm away from the outermost part of the lip, which ensured the lip could contact effectively with the cylinder liner. Based on the structural dimensions of the piston cup, we designed a 2-stripe structure, and the very little stripe space affected the service life of the piston [30]. Thus, the stripe space of our bionic piston was set at 5 mm. According to the machining technology, two parameters of stripe depth h and the angle between the stripes and lateral of the piston α were selected (Figure 2).

A mud pump piston sealing performance test bench was designed and built (Figure 3). This bench mainly consisted of a compaction part and a dynamic detection part. The compaction part was mainly functioned to exert pressure, which was recorded by a pressure gauge, to the piston sealed cavity. This part was designed based on a vertical compaction method: after the tested piston and the sealing liquid were installed, the compaction piston was pushed to the cavity by revolving the handle. Moreover, the dynamic detection part monitored the real-time sealing situation and was designed based on the pressure difference method for quantifying the sealing performance. This part was compacted in advance to the initial pressure P0 (0.1 MPa). After compaction, the driving motor was opened, and the tested piston was pushed to drive the testing mud to reciprocate slowly. After 1 hour of running, the pressure P on the gauge was read, and the pressure difference was calculated as , which was used to measure the sealing performance of the piston.

To more actually simulate the working conditions of the mud pump, we prepared a mud mixture of water, bentonite (in accordance with API Spec 13A: viscometer dial reading at 600 r/min ≥ 30, yield point/plastic viscosity radio ≤ 3, filtrate volume ≤ 15.0 ml, and residue of diameter greater than 75 μm (mass fraction) ≤ 4.0%), and quartz sand (diameter 0.3–0.5 mm) under complete stirring, and its density was 1.306 g/cm³ and contained 2.13% sand.

The orthogonal experimental design method was used to study the effect of factors and the best combination of factor levels [31]. Stripe depth h and angle α were selected as the factors and were both set at three levels in the sealing performance tests (Table 1).

The test index was the percentage of sealing performance improvement β calculated aswhere and are the pressure differences after the runs with the standard and the bionic pistons, respectively ().

The sealing performance tests showed the striped structures all effectively enhanced the contact sealing between the piston and the cylinder liner. In particular, the increase of sealing performance relative to the standard piston minimized to 21.05% in the bionic striped piston with a stripe depth of 3 mm and angle of 45° and maximized to 90.79% in the bionic striped piston with the stripe depth of 2 mm and angle of 90°. Range analysis showed the sealing performance of pistons was affected by the stripe depth h and angle α, and these two parameters (h and α) have the same effect on the sealing performance.

Figure 4 shows the effects of stripe depth and angle on the sealing performance of mud pump pistons. Clearly, the stripe depth should be never too shallow or deep, while a larger angle would increase the sealing performance more (Figure 4).

Sealing validity tests were conducted to validate the sealing performance of the bionic striped pistons. It was observed whether the sealing liquid would leak at the tail of the cylinder liner, and the time of leakage was recorded. The standard piston and the most effective bionic piston were selected to compare their sealing performances.

Both the standard piston and the bionic striped piston leaked, which occurred after 84 and 249 minutes of operation, respectively (Figure 5). Figure 6 shows the pressures of the two pistons during testing. Clearly, the sealing pressure of the standard piston declined rapidly before the leakage, but that of the bionic piston decreased very slowly. After the leakage, the reading on the pressure gauge in the standard piston declined to 0 MPa within very short time, but that of the bionic piston decreased much more slowly.

The beginning time of leakage was inconsistent between the standard and bionic pistons (84 minutes vs. 249 minutes). In order to compare the leakage of these two pistons, the leaked liquid was collected when the piston started to leak. The volume of the leaked liquid was measured using a graduated cylinder every 5 minutes from the 84th minute and 249th minute, respectively (both considered as 0 minute), for 20 minutes. Figure 7 shows the leaked amounts of the standard piston and the bionic piston. Clearly, after the leakage and failure, the leaking speed and amount of the bionic piston were both smaller than those of the standard piston.

The piston lips and the cylinder liner were under interference contact, and their mutual extrusion was responsible for the lip sealing. Thus, a larger pressure between the piston lips and the cylinder liner reflects a higher lip sealing effect.

The bionic striped piston with the highest sealing performance (h = 2 mm, α = 90°) was selected for the sealing mechanism analysis and named as the bionic piston. The 3D point cloud data of standard piston were acquired by using a three-dimensional laser scanning system (UNIscan, Creaform Inc., Canada). Then, the standard piston model was established by the reverse engineering technique. The striped structure of the bionic piston was modeled on basis of the standard piston.4.1.1. Contact Pressure of Piston Surface

The standard piston and the bionic piston were numerically simulated using the academic version of ANSYS® Workbench V17.0. Hexahedral mesh generation method was used to divide the grid, and the size of grids was set as 2.5 mm. The piston grid division is shown in Figure 8, and the grid nodes and elements are shown in Table 3. The piston cup was made of rubber, which was a hyperelastic material. A two-parameter Mooney–Rivlin model was selected, with C10 = 2.5 MPa, C01 = 0.625 MPa, D1 = 0.3 MPa−1, and density = 1120 kg/m3 [32, 33]. The loads and contact conditions related to the piston of the mud pump were set. The surface pressure of the piston cup was set as 1.5 MPa, and the displacement of the piston along the axial direction was set as 30 mm. The two end faces of the cylinder liner were set as “fixed support,” and the piston and cylinder liner were under the frictional interfacial contact, with the friction coefficient of 0.2.

