Patent Description:
Most oil-gas wells produce a mixture of oil, water, and gas. During hydrocarbon production, a determination of flow rates of individual phases (e.g., oil, gas, water, etc.) of a multiphase flow is desirable. The individual phase flow rates can be derived from the measured phase volume fractions and phase flow velocities. A determination of other properties of the multiphase mixture is also desirable, including the presence and salinity of produced water or injected water. Such properties can be used to determine information about the mixture and may affect other measurements being made on the multiphase mixture. Prior implementations to measure multiphase flows, such as thise described in <CIT> or in the <CIT>, use multiphase flowmeters and sensors to determine properties of the multiphase flows, e.g., permittivity of the mixture.

The present invention resides in an apparatus as defined in claim <NUM>, a method as defined in claim <NUM> and a non-transitory computer readable storage medium as defined in claim <NUM>.

The figures are not to scale. Wherever possible, the same reference numbers will be used throughout the drawing(s) and accompanying written description to refer to the same or like parts.

It is to be understood that the present disclosure provides many different embodiments, or examples, for implementing different features of various embodiments. Specific examples of components and arrangements are described below for purposes of explanation and to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting.

When introducing elements of various embodiments, the articles "a," "an," "the," and "said" are intended to mean that there are one or more of the elements. Moreover, any use of "top," "bottom," "above," "below," other directional terms, and variations of these terms is made for convenience, but does not mandate any particular orientation of the components.

Most oil-gas wells produce oil, gas, and water from an earth formation. For example, a flow of fluid including oil, gas, and water is considered a three-phase flow, or a multiphase flow or multiphase mixture. In such examples, the three-phase flow includes one gas phase corresponding to the gas component of the flow and two liquid phases corresponding to the oil and water components of the flow. It is desirable during an oilfield operation (e.g., well test operation, an oil and/or gas production operation, etc.) to perform flow measurements to determine the flow rates of individual phases of the multiphase flow. In particular, measurement of the volume fractions and flow velocities of for example, oil, gas, and water in a conduit, such as a pipe, is highly desirable. It is also desirable to determine properties of the multiphase mixture, such as the presence and salinity of water in the mixture, as this provides information about the mixture and may affect other measurements being made on the multiphase mixture.

In general, a determination of properties of a multiphase flow can be difficult due to a wide variety of flow regimes the multiphase flow can exhibit. For example, three phases of a multiphase flow can be mixed together with one phase as the continuous phase and the remaining two phases dispersed within the multiphase flow. Primarily, there is phase separation between gas and liquid with the liquid often moving at a much lower velocity than the gas.

Additionally, flow phase and velocity distributions of a multiphase flow may alter both spatially and temporally. Sudden or gradual variation in flow rates of one phase or another may cause a change in flow regime. Also, due to the high pressure encountered deep underground or below seabed, a flow that is mixed or in bubble-flow regime can become dominated by a discernible high gas fraction as the pressure drops nearer the ground or subsea surface and the gas expands and/or comes out of solution.

Prior implementations to measure multiphase flows used multiphase flowmeters and sensors to determine properties of the multiphase flows. In some prior implementations, the multiphase flowmeters included electromagnetic (EM) sensors such as radiofrequency (RF) and/or microwave sensors, electrical (e.g., capacitance, conductance) impedance sensors, to measure some of the properties including a permittivity and/or a conductivity of the multiphase flow through a conduit (e.g., a pipe). In such implementations, the multiphase flowmeter measured the permittivity and/or the conductivity at liquid-rich region(s) of the conduit (e.g., in the underside of a horizontal blind-tee section, in a near-wall region (e.g., a near inner-wall region) of a vertical pipe section). The multiphase flowmeter typically determined properties of the liquid phase of the multiphase flow including water conductivity (salinity). However, these prior implementations did not teach the determination a presence of water in the multiphase flow or in a wet-gas flow stream.

