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WO2008147953A1 - Estimation du rapport gaz/huile à partir d'autres propriétés physiques - Google Patents

Estimation du rapport gaz/huile à partir d'autres propriétés physiques Download PDF

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Publication number
WO2008147953A1
WO2008147953A1 PCT/US2008/064647 US2008064647W WO2008147953A1 WO 2008147953 A1 WO2008147953 A1 WO 2008147953A1 US 2008064647 W US2008064647 W US 2008064647W WO 2008147953 A1 WO2008147953 A1 WO 2008147953A1
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WO
WIPO (PCT)
Prior art keywords
desired property
values
downhole
fluid
sound speed
Prior art date
Application number
PCT/US2008/064647
Other languages
English (en)
Inventor
Rocco Difoggio
Original Assignee
Baker Hughes Incorporated
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
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First worldwide family litigation filed litigation Critical https://patents.darts-ip.com/?family=40075505&utm_source=google_patent&utm_medium=platform_link&utm_campaign=public_patent_search&patent=WO2008147953(A1) "Global patent litigation dataset” by Darts-ip is licensed under a Creative Commons Attribution 4.0 International License.
Application filed by Baker Hughes Incorporated filed Critical Baker Hughes Incorporated
Priority to BRPI0811933A priority Critical patent/BRPI0811933B1/pt
Priority to GB0919617A priority patent/GB2463393B/en
Publication of WO2008147953A1 publication Critical patent/WO2008147953A1/fr
Priority to NO20093427A priority patent/NO342446B1/no

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Classifications

    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
    • E21B49/08—Obtaining fluid samples or testing fluids, in boreholes or wells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/02—Analysing fluids
    • G01N29/024—Analysing fluids by measuring propagation velocity or propagation time of acoustic waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
    • G01V1/44—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging using generators and receivers in the same well
    • G01V1/48—Processing data
    • G01V1/50—Analysing data