Figure 9 shows the pressure clouds of the standard piston and the bionic piston. Since the simulation model was completely symmetrical and the pressures at the same position of each piston were almost the same, three nodes were selected at the lip edge of each piston for pressure measurement, and the average of three measurements was used as the lip edge pressure of each piston. The mutual extrusion between piston and cylinder liner happened at the lip, and thereby the larger of the lip pressure was, the better the sealing performance was. The lip pressure of the standard piston was smaller than that of the bionic piston (2.7371 ± 0.016 MPa vs. 3.0846 ± 0.0382 MPa), indicating the striped structure enhanced the mutual extrusion between the bionic piston and the cylinder liner and thereby improved the sealing performance between the lips and the cylinder liner. As a result, sand could not easily enter the piston-cylinder liner frictional interface, which reduced the reciprocated movement of sand and thereby avoided damage to the piston and the cylinder liner.

Figure 10 shows the surface pressures from the lip mouth to the root in the standard piston and the bionic piston. The surface pressure of the bionic piston surpasses that of the standard piston, and the pressure at the edge of each striped structure changes suddenly: the pressures at the striped structure of the bionic piston are far larger than at other parts. These results suggest the contact pressure between the edges of the striped structures and the cylinder liner is larger, and the four edges of the two striped structures are equivalent to a four-grade sealed lip mouth formed between the piston and the cylinder liner, which generates a multilevel sealing effect and thereby largely enhances the sealing effect of the piston.

The piston surface flow field was numerically simulated using the CFX module of the software ANSYS® Workbench V17.0. The side of the lips was set as fluid inlet, and the other side as fluid outlet, as shown in Figure 11. The inlet and outlet were set as opening models, and the external pressure difference between them was 0 Pa. The moving direction of the piston was opposite to the fluid flow direction. The fluid region was divided into grids of 0.2 mm, while the striped structures were refined to grade 2.

Figures 12 and 13 show the surface streamline clouds and sectional streamline clouds of the two pistons at the early stage of leakage when the fluid entered the interface. Clearly, compared with the standard piston, when the surface-leaked liquid from the bionic piston passed the striped structure, the streamlines were sparse and significantly decreased in number, and the flow velocity declined more. The flow velocity decreased from 0.9348 m/s to 0.7555 m/s in the bionic piston and from 0.9346 m/s to 0.9262 m/s in the standard piston. It shows that, after the blockage by the striped structures, the striped structure more significantly intercepted the leaked liquid and could reduce the leakage rate of the piston, thereby enhancing the sealing effect.

Figure 13 shows the section leakage streamline of the standard piston and the bionic piston. Clearly, compared with the standard piston, when the leaked liquid of the bionic piston flowed through the striped structures, the streamlines would reflux and reverse inside the striped structures, indicating the striped structures can efficiently store the leaked liquid and slow down the leakage.

To better validate the sealing mechanism of the bionic striped pistons, a piston’s performance testing platform was independently built and the sealed contact of the pistons was observed. A transparent toughened glass cylinder liner was designed and machined. The inner diameter and the assembly dimensions of the cylinder liner were set according to the standard BW-160 mud pump cylinder liners. The sealing contact surfaces of the pistons were observed and recorded using a video recorder camera.

Figure 14 shows the surface contact of the standard piston and the bionic piston. Clearly, in the contact areas between the standard piston and the cylinder liner, only the narrow zone at the lip mouth contacted, as the contact width was only 4.06 mm. On the contrary, the contact areas between the bionic piston and the cylinder liner were all very wide, as the contact width was about 18.36 mm, and the sealed area was largely enlarged (892.8 mm2 vs. 4037.6 mm2) according to the contact areas calculated, which were favorable for improving the sealing performance.

Figure 15 shows the oil film left after the piston running. The oil film width of the bionic piston was far larger than that of the standard piston (20.48 mm vs. 2.28 mm). The striped structure of the bionic piston could store the lubricating oils, and uniform oil films were formed after its repeated movement, which reduced the friction between the piston and the cylinder liner, so that the seal failure of the piston would not happen due to excessive abrasion.

(1)The bionic striped structure significantly enhanced the sealing performance of the mud pump pistons. The stripe depth and the angle between the stripes and the piston were two important factors affecting the sealing performance of the BW-160 mud pump pistons. The sealing performance was enhanced the most when the stripe depth was 2 mm and the angle was 90°.(2)The bionic striped structure can effectively enhance the contact pressure at the piston lips, enlarge the mutual extrusion between the piston and the cylinder liner, reduce the damage to the piston and cylinder liner caused by the repeated movement of sands, and alleviate the abrasion of abrasive grains between the piston and the cylinder liner, thereby largely improving the sealing performance.(3)The bionic striped structure significantly intercepted the leaked liquid, reduced the leakage rate of pistons, and effectively stored the leaked liquid, thereby reducing leakage and improving the sealing performance.(4)The bionic striped structure led to deformation of the piston, enlarged the width and area of the sealed contact, the stored lubricating oils, and formed uniform oil films after repeated movement, which improved the lubrication conditions and the sealing performance.

The bionic striped structure can improve the sealing performance and prolong the service life of pistons. We would study the pump resistance in order to investigate whether the bionic striped structure could decrease the wear of the piston surface.

Find W series mud pump from pressure grouting pump manufacturer - Saigao gruop in China. The W series mud pump can be widely used in all kinds of works in oil field, which is su...

The ballasted track currently remains one of the few leading types of railway track structures due to the advantages in construction and maintenance [1,2]. However, the particulate nature of ballast particles often leads to performance degradation of ballasted trackbed. For example, the abrasion and breakage of ballast particles intensify with increasing axle load and train speed, thus causing the unfavorable densification, fouling, and clogging (i.e., reduced drainability) problems in ballasted tracked [3,4,5]; consequently, mud pumps, among other commonly observed track problems, can be prompted within such fouled ballasted trackbed [6,7]. Mud pumps could seriously degrade track stiffness and thus endanger operational safety of railway trains [8,9,10]. Traditional manual inspection and detection of mud pumps and other track problems are often labor-intensive, time-consuming, and subjective in nature; therefore, it becomes indispensable to develop automated, intelligent, and accurate means for the early-age diagnosis and detection of mud-pumping risks in ballasted trackbed so that remedial maintenance measures can be timely taken according to real-time health condition rather than the fixed schedules.