Examples disclosed herein include water detection manager apparatus to detect a presence of water in a multiphase flow and/or a wet-gas flow stream. The water detection manager apparatus detects the presence of water by determining a mixture permittivity and/or a mixture conductivity of the multiphase flow. The water detection manager apparatus determines the mixture permittivity and/or the mixture conductivity by obtaining measurements from one or more EM sensors at a high data acquisition rate (e.g., <NUM> kilohertz (kHz) measurement rate, <NUM> measurement rate, etc.). In some disclosed examples, the one or more EM sensors include an RF/microwave open-coaxial probe (e.g., a microwave frequency open-coaxial reflection probe), an RF/microwave local transmission measurement sensor, etc..

One or more probes are installed at a liquid-rich region of a horizontal blind-tee end-flange, or at a vertical pipe near wall region, or at a vertical pipe end-flange to obtain the sensor measurements. Example water detection manager apparatus disclosed herein can detect the presence of water in either horizontal or vertical conduits. For flow-assurance purposes, detecting the presence of water in multiphase flows is important for oilfield operations (e.g., providing an alert of the risk of the formation of hydrates in the flow line) when a flow-stream water-to-liquid ratio (WLR) is very low and/or a gas volume fraction (GVF) is very high. In some disclosed examples, the water detection manager apparatus can set a WLR measured by a multiphase flowmeter (e.g., a dual-energy gamma-ray based multiphase flowmeter (MPFM)) to zero to avoid and/or otherwise prevent reporting of non-physical (e.g., negative) time-averaged WLR values and, thus, improve an accuracy or a confidence in flow rate measurements of oil and gas phases in a multiphase flow.

<FIG> illustrates an example multiphase flow measurement system <NUM> including an example water detection manager <NUM> to determine liquid properties of a multiphase flow <NUM>. In <FIG>, the multiphase flow measurement system <NUM> includes an example blind tee <NUM>. The blind tee <NUM> of <FIG> includes an example inlet <NUM>, a first example conduit <NUM>, an example outlet <NUM>, an example end (flange) section <NUM>, and a second example conduit <NUM>. In <FIG>, the first conduit <NUM> is a horizontal blind tee conduit and the second conduit <NUM> is a vertical blind tee conduit. At the downstream of the outlet <NUM>, a multiphase flowmeter may be installed (not shown in <FIG>).

In operation, the multiphase flow <NUM> enters the blind tee <NUM> through the inlet <NUM>, travels along the first conduit <NUM>, through the second conduit <NUM>, and out through the outlet <NUM>. The end section <NUM> operates as a barrier that forces the movement of the multiphase flow <NUM> into the second conduit <NUM>. In general, the blind tee <NUM> is configured so that the first conduit <NUM> is approximately horizontal and the second conduit <NUM> is approximately vertical. In some examples, the horizontal orientation of the first conduit <NUM> enables an example bottom section <NUM> of the first conduit <NUM> to be liquid rich and an example upper section <NUM> of the first conduit <NUM> to be gas rich. Alternatively, the flow in the second conduit <NUM> may not flow vertically upward, but may be arranged to flow vertically downward, or at another angle relative to the first conduit <NUM>.

In some examples, the bottom section <NUM> of the first conduit <NUM> includes liquid rich regions even in multiphase flows with high gas-to-liquid ratios (e.g., wet gas with gas volume fraction (GVF) > <NUM>%). In some examples, liquid rich regions can be produced in the blind tee <NUM> proximate the end section <NUM> and/or beneath an example opening <NUM> of the second conduit <NUM>. In some examples, the first conduit <NUM> can be about <NUM> meters or less in length (e.g., <NUM> meters, <NUM> meters, <NUM> meters, etc.). Alternatively, the first conduit <NUM> may be more than <NUM> meters in length. In some examples, more pronounced liquid rich regions can be produced when the end section <NUM> and the opening <NUM> are separated by a section of the first conduit <NUM>, as illustrated in <FIG>.

