U.S. patent application number 14/804895 was filed with the patent office on 2015-11-12 for flow management system and method.
The applicant listed for this patent is Advanced Flow Technologies Inc.. Invention is credited to Steve CONQUERGOOD, Len JOHNSON.
Application Number | 20150322773 14/804895 |
Document ID | / |
Family ID | 54367387 |
Filed Date | 2015-11-12 |
United States Patent
Application |
20150322773 |
Kind Code |
A1 |
JOHNSON; Len ; et
al. |
November 12, 2015 |
FLOW MANAGEMENT SYSTEM AND METHOD
Abstract
A monitoring tool is provided for monitoring wells for flow
anomalies. The temperatures of flowing well fluid and ambient
temperature are monitored and various methods applied to indicate
if a well is flowing as expected, is flowing less than expected
and, therefore, at risk of flow stoppage, not flowing or
calculation of flow rate when the well is flowing less than
expected. Approaches are described for determining trending
indicators from actual flow temperatures compared to a normal flow
relationship for establishing the presence of flow anomalies.
Temperature sensors, onsite processors and communications upload
data for display of well status flags on a mapping module enabling
pro-active detection and preventative action by operators.
Inventors: |
JOHNSON; Len; (Calgary,
CA) ; CONQUERGOOD; Steve; (Priddis, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Advanced Flow Technologies Inc. |
Calgary |
|
CA |
|
|
Family ID: |
54367387 |
Appl. No.: |
14/804895 |
Filed: |
July 21, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13462778 |
May 2, 2012 |
9121770 |
|
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14804895 |
|
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61521647 |
Aug 9, 2011 |
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Current U.S.
Class: |
702/12 |
Current CPC
Class: |
E21B 47/00 20130101;
G01K 2013/024 20130101; G01F 1/68 20130101; G01K 3/08 20130101;
G01K 13/02 20130101; G01F 15/063 20130101; E21B 47/07 20200501;
E21B 47/10 20130101 |
International
Class: |
E21B 47/06 20060101
E21B047/06; E21B 47/00 20060101 E21B047/00 |
Claims
1. A method for calculating flow rate of fluid from a well, the
method comprising: establishing a relation between characteristics
of the fluid and a surface component through which the fluid is
flowing for deriving a heat balance for the surface component;
establishing a relation between a temperature of the surface
component and ambient temperature; measuring the temperature of the
surface component and measuring the ambient temperature around the
well; and for a given instance of time; calculating the flow rate
of the fluid based on the measured temperature of the surface
component, the heat balance and the measured ambient
temperature.
2. The method of claim 1 wherein the characteristics of the fluid
comprise a temperature of the fluid or a rate of flow of the fluid
or specific gravity of the fluid or any combination thereof.
3. The method of claim 1 further comprising establishing a normal
flow temperature for the fluid during normal flow rate from
historical actual flow temperatures from the well and ambient
temperatures and wherein the measured temperature is between the
normal temperature and the measured ambient temperature.
4. The method of claim 1 further comprising optimizing calculation
of the flow rate by identifying factors influencing the heat
balance.
5. The method of claim 4, wherein the identified factors comprise
wellbore characteristics or wellhead characteristics or any
combination thereof.
6. The method of claim 1 further comprising calculating the flow
rate using computer modelling.
7. The method of claim 1 further comprising identifying the well as
a non-flowing well, having a flow rate of substantially zero, if
the measured temperature of the surface component is substantially
identical to the measured ambient temperature.
8. The method of claim 1 further comprising identifying the well as
as having the normal flow rate if the measured temperature of the
surface component trends towards the established normal flow
temperature.
9. A system for calculating flow rate of fluid from a well, the
system comprising: a processing equipment for: establishing a
relation between characteristics of the fluid and a surface
component through which the fluid is flowing for deriving a heat
balance for the surface component; establishing a relation between
the temperature of the surface component and ambient temperature;
at least one temperature sensor for measuring the temperature of
the surface component and measuring the ambient temperature; and
communicating equipment coupled to the at least one temperature
sensor and the processing equipment for relaying the measured
temperature of the surface component and the ambient temperature to
the processing equipment, wherein for a given instance of time, the
processing equipment, calculates the flow rate of the fluid based
on the established relations between the measured temperature of
the surface component, the heat balance and the measured ambient
temperature.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation-in-part of U.S. patent
application Ser. No. 13/462,778 entitled "FLOW MANAGEMENT SYSTEM
AND METHOD" and filed May 2, 2012 and claims the benefit of U.S.
Provisional Application Ser. No. 61/521,647, filed Aug. 9, 2011,
the entireties of which are incorporated fully herein by
reference.
FIELD
[0002] This invention relates generally to a system and method for
monitoring flow in gas and oil wells. More particularly, the
invention relates to detection and notification of well failures
including diminishing or loss of flow rate, which can be caused by
freeze offs, water loading, sand, scale, mechanical equipment
failure including pump jacks, downhole pumps, engines, hydraulics,
sucker rod, continuous rod, valves, piping, and operational issues
including gas locks, tubing leaks, field injection variations.
BACKGROUND
[0003] Flowing wells can fail unexpectedly. The Province of
Alberta, Canada has over 70,000 low flow, shallow gas wells.
Producers annually lose 5-15% of their wintertime production due to
freezing of wells and pipelines. The lost production can cost the
producers in the range of $70-100 million annually. Due to the low
revenue generation of individual wells, shallow gas fields and
mature oil fields generally have very little instrumentation.
Production measurement or measurement of flow tends to happen at
group meters and batteries, which reside sporadically throughout a
field, and usually have dozens or more unmetered wells flowing into
them. In the case of oil wells, the causes of failure are more
numerous as such wells include more mechanical components such as
pumping apparatus.
[0004] In the winter, producers watch their group meters for
production drops, which typically indicate that one or more wells
upstream of the meter are frozen. However, the meter does not
identify the frozen well or wells. Field personnel then either
attempt to find the frozen wells and inject a freeze inhibitor such
as methanol (methanol lowers the freezing temperature of water) in
an attempt to break up the ice or simply "batch pour" methanol into
wells more or less indiscriminately as a preventive measure.
Methanol injection method, which has been used for decades, is
often ineffective, expensive and potentially unsafe including
arranging risky wintertime access to leases regardless whether
wells are frozen or not.