The root cause of mud-pumping fault has remained a widely-studied but challenging topic. Tadatoshi [11] proposed a suction-driven model and showed that the main cause of mud pumps is the intrusion of fine particles from the subgrade generated by the suction of ballast bed during the loading and unloading cycles. Raymond [12] found that the freeze-thaw cycles can cause fine-grained materials to pump out of the ballasted trackbed in winters according to a field performance investigation of the North American railway geotextiles. Duong et al. [13,14] believed that the interlayer materials between the subgrade and the ballasted trackbed were mainly generated by broken ballast particles, which then penetrated into the subgrade surface. The formerly Transportation Technology Center, Inc. (TTCI) established a field-testing zone to further study mud pumps [10,15,16,17]. Despite a considerable number of research studies have been carried out to explore the mechanisms of mud pumping fault, there still lacks radical countermeasures to prevent and control it in railway engineering practices.

The accurate early-age diagnosis and detection of mud pumps are the key step on which timely and effective prevention and control measures depend. The late-stage mud-pumping fault manifested on the surface of ballasted tracked is relatively easy to detect through routine labor-intensive methods; however, it is quite challenging to directly identify the early-age mud-pumping problem initiated inside the thick ballasted trackbed. The ground penetrating radar (GPR) technology has been widely applied in the non-destructive detection of structural faults in railway ballasted trackbed and subgrade [10,18,19,20]. Hugenschmidt [21] successfully applied GPR in the detection of railway subgrade problems for the first time in 1998. Since then, many countries including China have conducted related field and laboratory studies in this field [22,23]. Trong Vinh Duong et al. [13] carried out physical model tests and analyzed the influencing factors of the mud-pumping problem occurring in the interlayer between the ballast bed and underlying subgrade, including particle size distribution, moisture content, pore water pressure, hydraulic conductivity, etc. Kuo et al. [24] developed a characterized grid method and a scoring method to assess the mud-pumping distribution with an accuracy rate of 80%. Although the GPR technology has been reported to successfully detect visible or hidden mud-pumping problems in ballasted railway tracks [21], the accuracy and reliability of different GPR equipment and supporting post-processing software programs still vary considerably, not to mention the fact that they are highly costly and unaffordable for routine applications. In addition to GPR, other techniques have also been widely used for non-destructive detection of railway track foundation problems in recent years, such as the digital image correlation (DIC) [25,26,27], Interferometric Synthetic Aperture Radar (InSAR) [25], impact-echo method (IEM) [28], and synthetic aperture focusing technology (SAFT) [29,30]. However, these methods all require costly equipment and/or highly specialized skills that railway engineering practitioners usually lack. Therefore, to diagnose the in-service health condition and detect invisible problems of the ballasted trackbed accurately and reliably, it becomes imperative to explore automated, intelligent, and universally applicable methods in lieu of traditional ones.

The occurrence of mud pumps could cause uneven (or differential) rail track settlement and increasing track irregularities [31,32,33]. The existence of track irregularities could not only compromise the operational safety of heavy-haul trains but also degrade track substructures [34,35,36]. Li et al. [37,38] proposed a data-driven method for infrastructure deformation identification based on the characteristics of track geometry data, as well as a spatio-temporal identification model for identifying high-speed railway infrastructure deformation by using four years of track geometry data. Li et al. [39] analyzed the time and frequency characteristics of track geometry irregularity signals at the locations of mud pumps and used a multi-scale signal decomposition method to extract defect-sensitive features and then realize automatic detection of mud pumping problems. The nearly continuous and real-time track health monitoring of the entire rail networks could be possibly accomplished in a timely and cost-efficient manner by mounting robust sensors on in-service trains. For example, the problematic sections of railway track sub-structures were reportedly detected by using the vertical acceleration responses of a moving train [40]. Zeng et al. [41] proposed a data-driven approach for identifying mud pumps in the railway track substructure based on vibrational acceleration responses and Long Short-Term Memory (LSTM) artificial neural networks. The vibrational responses of ballastless slab tracks were also compared to detect the locations of mud pumps and study the feasibility of technical countermeasures to rectify and control the mud-pumping damage [42]. Therefore, analyzing the vibrational responses of the ballasted trackbed appears to be potentially helpful and promising for intelligent detection of mud-pumping problems in railway tracks.

Particle movement is a meso-scale manifestation of inter-particle contact behavior of ballast assemblies within the ballast bed; therefore, investigating the meso-scale movement characteristics of ballast particles may emerge as a promising, effective alternative to diagnose and identify the mud-pumping problem of ballasted tracked. The use of motion sensors (termed as “SmartRocks”) has been reported in the literature to directly capture real-time movement of ballast particles and then evaluate the field performance of ballasted trackbed under different in-service conditions [43,44,45,46,47]. The applications of such so-called SmartRock sensors in effective and accurate measurements of the vibrational responses of unbound aggregate particles including railroad ballasts were demonstrated in laboratory scaled model tests and triaxial tests [43,48,49,50]. Liu et al. [51] compared the ballast particle motion data measured by SmartRock sensors against those simulated by the discrete element method (DEM) model. Preliminary studies [52,53] suggested that SmartRock sensors could be used as a potential tool to quantify ballast behavior without using invasive measurement devices or disrupting railroad operations and to reflect the variations of dynamic behavior of ballasted trackbed under different substructure conditions. However, the widespread, reliable field applications of this new smart sensing technology for detecting invisible track defects such as mud pumps within ballasted trackbed remains to be extensively explored.