In the illustrated example of <FIG>, a first example electromagnetic (EM) sensor <NUM> or a second example EM sensor <NUM> is disposed below a central axis <NUM> of the first conduit <NUM>. In <FIG>, the EM sensor(s) <NUM>, <NUM> are coupled to the water detection manager <NUM>. Alternatively, the EM sensor(s) <NUM>, <NUM> may be disposed above the central axis <NUM>. In <FIG>, the first EM sensor <NUM> is coupled to the first conduit <NUM> and is disposed in the bottom section <NUM> directly below the opening <NUM>. In <FIG>, the second EM sensor <NUM> is coupled to the end section <NUM> of the first conduit <NUM> and is disposed in the bottom section <NUM>. Additionally or alternatively, one or more of the EM sensors <NUM>, <NUM> may be disposed on the underside of the first conduit <NUM>, in the bottom section <NUM>, and/or coupled with the end section <NUM> below the central axis <NUM>. Additionally or alternatively, EM sensor(s) <NUM>, <NUM> may be installed at the liquid-rich region of a vertical pipe end flange, or at the near inner-wall liquid-rich region of a vertical pipe section.

In the illustrated example of <FIG>, the water detection manager <NUM> determines properties of the liquid phase (e.g., water conductivity/salinity, water volume fraction, WLR, etc.) of the multiphase flow <NUM> based on the positioning of the EM sensor(s) <NUM>, <NUM> in the blind tee <NUM> as depicted in <FIG> and/or in other examples as described above. In some examples, the water detection manager <NUM> can determine the properties of the gas phase (e.g., permittivity change with pressure and/or temperature) of the multiphase flow <NUM> based on alternative positions of the EM sensor(s) <NUM>, <NUM> or in combination with additional EM sensor(s) coupled to the blind tee <NUM>. For example, the water detection manager <NUM> can determine the gas phase properties based on one or more of the EM sensors <NUM>, <NUM> being disposed on the topside of the first conduit <NUM>, in the upper section <NUM> above the central axis <NUM>, near the inlet <NUM>, etc. In other examples, in addition to the EM sensor(s) <NUM>, <NUM>, additional EM sensor(s) can be disposed on the topside of the first conduit <NUM>, in the upper section <NUM> above the central axis <NUM>, near the inlet <NUM>, etc..

In <FIG>, the water detection manager <NUM> determines the properties of the liquid phase of the multiphase flow <NUM> that is present in a shallow measurement zone (e.g., about <NUM> millimeters (mm) depth of investigation) of the EM sensor(s) <NUM>, <NUM>, by obtaining sensor measurements from the EM sensor(s) <NUM>, <NUM>. In <FIG>, the EM sensor(s) <NUM>, <NUM> are RF/microwave frequency open-coaxial (reflection) probes (e.g., substantially similar to sensors described in <CIT>). Alternatively, the EM sensor(s) <NUM>, <NUM> may be RF/microwave-based magnetic-dipole antennas, RF/microwave local transmission measurement antennas, RF/microwave local resonance measurement antennas, millimeter-wave sensors, or electrical impedance (e.g., capacitance, conductance, etc.) measurement electrodes or probes (e.g., an electrical impedance local measurement sensor).

In the illustrated example of <FIG>, the EM sensor(s) <NUM>, <NUM> measure, at one or more chosen measurement frequencies, one or more properties of the multiphase flow <NUM>. The EM sensor(s) <NUM>, <NUM> perform sensor measurements (e.g. reflection measurements of amplitude-attenuation and phase-shift of the reflected RF signals relative to those of the incident signals) of the multiphase flow <NUM> and generate electromagnetic data based on the sensor measurements. The water detection manager <NUM> obtains the electromagnetic data from the EM sensor(s) <NUM>, <NUM> and determine a dielectric constant, or a permittivity (e.g., an electrical permittivity, a fluid permittivity, etc.), and/or a conductivity (e.g., an electrical conductivity, a fluid conductivity, etc.) of the multiphase flow <NUM> based on the electromagnetic data.