[0005] Applicant believes, this method persists because there is
currently no other solution which is not cost prohibitive. At
current prices, an average gas well produces $15,000-20,000 per
year in revenue. Traditional production measurement instrumentation
which could indicate the status of each well costs in excess of
$5,000 per well. Given the large numbers of such wells, producers
have not incorporated traditional measurement instrumentation on
most wells.
[0006] While oil wells have higher revenues than gas wells, control
is also more expensive, often implementing pump-off controls. It is
not always economical to employ pump-off and to incorporate
traditional measurement instrumentation on older low flowing oil
wells.
[0007] In summer, producers note diminished flow rates from gas
wells due to liquid loading in the wells and may take steps to
rectify the problem by unloading the liquid from the well.
[0008] There is a need for a system and method for optimized
measurement of flow so as to enable a producer to effectively
manage a well.
SUMMARY
[0009] Generally, a low cost tool is provided for monitoring wells
for flow anomalies and quantification of flow. The relationship,
including the gap between flowing temperature and ambient
temperature proves that flow is occurring. This temperature
difference can be modelled to report flow rate to producers. Flow
rate information may be used to identify flow reductions and/or
interruptions, to avoid downtime and for production reporting. In
winter conditions, early detection and predictive techniques can
avoid un-necessary, expensive and environmentally sensitive dosing
of wells with methanol or other freeze inhibiting agents. Further,
personnel are not placed at personal risk in the travelling and
attending of well sites that are not in need of attention. Further,
in any season, such detection provides certainty to operators
including understanding well production variation and equipment
reliability. Notification can be through a variety of means
including electronic alerts or visual alerts such through a map
view feature.
[0010] Systems and kits, as described herein, can be installed by
the end user and need not require electrical infrastructure not be
near a utility. Hence, older wells can be retrofit where it has
otherwise been uneconomical for implementing pump-off controls or
instrumentation.
[0011] In one aspect, a method is provided for identifying wellhead
flow anomalies comprising collecting actual flow temperatures and
ambient temperatures for establishing a normal flow relationship
for flow from the wellhead for various ambient temperatures,
measuring actual flow temperatures over time for flow from the
wellhead and measuring ambient temperature and determining trending
indicators from the actual flow temperature compared to the normal
flow relationship for establishing wellhead flow anomalies.
[0012] In another aspect, a method for calculating flow rate of
fluid from a well is provided. The method comprises establishing a
relation between characteristics of the fluid and a surface
component through which the fluid is flowing for deriving a heat
balance for the surface component. The method further comprises
establishing a relation between a temperature of the surface
component and ambient temperature. Further, the temperature of the
surface component and the ambient temperature around the well are
measured. The method further comprises calculating the flow rate of
the fluid, for a given instance of time, based on the measured
temperature of the surface component, the heat balance and the
measured ambient temperature.
[0013] In another aspect, a system for calculating flow rate of
fluid from a well is provided. The system comprises a processing
equipment for establishing a relation between characteristics of
the fluid and a surface component through which the fluid is
flowing for deriving a heat balance for the surface component. The
processing equipment also establishes a relation between the
temperature of the surface component and ambient temperature. The
system further comprises least one temperature sensor for measuring
the temperature of the surface component and measuring the ambient
temperature. Further, the system comprises a communicating
equipment communicatively coupled to the processing equipment for
relaying the measured temperature of the surface component and the
ambient temperature thereto. The processing equipment, for a given
instance of time, calculates the flow rate of the fluid based on
the established relations between the measured temperature of the
surface component, the heat balance and the measured ambient
temperature.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] FIG. 1A is a block diagram of one embodiment of a flow
monitoring and analysis system, applied to a gas well;
[0015] FIG. 1B is a simplified cross-section of a wellhead having a
temperature sensor installed at various optional locations;
[0016] FIG. 2 is a time graph of the flowing temperatures of gas
from a gas well over time as the ambient temperatures vary in a
winter season;
[0017] FIG. 3 is a flowchart illustrating various embodiments of a
flow obstruction or anomaly detection algorithm;
[0018] FIG. 4 is a time graph of the temperatures of gas from a gas
well over time through a series of flowing and frozen or no flow
incidents;
[0019] FIG. 5 is a time graph of the temperatures of gas from a gas
well trending downward over time, on its way to freezing;
[0020] FIG. 6 is a time graph of the temperatures of gas from a gas
well over time where methanol is effectively applied once risk of
freezing is predicted;
[0021] FIG. 7 illustrates a dynamic map having gas wells and gas
pipe lines displayed thereon, the gas wells indicating various
states of operation including flowing, at risk and frozen;
[0022] FIG. 8 is a time graph of the temperatures of gas from a gas
well over time which is not likely to freeze;
[0023] FIG. 9 is a cross-sectional view of simplified oil well
wellhead having production tubing oil flow and gas flow from the
tubing;
[0024] FIG. 10A is a time graph of the temperatures and pressures
of a 16 day period of relative normal operation of an oil well;
[0025] FIG. 10B is a close up of a flow interruption highlighted on
November 17 of the operations of FIG. 10A;
[0026] FIG. 11 is a time graph of the temperatures and pressures of
a 16 day period of operation of an oil well with a general trending
to freeze off;
[0027] FIG. 12 is a time graph of the temperatures and pressures of
a 16 day period of operation of an oil well demonstrating
intermittent flow to freeze off;
[0028] FIG. 13A is a flow chart of one embodiment of the steps to
identify flow anomalies;
[0029] FIG. 13B is a graph of linear weighting factors as applied
to the difference between calculated and actual flow
temperatures;
[0030] FIG. 13C is a graph of exponential weighting factors as
applied to the difference between calculated and actual flow
temperatures, and as the difference exceeds +/-5 C;
[0031] FIG. 13D is a flow chart of another embodiment of the steps
to identify flow anomalies including weighting factors;
[0032] FIG. 14 is a graph of the relationship of ambient
temperature and normal flowing temperatures, ambient oscillating
between about -13 C and 26 C;
[0033] FIG. 15 is a graph illustrating a linear best fit
correlation between ambient temperatures and flow temperature;
[0034] FIG. 16 is a graph illustrating the graph of FIG. 14, with a
curve for predicted or calculated normal flow temperatures for the
controlling ambient temperature, the actual and calculated flow
temperatures nearly superimposed;
[0035] FIG. 17 is a graph according to FIG. 16 with the difference
dT between the actual and calculated flow temperatures shown about
a zero or ideal base line;
[0036] FIG. 18 is a graph according to FIG. 17 with range limits or
bounds added about the dT zero base line to provide a threshold for
indicating a well at risk of flow stoppage;
[0037] FIG. 19 is a graph according to FIG. 18 moved forward in
time from normal operation to an identified event, the dT having
fallen well outside of the bounds and indicating a well
experiencing flow stoppage;
[0038] FIG. 20 is a graph illustrating trending behaviour which
could be at risk, or related to other operating parameters;
[0039] FIG. 21 illustrates the case of identifying no flow
scenarios with an identify function of ambient temperature and flow
temperature;
[0040] FIG. 22 is a graph of flowing temperature and ambient
temperatures for normal flow, for normal flow with the measurement
location insulated and not insulated, and when during flow
stoppage;
[0041] FIG. 23 is a graph according to FIG. 21 illustrating
weighting factors based on the degree to which the temperature
difference dT varies away from the expected flow relationship;
[0042] FIG. 24 is a schematic representation of a second
embodiment, the schematic illustrates a well which is flowing and
effect of the fluid on the surface piping;
[0043] FIG. 25 is a schematic representation of the well of FIG. 24
when it is not flowing;
[0044] FIGS. 26 and 27 are graphs illustrating the relationship
between actual flow temperatures to ambient temperatures (measured
around the well of FIG. 24) and an established normal temperature
for identifying expected flow, less than expected flow and no flow,
FIG. 26 is based on actual field data and FIG. 27 is a theoretical
graph illustrating a desired performance; and
[0045] FIG. 28 is a schematic of one embodiment of a flow rate
calculation system.