Definitions

  • the present invention relates generally to hydrocarbon exploration and production, and more particularly relates to a method and system for characterizing a desired property of a fluid downhole.
  • GOR gas-oil ratio
  • Brine modulus, density, and viscosities increase with increasing salt content and pressure. Brine is peculiar because the modulus reaches a maximum at a temperature from 40 to 8O 0 C. Far less gas can be absorbed by brines than by light oils. As a result, gas in solution in oils can drive their modulus so far below that of brines that seismic reflection "bright spots" may develop from the interface between the oil-saturated and brine-saturated rocks.
  • Batzle and Wang "Seismic Properties of Fluids," Geophysics, v.57, no. 11 , pp. 1396-1408 (November, 1992) (hereinafter, "Batzle and Wang,” which is hereby incorporated by reference herein in its entirety for all purposes).
  • the teachings of Batzle and Wang, commonly and collectively referred to as the Batzle and Wang relations, are widely known to and used by those of ordinary skill in the art.
  • the Batzle and Wang relations comprise a series of separate correlation equations for sound speed and for GOR in terms of other parameters but it does not provide any equation for GOR in terms of sound speed, live oil density, pressure, and temperature.
  • one Batzle and Wang correlation equation relates gas-containing ("live") oil density to GOR, gas density, and formation volume factor.
  • Another Batzle and Wang correlation equation relates formation volume factor to GOR, gas density, stock-tank (“dead”) oil density, and temperature.
  • the sound speed of live oil can be estimated by substituting for dead-oil density a pseudo-density based on expansion caused by gas intake into the equation for sound speed of dead oil.
  • the sound speed of live oil at borehole temperatures and pressures is generally between 1100 and 1700 meters per second.
  • Still another Batzle and Wang correlation equation relates the pseudo-density to formation volume factor, GOR, and stock-tank oil density. [0006]
  • the present invention relates to characterizing properties of fluids downhole.
  • the characterization is performed by taking a signal representing a measured property, or properties, of the downhole fluids and analyzing the desired property, or properties, and processing that signal using a correlation equation expressing the desired property in terms of the measured property, or properties, to produce an output signal representing the desired proeprty.
  • he correlation equation is derived through a chemometric analysis of a training data set using a series of algebraically-unsolvable, simultaneous, crude-oil correlation equations, and in particular, to the assessment of gas-oil ratios, gas brine ratios, and other properties of fluids in hydrocarbon formations not typically measured downhole.
  • chemometrics is the application of mathematical, statistical, graphical, and/or symbolic methods to chemical data to maximize the amount of information that can be derived therefrom. See, e.g., MA Sharaf, D. L. lllman and B. R.
  • a method comprises: receiving at least one input signal representing sound speed of a fluid downhole; processing the input signal using the correlation equation expressing the desired property in terms of at least sound speed wherein an output signal representing the desired property is produced; and outputting the output signal.
  • certain correlation equations relating to geophysical properties of a formation are first used to create a synthetic training set. That is, a sound speed and GOR pair is calculated from a set of randomly-generated stock-tank oil density, pressure, temperature, formation volume factor, and gas density values ranging between expected minimum and maximum values for each property.
  • the properties used in generating the synthetic training set include those that cannot be measured downhole using currently available techniques and/or instrumentation. For example, to measure stock-tank oil density would require, first, separating gas from the crude oil and then measuring the resulting liquid density at 1 atmosphere and 60° Fahrenheit, which cannot be done in the high-temperature, high-pressure, downhole environment.
  • the input values do not have to be generated randomly; in many examples, they may be generated by any of the standard methods of experimental design (e.g. factorial design, Plackett-Burman design, or Box-Behnken design (http://www.itl.nist.gov/div898/handbook/pri/section3/pri3.htm)).
  • the purpose of any design is to make sure that every neighborhood of input value space is included so that each combination of input values, within the range of each property, is represented.
  • a regression method is used to model the GOR relative to properties that are commonly measurable downhole, such as sound speed, temperature, pressure, live oil density, and so on, to create a correlation equation for GOR based on data that was generated synthetically from the original correlation equations.
  • the regression is performed through statistical and/or neural network methods.
  • Figure 1 is a flow diagram illustrating a method for characterizing a desired property of a fluid downhole by receiving a signal representing measuring sound speed of a fluid downhole and analyzing the desired property using a correlation equation expressing the desired property in terms of the measured properties in accordance with one embodiment of the invention
  • Figure 2 is a flow diagram illustrating a chemometric methodology for deriving a correlation equation expressing a desired property in terms of a set of measured properties in accordance with one embodiment of the invention
  • Figure 3 illustrates the generation of a table of output data from input data.
  • the columns of this table, along with various functions of the columns of this table e.g., pressure squared, pressure cubed, reciprocal pressure, pressure times temperature, etc.
  • Figures 4 and 5 illustrate the fit of the chemometric models calculated from sound speed, density, temperature, and pressure. Those of ordinary skill will understand that the better that the chemometric model fits the simultaneous Batzle equations from which the synthetic data were derived, the closer that the points will be to the equal-value (perfect prediction) line.