The water detection manager <NUM> determines a presence of water in the multiphase flow <NUM> based on values of permittivity and/or conductivity of the water phase being substantially higher than those of the hydrocarbon phase(s) (e.g., gas and/or oil), as shown in an example table <NUM> depicted in <FIG>. In the table <NUM> of <FIG>, a gas (e.g., a gas phase) has an example (relative) permittivity range of <NUM> - <NUM>. The relative permittivity of the table <NUM> represents a ratio of an absolute permittivity of a material relative to the absolute permittivity of vacuum. In the table <NUM> of <FIG>, oil (e.g., an oil phase) has an example (relative) permittivity range of <NUM> - <NUM>. In the table <NUM> of <FIG>, water (e.g., a water phase) has an example (relative) permittivity of approximately <NUM> at <NUM> degrees Centigrade (degC) with no salt content, and NaCl-based brines have example (relative) permittivities in the range approximately [<NUM>, <NUM>] depending on NaCl mass concentration dissolved in brine (i.e. salinity) and temperature. For example, pure water with no salt content (salinity zero) can have a relative permittivity of approximately <NUM> at <NUM> degC. In such examples, at the same temperature of <NUM> degC, the relative permittivity of water can decrease from approximately <NUM> to approximately <NUM> as the NaCl salt mass concentration in water (or salinity) increases to <NUM> kppm (thousand parts per million, or <NUM>%). At the same salinity, brine relative permittivity decreases with increasing temperature.

In the illustrated example of <FIG>, the table <NUM> depicts example conductivity values in Siemens per meter (S/m) for gas, oil, and water/brine. In the table <NUM> of <FIG>, gas has an example conductivity of <NUM>/m, oil has an example conductivity of approximately <NUM>/m, water has an example conductivity of approximately <NUM>/m with no salt content (and at DC or a low measurement frequency), and NaCl-based brines have example conductivities in the range approximately [<NUM>, <NUM>] S/m depending on NaCl mass concentration dissolved in brine and temperature. For example, pure water with no salt content can have a conductivity of approximately <NUM>/m at <NUM> degC. In such examples, at the same temperature of <NUM> degC, the conductivity of the water can increase from approximately <NUM>/m to approximately <NUM>/m as the salt concentration increases to <NUM> kppm. NaCl-based brine conductivity changes approximately <NUM>% per degC temperature change.

As noted in the table <NUM> of <FIG>, the permittivity for gas is pressure (p) and temperature (T) dependent. For example, the dielectric constant of methane gas increases with pressure at a fixed temperature. For example, at a pressure of approximately <NUM> bar and <NUM> degC, the dielectric constant of methane gas is <NUM>. Also noted in the table <NUM> of <FIG>, the permittivity values and/or ranges are given for light to heavy oil and are pressure, temperature, and measurement frequency dependent. Further noted in the table <NUM> of <FIG>, the permittivity and conductivity values for water/brine correspond to temperatures in a range of <NUM> to <NUM> degC and where a range of salinity of sodium chloride (NaCl) is <NUM> to <NUM> kppm.

The water detection manager <NUM> of <FIG> detects a presence of water based on the permittivity and conductivity values of the water phase being substantially higher than the gas and oil phases as shown in the table <NUM> of <FIG>. For example (not according to the present invention), the water detection manager <NUM> calculates a permittivity value of the multiphase flow <NUM> local to the EM sensor(s) <NUM>, <NUM> and determines that the multiphase flow <NUM> includes water based on the calculated (flow mixture) permittivity value being substantially higher (e.g., more than <NUM> times higher, etc.) than the permittivity values of <FIG> for the gas and oil phases. In other examples (not according to the present invention), the water detection manager <NUM> calculates a conductivity value of the multiphase flow <NUM> and determines that the multiphase flow <NUM> includes brine based on the calculated (flow mixture) conductivity value being substantially higher than a conductivity threshold value (e.g., higher than <NUM>/m etc.).