DESCRIPTION
[0046] Embodiments described herein are directed to a flow
management system that captures information from a well and
transmits the captured information to a remote location for further
processing in order to determine whether the well is flowing
normally or not, and further, for quantification of the flow rates
therefrom.
[0047] In one embodiment the captured information is processed to
determine whether the flowrate from the well is normal or
abnormal.
[0048] In another embodiment, the captured information is processed
to determine whether the well is frozen or about to freeze.
[0049] In another embodiment, the captured information is processed
to determine whether the operability of the well for the flow
production of the product fluids is compromised, such as through
impending or sudden mechanical or process failure.
[0050] Further, the processed data is correlated in a graphic
representation with location of the wells and represented in forms
including a red, yellow and green status, which provide producers
with a highly specific level of information regarding the status of
the wells.
[0051] In one embodiment, a volumetric flow rate for an actual flow
temperature is determined.
[0052] Embodiments are explained herein in the context of
monitoring flow in wells during winter. The graphs described herein
illustrate the studies carried out by the Applicant. The principles
herein apply to gas wells and to oil wells.
[0053] FIG. 1A is a block diagram of one embodiment of the system
of the invention. FIG. 1B is a general schematic illustration of
various ways of locating the system of FIG. 1A at a well site.
Access to the flow stream can include thermowells to separate the
pressure boundary from the sensor, or direct access through tee
fittings.
[0054] With reference to FIG. 1B, one or more components of the
system 1 is installed in a wellhead W or in a pipe P conducting
fluid therein adjacent the wellhead W. The fluid is a varying
mixture of gas, water, and oil. Typically in wellhead applications,
data is moved from wellhead locations via 4-20 mA or 1-5V dc
signals to a remote terminal unit (RTU). The RTU then sends the
data to a centrally located computer based system by radio
transmission. Herein, the system 1 comprises a sensor 2 which
senses the temperature of the gas flowing in the pipe i.e. internal
gas temperature (Gi) and the ambient temperature (Am) at the well
site. The sensor 2 is connected to a processor 3 which may include
storage or memory. The captured temperature information is stored
in the processor 3. The system 1 further comprises a communication
transmission device, such as a satellite modem 5 for transmitting
the captured information to a remote processing unit 4 for further
processing. In one embodiment, the system 1 is capable of
processing at least some of the captured information. The captured
information can be transmitted to the remote processing unit 4 by
other communication methods such as radio or cell phone
communication. The remote processing unit can be a server. The
server can provided notification to operators and others through
various means including electronic messaging and mapping. The
various components of the system 1 are powered by a power source 6.
Typically the power source is a battery. Some or all of the
captured information is processed or analyzed at the remote
processing unit 4 to determine the status of the well i.e. to
determine whether the well is flowing or whether the well is frozen
or whether the well is about to freeze.
The system 1 can have a small number of easily assembled
components. In one embodiment, the system 1 senses and transmits
parameters such as flow and pressure in the pipe.
[0055] Processing or Analysis
[0056] Applicant has studied the temperature of fluids flowing from
wells. In one case, Applicant has noted the characteristics of gas
flowing from shallow gas wells, their studies indicating the
following:
[0057] A. The temperature of gas emanating from shallow gas wells
is typically very stable. When flowing normally, the temperature of
the gas in the well (Gi) is in the range of about 5-8.degree.
Celsius (Tw) regardless of ambient temperature (Am). Tw is related
to the formation temperature, variable with depth. Applicant has
established Tw for various well formations after extensive studies
and data analysis.
[0058] B. When a well stops flowing, temperature inside the pipe
(Gi) moves toward ambient temperature (Am). That is, it will rise
in the summer and fall in the winter. Observations at A and B are
illustrated in FIG. 2. Internal gas temperature (Gi) is indicated
by X and ambient temperature (Am) is indicated by Y. Two things are
noticeable in FIG. 2--first, during normal flow, the internal gas
temperature (Gi) operates in a very stable zone even while the
ambient temperature (Am) fluctuates. Second, if the well is not
flowing (circled portions in FIG. 2) temperature inside the pipe
i.e. internal gas temperature (Gi) moves toward ambient (Am)--up in
the summer (circle E) and down in the winter (circle F).
[0059] C. When wells freeze, they do not do so overnight but
typically over a period of weeks.
[0060] FIG. 3 is a flowchart illustrating the steps of a flow
obstruction or flow anomaly detection algorithm processed at the
remote processing unit 4 of FIG. 1 to determine the status of the
gas well during winter. The temperature of fluid emanating from the
wellbore, Tw, is typically determined at block 30. The internal
flowing gas temperature (Gi) at the wellhead (block 31) and the
ambient temperature (Am) are measured (block 32) by the sensor 2.