The purpose of this paper was to further study and substantiate the feasibility of SmartRock sensors in real-world field applications to diagnose and identify mud-pumping risks in ballasted trackbed. Therefore, a typical section of heavy-haul railway ballast bed with severe mud pumping problems was chosen for investigation, where the SmartRock sensors were employed and instrumented accordingly to monitor particle-scale acceleration responses prior to, during, and after major maintenance operations including ballast-cleaning and tamping. The three-dimensional (3D) acceleration responses and associated marginal spectra of ballast particles recorded by SmartRock sensors in different positions were comparatively analyzed for the initial degraded and subsequent rectified scenarios of the ballast bed. The findings are expected to contribute to the optimization of maintenance operation parameters and smart track health monitoring.

An expert system is being developed to automatically detect and diagnose several important circulation system problems in geothermal drilling. The system is called the Circulation Monitoring System (CMS) and will be useful for detecting, characterizing, and quantifying lost circulation, fluid influx, gas/steam kicks, loss of mud pump efficiency, washouts, plugged nozzles, and sensor problems. Data from the outflow meter, pump-stroke counter, inflow meter, pit volume indicator, standpipe pressure sensor, and other sensors are processed by a Kalman filter and examined for deviations from expected patterns. The deviations are transformed into evidence for a Bayesian Network, which estimates the probability of each fault. The results are displayed by a Graphical User Interface, which also allows the user to see data related to a specific fault. A prototype has been field-tested and has successfully detected and diagnosed a variety of faults.

The ability of the expert system to analyze circulation system problems is dependent on having high quality inflow and outflow measurements. Sandia National Laboratories has developed a Rolling Float Meter (RFM) to measure outflow and is testing commercially available ultrasonic inflow meters. The RFM has proven rig worthy and is ready for commercialization. Most recently it has been tested by Epoch Wellsite Services on a relief well in California where it has successfully detected kicks that were not observable by standard outflow measuring devices.

[0001] This invention relates generally to the field of measuring the volumetric flow rate of a fluid. More particularly, the invention relates to a method and system for measuring the volumetric flow rate of a fluid in a drilling rig return line.

[0003] A kick can be defined as a well control problem in which the pressure found within the drilled formation is greater than the mud or fluid hydrostatic pressure acting on the borehole or face of the formation. This formation pressure causes fluids to flow from the formation into the well bore. In almost all drilling operations, the operator attempts to maintain a hydrostatic pressure greater than the formation pressure and thus prevent kicks. On occasion, however, and for various reasons, the formation pressure exceeds the mud pressure and a kick will occur. Kicks have become even more common due to the present trend of increasing drilling rates by using lighter drilling mud.

[0004] Another problem encountered when drilling a well is drilling fluid loss into the formation. This problem, known by the shorthand term, "Lost Circulation", occurs where the drilling fluid is flowing into a subterranean formation through which the borehole passes. Such condition should be detected quickly by a driller to prevent damage to such a formation and excessive loss of the drilling fluid.

[0005] A number of kick or lost circulation "indicators" can be observed at the surface before a kick has had time to result in a dangerous blowout or excessive time has elapsed since the beginning of lost circulation. Three of these are:

[0006] FLOW RATE CHANGE - An increase in the flow-out or flow rate leaving the well while pumping at a constant rate is one of the primary kick indicators. The increased flow rate is interpreted to mean that the formation is forcing formation fluids into the well bore. A decrease in the flow rate exiting from the well while pumping at a constant rate is an indicator of lost circulation.

[0007] FLOWING WELL WITH PUMPS OFF - When the rig pumps are not moving the mud, a continued flow-out from the well indicates that a kick is in progress. An exception to this indicator is when the mud in the drill pipe is considerably heavier than that in the annulus, as in the case of a slug.

[0008] PIT VOLUME CHANGE - If the volume of fluid in the pits is not changed as a result of surface controlled actions, an increase in pit volume indicates that a kick is occurring. The fluids entering the well bore as a result of the kick displace an equal volume of mud at the flow line and result in a pit gain. A decrease in pit volume under these conditions indicates lost circulation.

[0009] Two of the kick early warning signs described above require measurement of an increase in flow rate from the fluid return line, while the other requires measurement of an increase in pit volume. These indicators are difficult to interpret when drilling from a floating drilling vessel because of the heaving and rolling of the drilling vessel in response to wind and waves. Floating drilling vessel heaving and rolling creates fluid return line flow rate changes.

[0010] It has been found that the time elapsed between the beginning of a kick deep in the well and its detection at the surface by pit level monitoring is too long to provide sufficient time to bring the well under control such as by adding weight to the drilling fluid.

[0011] Studies have shown that accurate differential flow measurements, of the order of twenty-five gallons per minute (25 GPM) provides the earliest possible surface detection of kicks and/or lost circulation. Such high absolute accuracy under widely varying conditions for both flow-in and flow-out systems, however, is difficult to obtain with the systems of the prior art.

[0012] Presently, flow-in measurement is based on the number of strokes per minute of triplex mud pumps (see Fig. 1). The flow race obtained from the pump strokes is then corrected by a volumetric pump efficiency. This pump efficiency can fluctuate between 80% to 95% accounting for inaccuracies of plus or minus seven and one half percent in the flow-in measurement.

[0013] The prior flow-out measurement has usually included a "paddle" system installed in the rig return line. The paddle is a hybrid flow meter based on level and target (force) measurements. The prior art paddle has an uncalibrated accuracy of around forty percent. With calibration on the rig site, the "absolute" flow-out measurement is still only accurate to ten or fifteen percent due to the basic non-linearity of the device, and due to very poor zero stability of the device. Poor zero stability requires frequent recalibration.