Turning back to <FIG>, the water detection manager <NUM> obtains EM sensor (raw) measurement data, or EM data, at substantially high data acquisition frequencies (e.g., <NUM>, <NUM>, etc.). For example, the water detection manager <NUM> can include RF and/or microwave measurement electronics to rapidly acquire RF and/or microwave measurement data from the EM sensor(s) <NUM>, <NUM>. The water detection manager <NUM> processes the EM data substantially instantaneously (e.g., at <NUM>, <NUM>, <NUM>, etc.) to calculate mixture parameters associated with the multiphase flow <NUM> over a moving (e.g., rolling) short-time window (e.g., a time window of Δt = <NUM>, <NUM>, <NUM>, etc.). Alternatively, the water detection manager <NUM> processes the EM data at any other specified processing rate. For example, there are at least one hundred EM data samples rapidly acquired over each short-time window Δt, for the water detection manager <NUM> to calculate one or more mixture parameters that represent a characteristic and/or a quantification of the multiphase flow <NUM> local to a measurement zone of the EM sensor(s) <NUM>, <NUM>, as described below in mixture parameters (<NUM>) - (<NUM>):.

Additionally or alternatively, the water detection manager <NUM> can calculate fewer or more mixture parameters than the mixture parameters (<NUM>) - (<NUM>) as described above. Additionally or alternatively, the water detection manager <NUM> can determine other parameters, for example the water-detection occurrence frequency over a relatively long duration of time (e.g., number of positive water-detection events calculated every <NUM> seconds (s)), and the water salinity (e.g. determined based on one or more of Mixture Parameters (<NUM>)-(<NUM>) above, such as the ratio of the water-rich Mixture Conductivity Maximum to the water-rich Mixture Permittivity Maximum).

In the multiphase flow measurement system <NUM> of <FIG>, the water detection manager <NUM> is communicatively coupled to an example network <NUM>. The network <NUM> of the illustrated example of <FIG> is the Internet. However, the network <NUM> can be implemented using any suitable wired and/or wireless network(s) including, for example, one or more data buses, one or more Local Area Networks (LANs), one or more wireless LANs, one or more cellular networks, one or more private networks, one or more public networks, etc. In some examples, the network <NUM> enables the water detection manager <NUM> to be in communication with another multiphase flow measurement system <NUM> and/or with an external computing device (e.g., a database, a server, etc.) coupled to the network <NUM>.

In some examples, the network <NUM> enables the water detection manager <NUM> to communicate with the external computing device to store the information obtained and/or processed by the water detection manager <NUM>. In such examples, the network <NUM> enables the water detection manager <NUM> to retrieve and/or otherwise obtain the stored information for processing.

In the illustrated example of <FIG>, the water detection manager <NUM> generates a report including one or more mixture parameters associated with the multiphase flow <NUM> and transmits the report to another computing device via the network <NUM>. For example, the network <NUM> can be a cloud-based network, which can perform cloud-based data storage, analytics, big data analysis, deep machine learning, etc., to enable multi-well, multi-field reservoir-scale modeling, digital oilfield high-efficiency operations and automation, oil-gas production management and/or optimization based on information obtained and/or processed by the water detection manager <NUM>. In some examples, the water detection manager <NUM> can be an Internet of Things (IoT) device enabled to facilitate capturing, communicating, analyzing, and acting on data generated by networked objects and machines.

The water detection manager <NUM> generates an alert such as displaying an alert on a user interface, propagating an alert message throughout a process control network (e.g., transmitting an alert to another computing device via the network <NUM>), generating an alert log and/or an alert report, etc. For example, the water detection manager <NUM> generates an alert corresponding to a characterization of the multiphase flow <NUM> including a detection of water in the multiphase flow <NUM>.