If, at block 33, the ambient temperature is less than 0.degree. C.,
a first simple check is made to determine whether Gi is equal to
Tam (block 35) and the well is frozen at block 36. If flowing
temperature Gi is equal to Tam, the well is frozen. This indicates
that the well needs to unblocked. Typically this is done by
injecting methanol. Alternatively, at block 35, If Gi is not equal
to Am, a check is made to determine whether the difference between
Gi and Am is greater than a set gap threshold (block 37); and if
so, at block 38 the well is flowing. If the difference between Gi
and Am is not greater than the set gap threshold, meaning the
flowing temperatures and the ambient temperature are close or
closing, the well is a freeze off candidate, i.e. the well is very
likely about to freeze (block 39).
[0061] Back at block 33, if the ambient temperature (Am) is greater
than freezing (0.degree. C.), the well is flowing at block 38.
[0062] FIG. 4 illustrates the results of the algorithm from block
33. The graph indicates that when the internal gas temperature (Gi
and indicated by X) and ambient temperature (Am and indicated by Y)
match exactly, the well is frozen and is not flowing. There is a
noticeable drop in production when this happens. The graph also
indicates that when the internal gas temperature (Gi) diverges from
the ambient temperature (Am), the well is flowing. Field personnel
can head out to the lease to unblock the wells at the point of
first freeze (first dotted circle).
[0063] FIG. 5 illustrates the result of block 37. In Alberta,
beginning in late November, when ambient temperature (Am) indicated
by Y begins to drop (dips below 0.degree. C.), the temperature
inside the pipe (Gi) indicated by X begins to trend or drift down.
Each time Gi dips below 0.degree. C., ice begins to form. Finally,
as seen on the far right of the graph, the well goes into freeze
up, some 5 weeks after the process started.
[0064] Rather than waiting for the well to freeze completely, the
producers can be proactive and apply methanol to the well, and only
that candidate well, when the ice starts to form. This is
illustrated in FIG. 6, which shows that methanol is applied (shaded
portions in the graph) when Gi and Am are below 0.degree. C. and Gi
starts trending towards or following Am.
[0065] As discussed above, ambient temperature (Am) and internal
gas temperature (Gi) are values determined through measurement.
Typically, for the gas wells in Alberta, Canada and the purposes of
the example detection algorithm, the well temperature Tw is assumed
to be 5.degree. C. In one embodiment, the detection algorithm is as
follows:
[0066] If the Log 10[(abs(5-Am)*(Gi-5)A2)/(if (abs(Gi-Am)<2, 1,
ABS(Gi-Am) 2))>=B where Tw was about 5.degree. C. and B is about
2 for a typical gas well, then the flow is likely interrupted or
close to freeze up. Action needs to be taken to avoid freeze up
interruption of the flow.
[0067] If abs(Gi-Am)<B, where B=2 then a Trend of flow
temperature is determined as log.sub.10[abs(Tw-Am)*(Gi-Tw).sup.2]
and if the value of the Trend >=B then there is risk of flow
stoppage.
[0068] If abs(Gi-Am)>=B then a Trend of flow temperature is
determined as
log.sub.10[(abs(Tw-Am)*(Gi-Tw).sup.2)/abs(Gi-Am).sup.2)] and if the
value of the Trend >=B then there is a risk of flow
stoppage.
[0069] Further, as has been determined to be applicable to gas
flows from a gas well, a trend of the rate of change (TrendR) of
the difference between flow temperature and ambient temperature can
be indicative of flow anomalies, wherein Rate Trend or
TrendR=d(Gi-Am)*abs(Gi1-Am1).sup.2>100 where
d(Gi-Am)=(Gi1-Am1)/(Gi0-Am0).
[0070] Where an average of the last dynamic period (say three
hours) of the TrendR is greater than a threshold, say about 100,
then the flow is identified as having resumed normal flow and no
action needs to be taken.
[0071] The term abs(Gi-Am) 2 is used in both flow interrupted and
flow resumed equations to weight the value of the data point. When
the ambient temperature Am is close to the gas internal temperature
Gi then there is a possibility that the well can freeze.
[0072] According to one embodiment, anomalies are spotted by
determining the slope (Gi@max-Gi@min)/(Ammax-Ammin) over a time
period; typically a time period over a prior 24 hours is suitable
for detection. The time period of 24 hours typically includes a
wide range of ambient temperature through a day and night cycle,
and provides a sufficient data sample.
[0073] According another embodiment, flow stoppage or freeze off
can be predicted by looking at the square of the cumulative error.
A best fit line/polynomial equation is used to fit the flowing
data. New ambient data points are taken and the internal gas
temperature is predicted based on the best fit line. The error is
the difference from the predicted and actual, the difference being
zero when the two are the same. For normal flow, variation of the
difference falling below zero generally cancels with variations
above zero. If the cumulative error is increasing then this points
towards a pending freeze off or no flow situation.
[0074] According to another embodiment, freeze offs can be
predicted by looking at the distribution of gas temperatures at a
specific ambient temperature.
[0075] The further from the mean, the greater is the suggestion
that the flow is in the process of being interrupted.
[0076] According to another embodiment, freeze offs can be
predicted by looking at determining values predicting what the flow
temperature would be, based on ambient conditions when there is no
flow. Based on how closely the data matches the no flow prediction
model suggests would indicate whether or not the well is flowing or
not.
[0077] Presentation and Mapping of Processed Information
[0078] Managing information from potentially thousands of wells can
be a daunting task for producers. Therefore, in order to make it
easier for producers to use the processed information i.e. state of
the wells, the processed information is presented in a form which
can be readily read and understood by the producers.
[0079] In one embodiment, the processed information is correlated
with the location of the wells using appropriate mapping data
module or tools, such as that available from the Energy Resources
Conservation Board (ERCB) in Alberta, Canada, and displayed in a
format as shown in FIG. 7. The map in FIG. 7 shows gas wells and
gas pipe lines. Circles with dots in the map, normally depicted as
a green circle, indicate wells which are in a steady state and in
no danger of freezing. This state is also indicated by FIG. 8.
Shaded triangles, normally depicted as a yellow circle, indicate
wells where Gi is trending towards Am. These wells are potential
freeze off candidates and probably need investigation. Shaded
squares, normally depicted as a red circle, indicate wells that are
frozen. Through the substantially continuous transmission of well
data to the remote processing unit 4, the map can be updated in
substantially real time for best detection and timely response.