[0014] Using the pump strokes and the paddle measurement for flow-in and flow-out respectively, the best accuracy for the differential flow over the entire fluid flow range cannot be much better than about twenty-five percent, or three hundred (GPM) in twelve hundred GPM. This is more than ten times the required accuracy, rendering prior methods of differential flow rate measurement inadequate for desired kick detection.

[0015] Electromagnetic flow meters have also been used but have drawbacks. They do not work in oil based muds (conductivity too low). They require complete modification of the return line. In offshore rigs where modification of the return line is difficult and space is limited, there is usually no way to install them. They require expensive maintenance to sustain their accuracy.

[0016] Other industries have developed flow measuring systems suitable for use in waste water monitoring systems where sewer outflows must be monitored for pollution control purposes. These systems obtain flow measurements based on the velocity of the fluid in a channel and the area of the channel occupied by the flowing liquid. Ultrasonic level detectors and Doppler type velocity detection units have been used for these applications.

[0017] U.S. Patent No. 4,217,777 to Newman issued Aug. 19, 1980 discloses such a system and is incorporated herein for essential material and for all other purposes. Also U.S. Patent No. 4,202,211 to Perry issued May 13, 1980 discloses a similar system and is incorporated herein for essential material and for all other purposes.

[0018] Ultrasonic level detection systems are known in the art. Such systems are described in U.S. Patent No. 4,024,766 to Perry issued May 24, 1977, U.S. Patent No. 4,145,914 to Newman issued Mar. 27, 1979, and U.S. Patent No. 4,228,530 to Bergey issued Oct. 14,1980 all of which are incorporated herein for all purposes.

[0019] Further, U.S. Patent No. 4,754,641 to Orban et al., while providing improved results relative to the other methods for measuring fluid flow in return lines, still suffers from inaccuracies due to the requirement of a velocity probe which is inherently inaccurate in measuring mud flow in a drilling rig return line due to the wide range of elements in the mud. Thus, even with this advance, the art does not provide a method for sufficiently accurately determining a volumetric fluid flow rate such that a kick or lost circulation determination can be made in real time on a drilling rig.

[0020] It is therefore an object of the invention to provide an improved method and system for the measurement of volumetric fluid flow rate which is significantly more accurate than prior art methods and provides the measurements in real time while drilling.

[0021] It is another object of the invention to provide an improved fluid flow rate measuring system which obtains volumetric flow measurements without directly sensing the velocity of the fluid in the conduit.

[0022] It is a further object of the invention to provide an improved system and method for use in a return line of a drilling rig for quickly and accurately detecting a kick or lost circulation in the well bore.

[0023] It is even another object of the invention to provide a volumetric flow measuring system for accurately measuring flow rate of a fluid in supercritical flow conditions.

[0024] In accord with the objects of the invention, improved methods and systems are disclosed for use in a return line system of a drilling rig to aid in accurately determining a volumetric flow rate of mud in the return line without the aid of a direct velocity measurement means. The system invention broadly comprises: a non-intrusive level sensor located in or in proximity to the return line for sensing the height or level of the mud flowing in the return line and providing a signal indicative thereof; and a processor responsive to the level sensor signals for determining, in conjunction with knowledge of the return line configuration and mud parameters, the flow-out rate of the mud. Where the level sensor is acoustic, the system also includes a multiple of correction sensors for determining the temperature gradient in the return line and for investigating the presence of gas in the return line, and for providing signals indicative thereof to the processor which is responsive thereto. A more complete system also includes calibration means for calibrating the flow-out rate with the flow-in rate, and means responsive to the calibration means for determining an undesirable condition such as a kick or fluid loss. Where the system is to be used on a rig which is subject to movement (e.g. a floating rig), angle and position sensors are also employed.

[0025] In accord with other objects of the invention, the level sensor is installed in a chimney which extends from the flow line and which is in close enough proximity to the bell nipple (e.g. less than 10 feet away) such that the mud level is high and the friction between the mud which is in supercritical flow and the flow line is kept small. Where the level sensor utilized is an ultrasonic pulse echo transceiver, the correction sensors include a plurality of temperature sensors at different height locations (e.g. near the mud, at the junction of the return line and a chimney in which the transceiver is mounted, and near the transceiver), to provide information regarding the temperature gradient in the return line, as well as a calibration target which acts to sense a change in sound velocity due to the presence of gas in the return line. Data from the temperature sensors and calibration target help provide a determination of the speed of sound in the air (or air/gas) above the mud such that the echo time measured by the ultrasonic transceiver can be properly correlated to a distance between the transceiver and the mud surface. By knowing the shape and size of the return line, the slope of the return line, the height of the fluid in the return line, and a mud parameter such as the viscosity/density ratio, an accurate flow-out determination can be made without the use of a direct velocity sensor. Where the slope of the return line is changing (as determined by the angle sensor) due to movement of the rig, the flow-out results can be corrected to compensate for the motion. The flow-out determinations are calibrated against the flow-in measurements which are made by detecting mud pump strokes (the positive displacement per pump stroke being known).

[0026] Additional objects and advantages of the invention will become apparent to those skilled in the art upon reference to the detailed description taken in conjunction with the provided drawings.

[0027] FIG. 1 is a schematic view of a drilling fluid or "mud" circulation system for a floating or fixed drilling rig where a flow measuring system embodying the invention may be used;

[0028] FIG. 2a is a cross-sectional view of a return line system of the invention illustrating the fitting of an ultrasonic sensor system into an opening in the return line and schematically illustrating connection of the sensor system to a computer and associated instrumentation;

[0035] FIGS. 7a and 7b are logs of the flow-in of mud-displacing cement into a well-bore as measured from a cement truck, and the volumetric flow-out therefrom as measured by the system of the invention, respectively.