  • Figure 6 portrays a sampling sonde disposed in a cut-away of a wellbore.
  • Figure 7 illustrates a cut-away view of a sampling system.
  • Figure 8 represents plots containing raw data and processed data.
  • FIG. 1 there is shown a flow diagram illustrating a method for characterizing a desired property of a fluid downhole in accordance with one example of the invention.
  • the process begins with step 11 , receiving an input signal 13 representing sound speed of a fluid downhole.
  • the input signal is processed 17 using a correlation equation 15 expressing the desired property in terms of at least the sound speed.
  • step 12 involves selection of a first plurality of input parameters whose values can be used to calculate the values of a second plurality of parameters.
  • the input parameters include temperature (T), pressure (P), stock tank oil density (p 0 ), and gas gravity (G).
  • step 12 involves generating a plurality of (possibly random) combinations of values of these input variables.
  • the random value is taken from a predetermined range within which that parameter can realistically and foreseeably be expected to lie in an actual subsurface environment.
  • the random values of temperature may be temperatures within the range 100° ⁇ T ⁇ 400° F.
  • Pressure may be assumed to range from 0 ⁇ P ⁇ 30,000 PSI.
  • G 0.5556 for the gas gravity parameter, which represents a reasonable assumption that the gas is pure methane, which has a density approximately one-half the density of air. This value for G is reasonable because, by weight percent, natural gas averages about 86% methane and by mole percent, natural gas averages about 93% methane (Gas Research Institute Report # 82/0037). One could, of course, use slightly larger values for G to improve the model for heavier natural gases that contain more ethane, propane, butane, and so on. [0029] Batzle and Wang proposes an equation for the saturation gas oil ratio RQ as a function of the foregoing four variables T, P, G, and po, as follows:
  • the number of rows in the table of Figure 3 corresponds to the number of sets of (possibly but not necessarily random) input values (the number of "samples" or "cases") included in the training data set.
  • samples the number of samples included in the training data set.
  • one embodiment next calls for performing a chemometric analysis of a desired property (i.e., a desired column from the table of Figure 3) against other properties represented in Figure 3.
  • a desired property i.e., a desired column from the table of Figure 3
  • the desired property for which a regression is performed is preferably a property that is not readily measurable downhole
  • the properties against which the regression is performed are preferably those that are readily measurable downhole and/or approximated by other means.
  • Performing a regression as called for in step 16 can be performed by any of numerous means and techniques well known to persons of ordinary skill in the art.
  • the regression is performed using STATISTICATM, an analytics software application commercially available from StatSoft ® , Inc., Tulsa, Oklahoma.
  • STATISTICATM is an analytical tool widely known and used by persons of ordinary skill in the art, and although this is a tool presently known to be suitable for the purposes of the present invention, it is to be understood that other tools or techniques, presently known or yet to be developed, may be utilized in the practice of the invention with equal efficacy.
  • the chemometric analysis can be performed by a neural network analysis.
  • FIG 4 there is shown a plot graphically summarizing a regression process as performed in accordance with the presently disclosed embodiment.
  • the plot of Figure 4 is an example in which dependent variable API gravity (effectively an "inverse density") is regressed against live oil density p', pressure P, and temperature (T).
  • the substantially linear plot 18 represents the API values predicted using the Batzle and Wang equations, while the individual data points 20 in Figure 4 represent API values computed using the regression model generated in accordance with the presently disclosed embodiment.
  • FIG. 5 there is shown a plot graphically summarizing another regression process as performed in accordance with an example embodiment.
  • the dependent variable is the gas-oil ratio (GOR) is regressed against sound speed with 10702 samples.
  • GOR gas-oil ratio
  • a desired property of a fluid downhole is characterized through the use of a correlation equation expresssing the desired property in terms of fluid properties measured downhole.
  • the measured properties of the downhole fluid include sound speed measured downhole by generating an external acoustic signal, measuring the signal travel time through the fluid, and determining the fluid sound speed based on the measured travel time of the acoustic signal over a known distance through the fluid.
  • a method for determining sound speed of a downhole fluid is described in more detail in United States Patent Application Serial Nos. 11/194365 by DiFoggio and Yao and 11/638893 by DiFoggio, Bergren, and Han, incorporated herein by reference in its entirety for all purposes.
  • the steps of this example method include measuring a set of fluid properties downhole and inputting the set of measured properties into a correlation equation expressing the desired property in terms of the measured fluid properties.
  • the correlation equation is derived as explained in various examples herein.
  • the sampling system 22 of FIG. 5 comprises a vessel or container 20 in cooperation with a signal generator 21.
  • the outer surface of the container 20 can have a radial or rectangular configuration as well as the shape of a tube.
  • the vessel or container 20 can be comprised of a conduit or pipe.
  • the container 20 should be capable of retaining and storing the fluid 18 within its confines during analysis. Although shown as open at its top, the container 20 can also be sealed thereby fully encapsulating the fluid 18 therein.