[0080] Thus, one assigns status flags for trending indicators
comprising normal flag for normal flows, a risk flag for flows
indicating a risk of flow anomalies, and a frozen wellhead. The
status map is updated by illustrating each wellhead displayed
thereon, fit with an embodiment described herein, for displaying
normal, risk or frozen status flags for the wellhead.
[0081] This form of representation provides a radically different
method for locating frozen wells as it pinpoints locations rather
than relying on the indiscriminate guess work approach presently
employed in the industry.
[0082] The system and method described herein allow producers to
distinguish between wells that are going to freeze and those which
are not and allow the producers to be proactive by treating wells
which are about to freeze. This totally changes the method from
reactive, hastily executed and indiscriminate approach to a
proactive, planned over time and highly discriminating program. The
result is higher production levels, lower costs and greater safety
combined with an extremely attractive return on investment (ROI)
for the producers. The technology allows producers to be
knowledgeable and proactive about treating freeze offs.
[0083] Flow of gas in shallow wells during summer can also be
monitored using the methodology and the system described herein.
Flow of gas during summer can be interrupted due to various factors
such as solar loading or liquid in the well which diminishes gas
flow. Applicant has observed that during summer, one can determine
when production decreases when the internal temperature of the gas
(Gi) trends towards the ambient temperature (Am). The detection
algorithm described above for detecting drop in production during
winter can also be used in summer to detect diminishing gas
flow.
Oil and Gas Embodiments
[0084] With reference to one common arrangement of a wellhead shown
in FIG. 9, and turning to an oil well embodiment, oil wells
commonly produce both gas and oil and water in widely varying
ratios. As described above for gas wells, monitoring temperature of
the flowing fluids over time provides useful indications of the
health of an oil well wellhead even when the makeup of the fluid
stream, and the flow regime, changes. Detection of low or no flow
conditions in oil wells, is conducted through analysis of at least
the temperature of several key aspects of the well. Early detection
allows for timely repair, minimized downtime, maximizes production
and minimizes damage or further damage to equipment. The flow
identification works for all well types including free flowing,
artificial lift, beam pumps, hydraulic pumps, submersible pumps,
progressive cavity pumps, sucker rod, and co-rod for example.
[0085] Flowing temperature can be sensed inside the wellhead flow
piping. Flowing temperatures can also be monitored using an
external temperature sensor strapped to outside of the piping,
typically using some degree of insulation to make the sensor more
reactive to the piping (See FIG. 22). Temperature sensors can be
positioned to monitor oil flow To, gas flow Tg, or mixed flow Tm.
Temperature sensors can be positioned inside the pipe, or on the
outside pipe wall.
[0086] Pressure signals can also be useful, annulus pressure having
generally a closer correspondence with tubing flow. Pressure sensor
monitors flowing pressure and pressure cycles from pumping. In
pumping arrangements, wellhead temperature is typically measured at
a pump's stuffing box.
[0087] Again, as in the gas embodiment, a reduction or loss of
fluid flow due to freezing can be indicated by one or a combination
of measured characteristics. Scenarios include a trending of
flowing temperature moving downwards towards ambient, say 0.degree.
C., flowing temperature correlating too closely with ambient; and
wellhead temperature correlating too closely with ambient.
[0088] Further, one can monitor a change in pattern of the
temperatures and/or pressure trend including intermittent flow
which causes cycling of the monitored signals. Characteristic of
oil wells which are being pumped, such as through mechanical
pumping apparatus extending down hole, is interaction of the moving
parts and the wellhead. In both reciprocating and rotary pumping
applications, a polish rod passes through the wellhead and is
sealed at a stuffing box of sorts. The seal interface is associated
with friction and localized heating. Such heating is typically
mitigated and cooled by the flowing stream of oil up the tubing and
out of the wellhead. Thus, a reduction of oil flow, for one reason
or another, results in wellhead temperature rising above
normal.
[0089] Further, a reduction in cyclic pressure levels can be
monitored as indicative of equipment failure or no oil being pumped
despite continued pump operation. Similarly, an increase in cyclic
pressure levels suggests a downstream restriction or blockage.
[0090] Notification of such problems can be remote from web server
including via electronic messaging (such as email), a mapping
module accessible by operators on an intranet or distributed
network or locally at the wellsite using indicator lights, cell
phone, wireless data message from processor itself.
[0091] With reference to FIG. 10A, a relatively normal flow
operation is illustrated with one interruption in flow on November
17 indicated by both a drop in flowing temperature and stuffing box
temperature. The drop is illustrated more clearly in a close up of
the period of interruption on FIG. 10B.
[0092] With reference to FIG. 11, monitored conditions are shown
with a partial reduction in flow and a complete stoppage, the
portion at November 20 illustrating a cessation of oil with some
gas flow from the annulus. The wellhead temperature has trended to
ambient, while flowing temperature, of the oil, is still warmer
than ambient. At November 22, both flowing temperatures and
wellhead temperatures have trended to ambient indicating no flow of
either oil or gas.
[0093] With reference to FIG. 12, monitored conditions are shown
with a 13 days of normal flowing operations and thereafter
intermittent flow to freeze off. On November 14, flowing
temperature and wellhead temperatures are intermittently tracking
ambient indicating developing problems. At November 18,
temperatures plummet to correlate with ambient indicating cessation
of flow with neither flow of oil nor gas.
[0094] Assessment of flow characteristics for an oil well, compared
to a gas well, have at least the following competing factors: the
volumetric flow rates from gas wells are typically much greater
than that of oil, however the heat capacity and conduction from the
flow of gas to the wellhead is less effective than that for oil,
negatively affecting the sensitivity of temperature measurement.
Further, the freeze off for gas wells is typically at about
0.degree. C. while oil is more aligned with sub-zero ambient
temperatures. Hence, the failure point for oil flows varies and may
be more akin to a chill-off point.
[0095] Note that while the examples are discussed in the context of
cessation of flow due to cold ambient temperatures, they can also
apply as warnings for a host of partial or complete failures such
as gradual pump failures, watering off, leaks or rupture in the
production tubing, some form of interference with the flow of
production fluids such as sand, scale, or paraffin at the
wellbore.
[0096] Hence, in another embodiment, determination of oil well
freeze-off is aided by inspection of the difference between actual
flow temperatures and normal flow temperatures for given ambient
temperatures.