[0037] Referring to Fig. 1, a floating or fixed drilling rig mud circulation system is schematically illustrated, and it will be appreciated that the invention may be used with a bottom supported offshore drilling rig or a land drilling rig, as well as with a floating rig. As discussed above, flow rate into the well may be derived by counting the strokes per minute of mud pumps 16 or by direct measurement with a flow meter. After the "mud" or drilling fluid travels down the drill string 18, it moves up the annulus 20 between the casing 22 and the drill string 18 to the bell nipple 24. A return line 26 communicates with the bell nipple 24, as best shown in Figs. 1 and 2a, to return the mud to the mud pits 28. The flow-out measuring sensor system S according to the invention is disposed in the return line 26 in relative close proximity to the bell nipple 24; preferably within ten feet thereof.

[0038] The sensor system S in cooperation with a computer 14, which by way of example only includes a disk memory 28, a RAM memory 30, a CPU 32, and a ROM memory 34 (see Fig. 2a), is provided to accurately measure in real time the flow Q through return line 26. The volumetric flow Q is simply the product of the cross-sectional area A of fluid flowing at a given location in the line and the average velocity of the fluid moving at that location. However, because a determination of velocity is not made with a velocity probe, as most velocity probes are either intrusive or cannot handle the wide range of mud rheology, cuttings, gas, etc., the determination is made in the following manner,

[0039] In a simple return line geometry such as that seen in Fig. 2a, the velocity of mud in the annulus 20 is typically between one-half and one ft/sec, whereas the velocity of the mud in the return line 26 is typically between five and ten ft/sec. The acceleration of the mud is due to gravity and the slope of the return line, with the slope being great enough (e.g. typically greater than .5 degrees) to overcome the retarding effects of friction between the fluid and the pipe wall. In fact, most return lines have a slope of between two and twenty degrees. Under these conditions, a "critical flow" is established in the bell nipple, with the mud having a depth Hc and velocity Vc as seen in Fig. 2b. As the flow accelerates down the return line, the mud is in supercritical flow, and the velocity increases and the mud depth decreases, as is seen in Fig. 2b. This condition continues until the friction loss increases enough to offset the gravitational forces causing the acceleration. However, most return lines are too short for this equilibrium to be reached.

[0040] The inventors have found that in a typical return line with mud in supercritical flow, an increase of flow typically translates into an increase in mud depth (level) according to a substantially linear relationship for flow rates above about two hundred gallons per minute (200 GPM). Put another way, and as seen in Fig. 4 which shows the relationship between flow rate, mud level, and velocity in a return line, mud velocity is almost constant above 200 GPM, and an increase in flow rate directly translates into an increase in mud depth. Thus, for any given return line configuration with typical flow rates, the measured height of the mud in the return line may be calibrated to a flow race with reasonable accuracy. By way of example, the measurements indicated in Figure 4, which relate level to flow, were made three feet from the bell nipple in a return line of twelve inch diameter and five degree slope, and a mud with a density of twelve PPG and viscosity of ten cp. For return lines of different diameter or slope, mud of a different viscosity/density ratio, and a measurement location of different distance from the bell nipple, the curves of Figure 4 would assume different values.

[0041] As stated above, a review of Fig. 4 indicates that the GPM flow-out can be determined directly from the mud level without a determination of velocity. Thus, for the stated return line geometry and mud properties, a measured mud depth (or level) of 2.4 inches is equivalent to a mud flow-out of 300 GPM, while a measured mud depth of 4.8 inches is equivalent to a mud flow-out of 900 GPM. With a slope of 2.4"/600 GPM, in order to achieve a desired accuracy of the order of 25 GPM, a measurement of mud depth must be accurate to at least 0.1 inch.

[0042] Given the fact that flow rate can be measured directly from mud level if the return line geometry and mud makeup are known, means and methods for making the level measurement must be set forth. One preferred means for accomplishing the mud level measurement is seen in Fig. 2a where a sensor system mounts on the return line 26 and sits in an eight inch diameter hole cut into the return line. Sensor system S includes a chimney section 40 of six inch diameter in which the mud level sensor is mounted, and an inflatable seal 41 which fits around the chimney and inside pipe flanges 43 welded to the cut in the return line 26. For mechanical stability and alignment purposes, a support 45 is provided around chimney 40. Turnbuckles 46 connect the support to clamp 48 which grips the return line 26. This permits alignment of the sensor system S relative to the return line such that the sonic beam produced by a transceiver 50 (as discussed below) is substantially normal to the mud. In this arrangement, sonic beam reflections can be received and sensed by the transceiver 50.

[0043] Sensor system S may be provided in any top entry opening in return line 26, although it is preferable that the system be employed within ten feet of the bell nipple. Sensor system S achieves access to the interior of return line 26 without the need for line 26 being disconnected from an existing rig hookup to bell nipple 24.

[0044] The sensor system S includes a mud depth or level sensor for measuring the distance between the sensor and the mud surface. The sensor preferably includes an ultrasonic transmitter-receiver ("transceiver") 50 which both transmits and detects ultrasonic waves. Because a transceiver cannot detect a wave immediately after it has transmitted one (i.e. the transceiver has "dead time"), the transceiver 50 is preferably mounted in a housing or chimney 40 which removes the transceiver from the mud surface and causes the return signal to be received after the dead time. Mounting the transceiver 50 in the chimney 40 also protects it from mud splashing. Even so, a water sprayer 79 which receives water from water source 58 is preferably provided to clean the transceiver 50 and the other sensors located in or about chimney 40.