  • the signal generator 21 can be attached to the outer or first wall 24 of the container 20 or maintained in place. As will be described herein below, for the purposes of reference, both the first and second walls (24, 26) shown adjacent to the signal generator 21 are shown as well as the third and fourth walls (28, 30) distal from the signal generator 21.
  • the signal generator 21 can be comprised of any device capable of producing a recordable acoustic signal that passes through the fluid. This includes traditional acoustic devices such as piezoelectric devices, however other acoustic transducers can also be used to accomplish this function. For example, an Electro-Magnetic Acoustic Transducer (EMAT) can insert ultrasonic waves into metal by electromagnetic coupling.
  • EMAT Electro-Magnetic Acoustic Transducer
  • a pulsed laser that strikes an object can generate acoustic waves at a frequency that depends on the laser pulse frequency;
  • the signal generator 21 can also be used as a receiver for receiving and recording reflections of the signals generated by the signal generator 21.
  • a flexural mechanical resonator useful with the device disclosed herein is described in detail in United States Patent No. 6,938,470, the disclosure of which is incorporated for reference herein in its entirety for all purposes.
  • the sampling system [0046] In one alternative of the present device, the sampling system
  • sampling system 22 is combined with the sonde 10 and in fluid communication with the sample port 14.
  • connate fluid from the formation 6 is collected by the sample port 14 and delivered to the container 20 for analysis of the fluid.
  • the sampling system 22 is preferably housed within the sonde 10 during deployment and operation of the sampling system 22. Combining the sampling system 22 with the sonde 10 provides the advantage of "real time” sampling and reduces the risk of allowing changes in either the pressure or the temperature of the fluid that could in turn affect the sampling results.
  • use of the sampling system 22 is not limited to the fluid collection apparatus of FIG. 1 , but can be used with any type of device or circuit used in collecting downhole connate fluid.
  • connate fluid is drawn into the sample port 14 of a downhole sonde 10.
  • the fluid is then introduced into the container 20 for subsequent analysis.
  • the signal generator 21 is then activated so that a signal 31 , such as one or more acoustic pulses, is generated.
  • a signal 31 such as one or more acoustic pulses
  • the generated signal 31 is illustrated as a series of curved lines emanating from the transducer 21.
  • the signal 31 passes through the first and second walls (24, 26) of the container 20, into the contained fluid 18, and onto the distal third and fourth walls (28, 30). A portion of the generated signal 31 (the reflected signal 33) reflects back to the direction of the signal generator 21.
  • the reflected signal 33 is illustrated for convenience as a series of curved lines directed towards the signal generator 21.
  • the signal generator 21 can operate as a transmitter and also as a signal receiver.
  • a separate transducer (not shown) could be included that operates solely as a signal receiver for receiving the reflected signals 33.
  • a short voltage spike can be applied to the transducer that typically lasts about 1-2 microseconds.
  • This spike causes the transducer to resonate at its resonant frequency, which is typically from about 5 MHz to about 10 MHz.
  • the transducer rings primarily at its resonant frequency, for about a microsecond.
  • An ever-decreasing portion of this microsecond-long pulse bounces back and forth between the tube wall that is bounded by surface 24 and surface 26, (which is in contact with the transducer 21 ) because a portion of the pulse is transmitted into the fluid upon each bounce off surface 26.
  • the transmitted portion of the pulse passes beyond surface 26, enters the fluid 18, reflects from the surface 28, and eventually returns to be detected by the transducer 21.
  • the acoustic transducer serves both as source and receiver.
  • a highspeed (40-70 MHz) analog-to-digital converter monitors the signal received by the transducer.
  • the signal generator 21 receives and records the reflected signal for subsequent analysis.
  • the recorded signal can either be immediately processed to determine fluid data, transmitted from the sonde 10 to a separate site for storage or data processing, or can be recorded within the sonde 10 for later analysis.
  • the sound speed (c) of the liquid is determined by dividing the travel time of the signal through the fluid 18 by the distance the signal traveled through the fluid. This can be accomplished by designating the letter "d" as the distance between surface 26 and 28.
  • variable 2t can be designated as the time difference between the arrival time of the first echo (corresponding to one round trip going from surface 24 to 26 and back again to 24) and the arrival time of the echo off surface 28 (corresponding to one round trip from 24, past 26, to 28, and eventually, back to 24). Therefore, 2t is amount of time it took sound to travel a round-trip distance, 2d, within the fluid from surface 26 to surface 28 and back to surface 26. The sound speed therefore is d/t.
  • the raw amplitude data from the signal generator 21 can be first processed by applying a digital bandpass filter to reject any frequencies that are not close to the acoustic source frequency. For example, for a 10 MHz acoustic source and a 40 MHz sampling frequency, one could apply a 9-11 MHz digital bandpass filter. Next, one can compute the square of the amplitude at each sampling time, which corresponds to the energy received at that time. Then, one can generate a cumulative sum of squares (CSS) of these amplitudes, which is the cumulative sum of energy received up until that time.
  • SCS cumulative sum of squares
  • the digital bandpass filtering and cumulative sum of squares have already smoothed the raw data and removed some noise.
  • the variable thresholding method serves to distinguish recorded signals emanating from the far wall of the vessel or container 20 from signals received that emanate from within the near wall (between surfaces 24 and 26) of the vessel or container 20.