[0097] Briefly, with reference to FIG. 13A, in an oil well
scenario, at Block 131, data is collected during normal flow
operations, establishing a relationship of flowing temperatures,
for that wellhead, for the recent experience of ambient
temperatures. The duration of history data required can vary from
several days to several months depending on the degree of
correlation of the two temperatures at various times. This degree
of correlation is influenced primarily by the volumetric flowrate
of the fluids, but secondarily by the composition of the flowing
fluid stream (oil/water/gas), by environmental conditions such as
season, sunlight, humidity, wind, by specific sensor installation
details (pipe size, sensor size, thermal coupling, insulation), and
data collection techniques such as sampling rate, averaging. At
block 132, a relationship, such as a linear relationship from
linear regression techniques, is calculated for predicting a normal
flow temperature for a given ambient temperature. In a linear
relationship slope M and intercept b are obtained for y=mX+b, where
X is the ambient temperature and Y is the measured flow
temperatures. Simplistically, going forward from the sample data,
if actual measured flow temperature varies from the predicted flow
temperature, then there could be an anomaly in the flow
conditions.
[0098] The relationship can be more sophisticated, as described
later, to accommodate for various other factors and
sensitivities.
[0099] A block 133, once the relationship is known, ongoing data is
obtained for the well. The data is likely streamed for analysing
the health of the well on an ongoing basis. At block 134, measured
ambient temperatures TAmb, as the controlling temperature X, is
processed through the normal flow relationship for predicting a
calculated flowing temperature TCalc if the well is normal. As the
relationship is an approximation, and many factors can affect the a
direct linear relationship, including rate of change of ambient
temperatures and nature of the flowing fluid, a predicted flow
temperatures will not exactly match the actual, even during normal
flow, or even the sample data reprocessed through the relationship.
Hence, the match of actual to predicted flow temperature is
compared within a range.
[0100] At block 135, a differential temperature is calculated
between the actual and predicted flow temperatures at each measured
ambient temperature over time.
[0101] When this differential temperature dT is about zero or close
thereto, the well is flowing completely normally, as indicated by
past measurement. At block 136, the differential temperature dT is
compared to a range either side of zero, the further from zero, the
more suspect, although the quantum of the variation from zero may
not be arithmetic. The magnitude of dT and whether dT is inside or
outside the chosen range is calculated. At block 137, if the
differential temperature dT is outside the chosen range, the well
is frozen or otherwise has stopped flowing.
[0102] At block 138, if the differential temperature dT is within
the range, further calculation determine how closely dT deviates
from zero, and if dT is approaching the range limits. At block 139,
if the differential temperature dT is approaching the range limits,
the well is at high risk of freezing or stopping flowing. At block
140, if the dT is within the range and close to the ideal zero
datum, the well is normal and flowing, at no risk of freezing.
[0103] With reference to FIG. 13B, a weighting factor can be
calculated which increases as differential temperature dT moves
away from zero and towards the assigned range limit. In the case of
FIG. 13B, the weighting factor is linear and ranges from 0.0 to
1.0, but many other types of calculations can be incorporated as
well. With reference to FIG. 13C, one can calculate non-linear,
such as exponential or other weighting factors, with other integer
or floating point numeric ranges to adjust the effect for each data
point as dT increases, nearing the range limit. Thus, as the
differential temperature dT approaches the range limit, the effect
of the temperature difference values approaching the range or error
bounds is accentuated, being more likely indicative of the flow as
being at risk or being frozen.
[0104] With reference to FIG. 13D, the normal flow relationship
which is to be calculated between ambient temperature TAmb and
flowing temperature TFlow can be modified to account for the
calculated weighting factors. Using these weighting factors
improves the correlation between these measured parameters, by
applying higher weighting to the values where the differential
temperature dT is near zero, and applying lower weighting to the
values where the differential temperature dT is near the range
limits.
[0105] With reference to some sample data, and as shown in FIG. 14,
normal flowing temperatures TFlow of the oil flow from an oil well
is illustrated, with a weak response of the oil flow temperature
TFlow compared to the ambient temperature TAmb, sharp drops in
ambient TAmb reflected by small changes in flowing temperature
TFlow. In an embodiment, a sampling of 100 to 1,000 data points for
normal flow are obtained for a starting relationship of ambient and
normal flow temperatures.
[0106] With reference FIG. 15, a relationship is obtained, such as
a linear regression of the data points, so as to establish a normal
flowing temperature for the independent variable of ambient
temperature TAmb. Hence, going forward, as ambient temperatures
TAmb varies, one can determine an expected normal flowing
temperature TCalc. The veracity of the example linear relationship
is illustrated in FIG. 16 in which actual flowing temperatures of
FIG. 13 are compared with the calculated flowing temperatures.
[0107] With reference to FIG. 17, a temperature difference between
actual and calculated temperatures is determined which, for the
normal data points, should track about zero. Hence, variation from
zero indicates a flowing temperature that has left the normal
relationship determined for that wellhead. As the example linear
relationship is not very sophisticated, there is some variation
from zero, even with normal flow.
[0108] With reference to FIG. 18, so as to aid in distinguishing
normal flow using the values for temperature difference, one can
establish range limits or difference bounds about the zero
relationship. Often non-zero temperature differences occur with
normal flow but will generally remain within the difference bounds.
Those temperature difference values approaching and falling outside
the difference bounds can be indicative of a risk of no flow and no
flow. As shown, difference bounds have been set at plus and minus
3.degree. C., variation of the temperature difference value all
falling within the bounds and in no case was the wellhead at risk
of no flow.
[0109] As shown in FIG. 19, in a clear example, as flow
temperatures falls to ambient, flow has stopped. However, even
prior to no flow, one can use the temperature difference, falling
outside well outside the difference bounds, as the indicator of
impending freeze off, permitting an alert and preventative
action.
[0110] Temperature difference bounds can also be used to temper the
predicted indications which are the effect of flow variations
rather than problems with the wellhead. For example, and with
reference to FIG. 20, at day 7 through 10, despite very low ambient
temperatures, a higher than typical opportunity for freeze-off, and
with a drop in the determined temperature difference, the lower
actual flow temperatures really were only indicative of a decrease
in flow rate unrelated to a problem with the well or wellhead.