[0045] To convert the echo return time into a distance requires knowledge of the velocity of sound in the medium through which the sound pulse travels, as distance is equal to the product of time and velocity. Parameters affecting the velocity of sound include the temperature and the composition of the medium through which the sound travels. As the composition and the temperature of the "air" above the mud in the return line can change over time, additional sensors are utilized to monitor these parameters. For temperature, preferably three sensors 29a, 29b, and 29c are utilized to measure the heat gradient present between the mud surface and the transceiver 50. Thus, the first sensor 29a is placed on adjustable pole 52 and located near the mud. A second sensor 29b is located at the junction of the return line 26 and the chimney 40, while the third sensor 29c is located close to the transceiver 50. The sensors used are preferably AD590 solid state devices available from Analog Devices which produce exactly 1 microamp per degree Kelvin and are accurate enough to be calibrated electrically.

[0046] A manner for compensating the determined echo time for temperature gradients and changes therein is found in U.S. Patent #4,754,641 and will not be further discussed herein. It should suffice to note that all temperature determinations are fed via signal conditioners 57 and A/D converter 59 to the computer or processor means 14 which utilizes the temperature and echo time information in providing a distance, and hence a return line mud height determination. It should also be noted that similar techniques can be used with fewer or greater numbers of temperature sensors to provide more or less accuracy, and it is not the intent hereof to be limited to exactly three temperature sensors.

[0047] In taking into account the composition of the medium through which the sound is travelling, it is not necessary to determine the actual composition. Rather, it is only necessary to have a reference from which relative changes can be calculated. In particular, the provision of a reference target 51 on adjustable pole 52 at a known distance from the transceiver 50 permits a determination of the time it takes for the ultrasonic waves to travel a fixed distance at the temperatures provided by the temperature sensors 29a and 29b in whatever medium is present (e.g. air, gas, or air/gas mixture). Thus, by first sensing the reference echo time from transceiver 50 to target 51 and back to transceiver 50, and then sensing the echo time from transceiver 50 to the mud surface and back to the transceiver 50, the reference echo time can be used in conjunction with the temperature information to determine the distance between the transceiver 50 and the mud surface in an extremely accurate manner.

where Vs is the sonic velocity, Ta, Tm, and Tt are respectively the absolute temperature, the mean temperature of the mud path and the mean temperature of the target path, K is the effect of the gas composition on the sonic velocity, Lm is the distance from the transceiver 50 to the mud surface in the return line, Lt is the distance from the transceiver to the target, and △Tm and △Tt are the mud echo and target echo times respectively.

which indicates that with the reference target, the distance to the mud surface is derived from measurable (△Tm, △Tt, Tm, Tt) or known (Lt) parameters and is not dependent on the composition effect K of the gas. It should be noted that Tm and Tt as provided represent the mean of the gradient over distances Lm and Lt respectively, and that more complex representations more specifically accounting for temperature gradients would suggest themselves to those skilled in the arts.

[0050] Although knowing the actual composition of the medium through which the sound pulses travel is not necessary in practicing the present invention, it has been found that the method and apparatus of the present invention can be used effectively to detect the presence of methane gas (CH₄) in the mud return line and to calculate an approximate volumetric fraction of methane. Specifically, since the speed of sound in "air" (nitrogen/oxygen mixture) is approximately 332 m/sec at 0°C while the speed of sound in methane is approximately 430 m/sec., a large change in the speed of sound measurement derived from the target signal may properly be interpreted to indicate the introduction of methane into the return line since methane is by far the most abundant gas encountered during a drilling operation.

[0051] In equation (1) above, K is equal to the ratio of specific heats (Cp/Cv) or γ, times the universal gas constant R, divided by the molecular weight MW. For air, γ is approximately 1.4 and MW is approximately 29 while for methane, γ is approximately 1.3 and MW is 16. For a mixture of gases containing X volume fraction of methane and (1-X) volume fraction of air,

[0052] In operation, a measurement of the speed of sound known or assumed to be pure "air" is taken and stored in one of the memories of computer 14 as a reference. Then, as further measurements are taken in operation mode, the measured speed of sound is compared to the reference and X is solved for in equation (4b) above either on command or automatically, and displayed on recorder 60.

[0053] In order to obtain both target and mud echo information, the target 51 should be located in the return line such that the echoes received from the target do not interfere with the echoes received from the mud surface. In return lines of different diameters, the location might need to be different to avoid the second echo of the target. The placement of the target 51 on the adjustable pole 52 permits such adjustment and ensures that the target can be located at a location of more than half the distance from the transceiver to the mud surface. Alternatively, if desired, the sensing of the target and mud echoes can be time multiplexed. Also, if desired, automatic adjustment of transceiver transmission frequency in order to obtain the largest echo signals available can be provided by having microprocessor 61 which controls sensor 50 conduct a search for the best frequency.

[0054] Once the distance between the transceiver 50 and the mud surface (and the distance between the transceiver and the pipe or sediment surface of an "empty" pipe which may be determined by using the sensor system or through a knowledge of the pipe diameter etc.) is determined by the computer 14, a direct determination of flow rate may be obtained from a look-up table representing the mud height to flow rate relationship for the particular return line and mud parameters. Such a look-up table is generated either by accumulating experimental data or according to the following theoretical analysis.

[0055] Flow rate (Q) may be defined as the mathematical product of fluid velocity (V) and the cross-sectional flow area of the mud (A); i.e. Q = VA. The cross-sectional flow area of the mud is simply a function of the mud level and the geometry of return line. Complicating factors such as the presence of sediment 87 (as seen in Fig. 3) may also be taken into account, such as discussed in U.S. Patent #4,754,641. The sediment level may be determined in the absence of flowing mud. It is assumed that the sediment is simply stationary material which is taking up some of the cross-sectional area of the return line. While the resulting geometry of the fluid flow is not a simple one, it is nevertheless within the knowledge of those skilled in the art to solve for the cross-sectional flow area.