  • FIG. 8 there is illustrated a plot having a raw data plot 32, a smooth data plot 34, and a variable threshold plot 38.
  • the portion of the raw data has been redacted (as well as the corresponding smoothed and threshold data) that corresponds to the ringing of the transducer immediately after it receives a high voltage spike.
  • This plot shows sampling of the signal amplitude at discrete intervals (digital data). To avoid aliasing, the sampling rate is several times the acoustic source frequency.
  • the square of the amplitude for each channel is computed. The amplitude for each channel is proportional to the acoustic intensity (energy) that was received at that channel's time.
  • the data smoothing is further accomplished by computing the first derivative with respect to time of the cumulative sum of squares using Savitzky-Golay (SG) coefficients, which helps create smoothed numerical derivatives.
  • SG Savitzky-Golay
  • Enhanced smoothing is accomplished by using Savitzky-Golay coefficients of lower order (such as square or cube) polynomials over a fairly large number of points (25 channels).
  • the first derivative of the cumulative sum of squares is the smoothed energy received versus time, which shows distinct acoustic energy pulses.
  • the resulting values produced by the Savitzky-Golay method are shown plotted in the smooth data plot 34 of FIG. 8.
  • the second derivative is taken of the cumulative sum of squares using Savitzky-Golay (SG) coefficients of a low order and a large number of points.
  • the local maxima (pulse energy peaks) of the first derivative curve can be used to indicate the time at which a particular pulse reflection is received by the receiving transducer 21. It should be pointed out that the second derivative crosses zero when the first derivative reaches either its local maxima or minima.
  • a pulse peak occurs between two channels whenever the second derivative changes from positive (in the left channel) to negative (in the right channel) with increasing time and the first derivative exceeds some variable threshold, which is described in detail later.
  • Subchannel time resolution can be achieved by interpolating so as to estimate the location between two channels where the second derivative crosses zero.
  • energy maxima can be distinguished from energy minima (both of which correspond to zeros of the second derivative of the CSS) based on the sign of the third derivative of the CSS.
  • the sound speed of the fluid within the vessel or container 20 is twice the wall thickness divided by the (round-trip) time between reverberation pulse peaks within the tube wall.
  • the wall sound speed may change with temperature or with pressure of the fluid inside the tube thus causing the wall's acoustic impedance to change.
  • the wall's acoustic impedance must be known to compute fluid density from fluid sound speed and the decay rate of within-wall pulse echo reverberations. Direct downhole measurement of the wall's sound speed can be made from the wall thickness and the time between within-wall pulse peak reverberations.
  • the wall speed is one parameter used to calculate the density of whatever fluid is in contact with the wall. Another factor in calculating fluid density is the wall density but changes in the wall's density with temperature and pressure are a much smaller effect that can usually be ignored or estimated from a table.
  • the smooth data plot 34 comprises reflected signals both from signal reverberations within the near wall (between the first and second wall 24 and 26) as well as a reflection from the far wall (third wall 28). These reflected signals are illustrated as curves 36 on the smooth data plot 34.
  • the acoustic signal reverberating within the near wall decays over time, this can be seen in the decreasing local maxima of the curves 36 of the smooth data plot 34 of FIG. 3.
  • the amplitude of the signal reflected from the far wall (third wall 28) will exceed the amplitude of the last observable within-wall reverberation.
  • the variable threshold method can be used to determine the time (channel number) at which the far wall reflection pulse reaches its peak energy.
  • the threshold keeps being lowered to the height of the last within-wall reverberation peak.
  • the first pulse peak whose amplitude increases from its predecessor is taken as the far wall reflection.
  • the variable pulse- peak-detection threshold function is generated using two passes.
  • the threshold value for each channel is the largest energy (first derivative of CSS) value that occurred in the previous M channels, where M is the number of channels between peaks of energy pulses reverberating within the wall.
  • This first pass for creating a variable threshold generates a staircase- like function (not shown) having horizontal steps joined by rises and falls that are not perfectly vertical.
  • a graphical representation of the second pass is shown comprising a series of steps 40 having horizontal steps 42 and vertical sections 44.
  • the vertical sections 44 are adjusted to be substantially vertical (i.e. have an infinite slope) while keeping the horizontal steps 42 substantially the same except for extending them left or right. This is accomplished by extending each horizontal step 42 leftward to the last channel of a higher step whenever a higher step 42 lies to its left.
  • the signal generator 21 can be positioned within the confines of the vessel or container 20, on its outer circumference, or even within the body of the container 20 (i.e. between the first and second walls 24 and 26 or between the third and fourth walls 28 and 30).
  • the accuracy of the disclosed method is dependent on the accuracy of the measurement of the set of measured properties. It is desirable for the measured properties to consist of properties for which highly accurate measurements are available downhole to reduce propagation of uncertainty in the characterization of the desired property. For example, the sound speed of live oil at borehole temperatures and pressures is generally between 1100 and 1700 m/sec. Therefore, it is desirable to have a sound speed measurement resolution of near 1 meter per second, which is less than 0.1 % of the typical sound speed value, to minimize uncertainty in the characterization of the desired fluid property.