[0111] This same variance in temperature difference dT can be used
to predict flow interruptions based on trending this series of
points over time. As the trend of dT moves towards the defined
range limits, forecasting methods can be used to generate an
exception status even before the actual limit is reached. This
forecasting can include a variety of mathematical techniques such
as extrapolating the slope of the trend line, integration of the
area under the curve, which represents the total amount of abnormal
flow condition, or calculating and applying tighter range limits
for short intervals of time to determine a succession of intervals
where the flow is judged to be normal or abnormal.
[0112] As shown in FIG. 21, a 1:1 relationship or identity function
is shown for the correlation between ambient temperature TAmb and
flowing temperature TFlow when the well is not producing at all.
Thus for any given ambient temperature, if there is no flow, the
flowing temperature will equal the ambient temperature. Data points
which fall outside the defined limit boundaries, and in particular
close to this 1:1 relationship are indication that there is no flow
at the well.
[0113] With reference to FIG. 22, a graph of flowing temperature
and ambient temperatures is illustrated for normal flow, for normal
flow with the measurement location insulated and not insulated, and
when the flow was down.
[0114] As shown in FIG. 23 the relative weighting of data points
can be established based on the degree to which the temperature
difference dT varies away from the expected relationship. As
previously discussed above, a calculation to establish weighting
factors can be linear, exponential, or other mathematical
formulations. Weighting factors are established such that as the
temperature difference dT approaches the defined range limit, the
weighting factor will decrease towards zero, indicating less strong
correlation, and less applicability of the measured data point.
[0115] A kit, referred to as an onsite watchdog unit, can be
provided for upgrading a wellhead for monitoring. One or more
sensors are provided, such as one or more temperature sensors, and
optionally one or more pressure sensors. Alternatively, one or more
sensors, having electronic output, may already at the wellhead for
other purposes. The watchdog unit comprises one or more sensor
inputs for receiving at least the temperature sensor signals, a
memory module for storing data including signals over time, a CPU
or processor for managing the sensor signals, and a communications
module for transmission of data to a remote site. The processor can
merely manage receipt of sensor signals for transmission as signal
data, or can perform some or all processing of the signals prior to
transmission. An embodiment of a communications module includes
satellite communications. Raw signals or processed data, comprising
at least data representing actual flow temperature and ambient
temperature, is uploaded to a server for further processing as
necessary and updating of a mapping module. The server may be
accessed by one or more applications including those for updating
the mapping module, for regulatory and interested party use.
[0116] In one example scenario, measured data channels included
flowing temperature (RTD with thermowell), stuffing box temperature
(surface RTD) and Ambient temperature (small RTD probe in shade).
Data was collected and stored each minute for establishing a normal
flow relationship. Once per hour, a dT between the lowest and
highest minute reading was calculated and reported. Hourly readings
were reported for channels including the three temperatures and
other sensors including pressure. All channels were transmitted
offsite every four hours for analysis and mapping.
Quantification of Flow Rate
[0117] The foregoing paragraphs establish the following: actual
flow temperatures and ambient temperatures can be correlated to
arrive at a normal flow temperature (TNorm) for a well.
Relationship between actual flow temperatures and ambient
temperatures, characterized during times when fluid is flowing from
the well, allows for calculation of TNorm.
[0118] The foregoing paragraphs have also established that when
actual flow temperature follows or trends towards TNorm, flow rate
of fluid from the well is as expected (normal condition). When
actual flow temperature trends towards TAmb, the well is not
flowing as expected (abnormal condition). The abnormal condition
could include reduced flow or no flow. Further, as set forth in
earlier embodiments, it has been determined that when actual flow
temperature is substantially identical to TAmb, the well is not
flowing.
[0119] The following paragraphs describe methodologies for
calculating and reporting a volumetric flowrate for an actual flow
temperature by understanding the effect of heat exchange between
the warm fluid and piping through which the fluid is being
conducted and heat loss to the environment.
[0120] It is a known phenomenon that heat from the elevated
temperature of a reservoir is carried with fluid as it flows up a
well to the surface. When warm fluid flows through a surface
component at the surface such as piping adjacent a wellhead, the
heat contained in the fluid affects the temperature of the piping
TPipe at the surface. The greater is the volume of warm fluid which
contacts the surface piping, the greater is the amount of heat
which is transferred to thereto.
[0121] It has been noted that when warm fluid normally flows
through the surface piping, because of the principle explained
above, TPipe diverges from and becomes more stable than the ambient
or atmospheric temperature TAmb.
[0122] The following paragraphs explain methodologies for
determining a volumetric rate for an actual flow temperature based
on the heat exchange between the fluid, the surface piping and the
environment. Embodiments calculating volumetric flow rate are
described in particular with reference to FIGS. 24 to 26B.
[0123] Heat from the elevated temperature of a reservoir 100 is
carried with fluid 102 as it flows up a well 104 to the surface S.
As used herein "fluid" includes gas or oil or water or mixtures
thereof. This heat causes temperature TPipe of a piping 106
adjacent a wellhead 108, at the surface, to diverge from the
ambient or atmospheric temperature TAmb. In other words, in normal
flowing condition, temperature TPipe of the surface piping 106 does
not match TAmb. This theory is illustrated in FIG. 24 and
establishes a first normal relationship between TPipe and TAmb.
Temperature of the surface piping may be measured by placing one or
more temperature sensors inside or otherwise in thermal sensing
relationship with the surface piping 106. The one or more
temperature sensors may be strapped to the outside of the surface
piping 106.
[0124] When fluid 102 stops flowing through the wellbore 104 and
consequently surface piping 106, it has been noted that TPipe
adapts to trend closely towards TAmb. The foregoing paragraphs
teach that when this occurs, a freeze-off is imminent. This theory
is illustrated in FIG. 25 and establishes that there is a second
relationship between TPipe and TAmb. As would be understood, time
and rate taken for TPipe to match TAmb depends on a multitude of
factors and will vary from one well to another.
[0125] Based on the teachings in the foregoing paragraphs, TNorm
can be calculated from empirical data collected for TPipe and TAmb.
Further, trending of TPipe with TNorm indicates that the well is
flowing as expected. An expected flow rate may be known or
calculated for TNorm for a particular well from historical flow
rate data collected for that well.