[0056] A determination of average fluid velocity (V) is not as straight-forward as the determination of cross-sectional area, particularly because the determination is not a direct one (i.e. no velocity sensors are used). With a simple return line geometry and no friction, the velocity of the mud would be a direct result of the vertical fall of the liquid surface; the energy of which would be converted from potential to kinetic energy. In particular, such a system could be described according to the following relationships:

where relationship (5) is the basic energy equation which equates the total energy E to the potential energy related to height h, and the kinetic energy related to velocity V and gravity g, and relationship (6) is the basic continuity equation which equates volumetric flow rate Q with area A and velocity V. From (5) and (6) follows:

where dA/dh is the surface width of the fluid = b. In critical flow, where the energy E is at a minimum for a given flow rate Q, dE/dh = 0, and the area A is the critical area Ac. Thus, relationship (8) simplifies to

where Vc is the critical velocity, g is the acceleration due to gravity, Ac is the critical cross-sectional area of the mud in the return line close to the junction of the return line with the bell nipple (i.e. the critical area), and b is the surface width of the fluid. For a given mud flow rate Q and geometry which relates Ac and b, the critical velocity Vc, the critical area Ac, and the critical depth hc become known. As a result, tables can be generated which relate various flow rates Q and resulting values of Vc, Ac and hc.

[0058] While relationships (5) - (10) assume the absence of friction up to the critical point, it will be appreciated that friction does play a role in the velocity of the mud in the return line, and accounting for friction is necessary. The following conservation of energy equation makes such an account:

where f is a friction factor, H is the height of the fluid surface at the location of the level sensor, L is the distance from the bell nipple to the level sensor, Z is equal to the product of L and the sine of the slope angle ϑ of the return line,(i.e. Z = L sin ϑ) and D is the hydraulic diameter which is equal to 4A/wetted perimeter. The slope angle ϑ of the return line is either predetermined, or is measured with an angle sensor 12. Angle sensor 12 is preferably a pendulum sensor, with the pendulum acting to change the resistance of a potentiometer. The pendulum sensor 12 is particularly important with respect to rigs which are subject to movement as will be discussed hereinafter.

[0059] With the provided continuity (6) and critical flow (10) equations and with the provided energy equation (11), the velocity V at the location of the level sensor can be determined as long as the friction factor f can be found. The friction factor f can be determined according to the Reynold"s number Re pursuant to well known equations. The Reynold"s number, in turn, is dependent on the velocity, hydraulic diameter, density and viscosity of the flowing fluid according to Re = VDρ/µ. The density and viscosity are typically monitored on the job site and are available. Account, however, should be taken if the viscosity or density changes significantly over time. By keeping the location of the level sensor near the bell nipple, a crude estimate of friction is sufficient, as the inventors have determined that within approximately ten feet of the bell nipple, the friction losses of the returning fluid are small and that a crude estimate yields reasonable results. In fact, Re and f are considered to be constant and equal to their critical values throughout the length of the return line (although the critical values may change over time if the flow or mud parameters change). This is a reasonable approximation for as the velocity increases, the depth decreases, tending to keep Re constant. A typical friction loss of about twenty percent yields a velocity reduction of about ten percent, and an error of ten percent in analyzing the friction losses would result in a tolerable change of velocity of only one percent. Regardless of how the friction loss determination is originally estimated, calibration of flow-out corrects for any inaccuracies as is hereinafter described. In sum, then, equations (5) - (11) are solved at the outset of a job for the fixed values of the pipe size D, distance between the sensor system S and the bell nipple L, return line slope ϑ, mud viscosity µ, and mud density ρ, to establish the height (h) to flow (Q) look-up table appropriate for the job.

[0060] Turning to Figure 5, the method for determining the flow rate in the return line, which utilizes calibration is seen. At 100 the echo times for the reference target and for the mud surface are measured, along with the temperature gradient in the return line and chimney as measured by the temperature sensors. Also, as will be discussed hereinafter, the flow into the well is measured. In a preferred embodiment, the angle of the return line, and the density and viscosity of the mud are further measured. At 104, the echo times and temperature gradient are used to find the fluid flow height H. Also, at 104 the mud viscosity and density are used in conjunction with parameters stored at 200 such as the return line geometry (e.g. diameter), the horizontal distance from the bell nipple to the measurement location (L), the return line slope (ϑ), the gravitational constant (g), and any other relevant parameters which are constant for the given system, to provide a determination of the velocity of the mud in the return line at the measurement location in accord with equations (4) through (11) above. From the fluid flow height, the cross-sectional area of the mud in the return line at the measurement location is determined at 104. If available, additional information such as sediment level (box 107) may be provided to the processor which determines at 104 the cross-sectional area of the mud.

[0061] At 110, a determination of the flow-out (Q) of the mud from the wellbore is obtained from a transform (i.e. look-up table such as is represented by Fig. 4 for the provided return line and mud parameters) which relates the flow height to flow-out. Alternatively, the flow-out (Q) is found as the product of the determined cross-sectional area (A) of the mud and the mud velocity (V) at the measurement location. The flow-out (Q) determination at 110, however, is preferably viewed as a theoretical flow-out, such that through a calibration, an absolute flow-out determination (which is only absolute relative to the accuracy of the flow-in pump measurements) can be made. Thus, at start-up a single or multi-point calibration lasting only several minutes is preferably performed, and provides a calibration between the actual flow-out and the "estimated" theoretical flow out. The calibration accounts for non-linearity, errors in estimating friction, and other systematic errors which may be present such as changes in geometry, mud properties, sensor calibration, etc. Then, during drilling, when the theor