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Abstract

L'invention concerne un procédé pour caractériser une propriété souhaitée d'un liquide en fond de trou comprenant la réception d'un signal d'entrée représentant la vitesse sonore d'un liquide en fond de trou, au traitement du signal d'entrée en utilisant une équation de corrélation exprimant la propriété souhaitée en termes d'au moins la vitesse sonore pour produire un signal de sortie représentant la propriété souhaitée et la fourniture en sortie du signal de sortie. L'équation de corrélation peut être dérivée d'une analyse chimiométrique d'un jeu de données d'apprentissage comprenant une pluralité de valeurs d'entrée et une pluralité de valeurs de sortie déduites des valeurs d'entrée. Dans au moins un exemple, la propriété souhaitée est un rapport gaz/huile.
PCT/US2008/064647 2007-05-23 2008-05-23 Estimation du rapport gaz/huile à partir d'autres propriétés physiques WO2008147953A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
BRPI0811933A BRPI0811933B1 (pt) 2007-05-23 2008-05-23 método para caracterizar uma proporção de gás-líquido dissolvido de um fluido
GB0919617A GB2463393B (en) 2007-05-23 2008-05-23 Estimating gas-oil ratio from other physical properties
NO20093427A NO342446B1 (no) 2007-05-23 2009-11-26 Estimering av gass-olje-forhold for et brønnfluid ut fra andre egenskaper

Applications Claiming Priority (2)

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US93138107P 2007-05-23 2007-05-23
US60/931,381 2007-05-23

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GB (1) GB2463393B (fr)
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US10975687B2 (en) 2017-03-31 2021-04-13 Bp Exploration Operating Company Limited Well and overburden monitoring using distributed acoustic sensors
WO2021093976A1 (fr) * 2019-11-15 2021-05-20 Lytt Limited Systèmes et procédés d'améliorations du rabattement dans des puits de forage
WO2021093974A1 (fr) * 2019-11-15 2021-05-20 Lytt Limited Systèmes et procédés d'améliorations du rabattement dans des puits
US11053791B2 (en) 2016-04-07 2021-07-06 Bp Exploration Operating Company Limited Detecting downhole sand ingress locations
US11098576B2 (en) 2019-10-17 2021-08-24 Lytt Limited Inflow detection using DTS features
US11199084B2 (en) 2016-04-07 2021-12-14 Bp Exploration Operating Company Limited Detecting downhole events using acoustic frequency domain features
US11199085B2 (en) 2017-08-23 2021-12-14 Bp Exploration Operating Company Limited Detecting downhole sand ingress locations
US11333636B2 (en) 2017-10-11 2022-05-17 Bp Exploration Operating Company Limited Detecting events using acoustic frequency domain features
US11466563B2 (en) 2020-06-11 2022-10-11 Lytt Limited Systems and methods for subterranean fluid flow characterization
US11473424B2 (en) 2019-10-17 2022-10-18 Lytt Limited Fluid inflow characterization using hybrid DAS/DTS measurements
US11593683B2 (en) 2020-06-18 2023-02-28 Lytt Limited Event model training using in situ data
US11643923B2 (en) 2018-12-13 2023-05-09 Bp Exploration Operating Company Limited Distributed acoustic sensing autocalibration
US11859488B2 (en) 2018-11-29 2024-01-02 Bp Exploration Operating Company Limited DAS data processing to identify fluid inflow locations and fluid type
US12196074B2 (en) 2019-09-20 2025-01-14 Lytt Limited Systems and methods for sand ingress prediction for subterranean wellbores

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US20060241866A1 (en) * 2005-04-22 2006-10-26 Baker Hughes Incorporated Method and apparatus for estimating of fluid contamination downhole

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