[0126] However, there are instances when the well is flowing but at
a reduced flowrate, such as at a flow rate which is less than the
expected flow rate. When this occurs, it has been noted that the
trend of TPipe will fall somewhere between the TAmb and TNorm. This
phenomenon has been illustrated in FIGS. 26 and 27. Calculating
volumetric flow rate when the well is not flowing as expected is
valuable to oil and gas producers as it indicates not only short
term production issues, but also longer term reservoir issues such
as decline rates and reserves.
[0127] In one embodiment, mathematical modelling is used to
determine and report the volumetric flow rate of fluid 102 flowing
through wellbore 104 during an abnormal condition. The flow rate is
calculated based on the measurements of TPipe and TAmb trended over
time. When TPipe and TAmb for any given instance of time is
provided, the model can compute the flow rate responsible for these
temperatures.
[0128] Fluid flow rate (F) may be calculated with the assistance of
standard methodologies, one such relationship being F=f(.DELTA.T,
Qp)
[0129] .DELTA.T=Difference between TAmb and TPipe
[0130] Qp=Pipe heat balance
[0131] As one would understand, heat balance is a relationship
between heat provided to the surface piping 106 and heat lost or
gained (QLoss) due to environmental factors. A major source of heat
input is the heat carried by the fluid from the reservoir, and
flowing through the well. Accordingly, the piping 106 can be viewed
as being warmed or cooled by the fluid flowing therethrough. The
temperature of the fluid will be equal to reservoir temperature
(TRes) at reservoir depth. The fluid cools as it flows up the
wellbore to the surface due to heat loss (QRes) into the well
piping and rock. This heat QRes causes TPipe to diverge from TAmb.
In normal instances (illustrated in FIG. 24), when fluid is flowing
through the pipe, the heat QRes provided to the pipe will be more
than the heat expended or lost QLoss. When the heat input QRes is
less than QLoss (illustrated in FIG. 25), this is an indication
that fluid flow through the pipe is very low or has stopped, as
flow of fluid through the pipe is one of the primary sources of
heat input.
[0132] For calculation of the flow rate and as stated above, a
relation between characteristics of the fluid and the surface
piping is established for deriving the heat balance Qp for the
surface piping. Further, a relation between TPipe and TAmb is
established. For a given instance, the temperature of the surface
piping and the ambient temperature are measured to arrive at
.DELTA.T and flow rate is calculated based on Qp and .DELTA.T.
[0133] It should be understood that, in the calculation of the flow
rate other appropriate factors may be taken into consideration such
as factors affecting the heat balance and .DELTA.T. Some of the
factors influencing .DELTA.T and Qp include: wellbore
characteristics such as well depth (reservoir temperature increases
with increasing depth, giving a greater heat source); subsurface
geology (some examples being rock composition and formation, faults
or geothermal variation) and wellhead characteristics such as
characteristics of the surface piping (for example, its diameter,
length, composition, orientation or solar exposure/loading).
Further influencing parameters include sensor placement and its
contact with surface piping; degree of insulation between the
surface piping, sensor, and atmosphere; and characteristics of
fluid (for example, a temperature of the fluid, a rate of flow of
the fluid or specific gravity) Of the above-stated factors, solar
loading has been found to be quite relevant on TPipe or temperature
of the overall system. In order to optimize the calculation of flow
rate despite solar loading, in one embodiment, only temperature
data from nighttime periods are utilized. In one embodiment, only
data points between 1 and 4 hours after sunset and the before the
next sunrise are taken into consideration to eliminate the
influence of solar loading.
[0134] It has been determined that the contribution of heat from
the reservoir varies considerably with the depth of the well. Due
to variations in geology and rock formation at different
geographical locations, rise in temperature with increasing depth
can vary from 0.6 to 1.6 degrees Fahrenheit per 100 feet of depth
below surface. Due to the substantial infinite heat source of the
reservoir, temperature of the fluid flowing through the well is
initially at the reservoir temperature. In one embodiment, errors
in the calculation of flow rate due to this variation, is
eliminated by either logging or calculating the reservoir
temperature at the time the well is drilled. This converts the
variable into a known parameter which may be categorized as a known
temperature.
[0135] In one embodiment, flow rate is calculated by entering into
a computer model any combination of the above-stated variables
along with TPipe and TAmb. With this known information the model
calculates the flow rate responsible for these temperatures.
[0136] In one embodiment, this calculated volumetric flow rate is
trended over time, and provided to a producer to be used for short
term or long term operational improvements. Long term improvements
may include reservoir modelling, draw down calculations, and
reserve calculations.
[0137] FIGS. 26 and 27 illustrate the relationship between TPipe,
TNorm and TAmb. As stated earlier, TNorm may be determined from
TPipe and TAmb collected for a well. TNorm is indicative of an
expected flow rate. As seen in FIG. 26, section marked A, when
TPipe closely follows TNorm, the well is flowing as expected. In
FIG. 26, section marked B, when TPipe starts to closely follow
TAmb, the well is likely to be frozen. In FIG. 26, section marked
C, when TPipe starts to diverge from TNorm and follow TAmb, the
well is not flowing as expected.
[0138] FIG. 27 is also indicative of the three states defined
above. As seen in FIG. 27, section marked A, when TPipe is closely
following TNorm, the well is flowing as expected and the flow rate
(F) of the fluid will be substantially equal to the expected flow
rate or FNorm. FIG. 27, section marked B, when TPipe diverges from
TNorm and starts to trend towards TAmb, the well is flowing less
than normal. Therefore, in such an instance, F<FNorm. FIG. 27,
section marked C, when TPipe is closely trending with TAmb, the
well is likely to be frozen. Accordingly, F will be likely equal to
zero.
[0139] FIG. 28 illustrates one embodiment of a flow rate
calculation system 110. As seen in FIG. 28, the system 110
comprises a processing equipment 112 such as a microcontroller. The
processing equipment 112 establishes a relation between the
characteristics of the fluid and the surface piping 106 for
deriving Qp. The processing equipment 112 also establishes a
relation between the TPipe and TAmb. The system 110 also comprises
a temperature sensor 114 for measuring TPipe and TAmb. Further, the
system comprises a communicating equipment 116 which is operatively
coupled to the temperature sensor 114 and the processing equipment
112. The communicating equipment 116 relays the measured TPipe and
TAmb to the processing equipment 112. After receiving the measured
TPipe and TAmb, the processing equipment 112 calculates the flow
rate based on Qp, measured TPipe and TAmb.
* * * * *