<FIG> is a block diagram of an example implementation (not according to the present invention) of the multiphase flow measurement system <NUM> of <FIG> including the water detection manager <NUM> of <FIG>. The water detection manager <NUM> obtains EM data from the EM sensor(s) <NUM>, <NUM> and calculates one or more mixture parameters associated with the multiphase flow <NUM> of <FIG> based on the EM data. The water detection manager <NUM> detects a presence of water in the multiphase flow based on the one or more mixture parameters. The water detection manager <NUM> can generate and transmit a report including the one or more mixture parameters and/or the water detection determination result to another computing device via the network <NUM>. Additionally or alternatively, the water detection manager <NUM> can generate and propagate based on the one or more mixture parameters and/or the water detection determination result to another computing device via the network <NUM>. In <FIG>, the water detection manager <NUM> includes an example collection engine <NUM>, an example measurement configurator <NUM>, an example parameter calculator <NUM>, an example water detector <NUM>, an example report generator, and an example database <NUM>.

In the illustrated example of <FIG>, the water detection manager <NUM> includes the example collection engine <NUM> to control a device and/or receive data from the device communicatively coupled to the water detection manager <NUM>. For example, the collection engine <NUM> implements RF/microwave sensor electronics to receive and/or otherwise obtain data from the EM sensor(s) <NUM>, <NUM>. In some examples, the collection engine <NUM> instructs the EM sensor(s) <NUM>, <NUM> to transmit data to the collection engine <NUM>. In other examples, the collection engine <NUM> receives data from the EM sensor(s) <NUM>, <NUM> without instructing the EM sensor(s) <NUM>, <NUM> to transmit the data. In some examples, the collection engine <NUM> controls the EM sensor(s) <NUM>, <NUM> by directing the EM sensor(s) <NUM>, <NUM> to excite a signal at a specified frequency (e.g., a measurement frequency). For example, the EM sensor(s) <NUM>, <NUM> can operate at one measurement frequency or a plurality of measurement frequencies.

In the illustrated example of <FIG>, the water detection manager <NUM> includes the measurement configurator <NUM> to adjust an operation of a device communicatively coupled to the water detection manager <NUM> and/or a configuration used by the parameter calculator <NUM> to calculate mixture parameters. In some examples, the measurement configurator <NUM> adjusts an operation of one or both EM sensors <NUM>, <NUM> by decreasing or increasing an excitation frequency of one or both EM sensors. In some examples, the measurement configurator <NUM> adjusts an acquisition frequency of the collection engine <NUM>. In some examples, the measurement configurator <NUM> changes a processing frequency, a type of measurement window used (e.g., a moving window, an exponential moving average, etc.), and/or a measurement window interval (Δt) used by the parameter calculator <NUM> to calculate mixture parameters associated with the multiphase flow <NUM> of <FIG>.

In the illustrated embodiment of <FIG>, the water detection manager <NUM> includes the parameter calculator <NUM> to calculate and/or otherwise determine one or more mixture parameters associated with the multiphase flow <NUM> of <FIG>. For example, the parameter calculator <NUM> calculates one or more of the mixture parameters (<NUM>) - (<NUM>) as described above at a processing frequency. For example, the parameter calculator <NUM> determines the mixture parameters (<NUM>) - (<NUM>) every <NUM>, <NUM>, <NUM>, etc., and/or any other processing frequency.

In the illustrated example of <FIG>, the water detection manager <NUM> includes the water detector <NUM> to determine a presence of water in the multiphase flow <NUM> based on one or more mixture parameters associated with the multiphase flow <NUM>. In some examples (not according to the present invention), the water detector <NUM> compares a permittivity (e.g., a maximum permittivity, a minimum permittivity, etc.) of the multiphase flow <NUM> to a water detection threshold and determines that water is present based on the comparison. For example, the water detector <NUM> determines that the permittivity satisfies the water detection threshold based on the permittivity being substantially greater (e.g., more than twice) than the oil permittivity, or other the water detection threshold.

The water detector <NUM> compares a permittivity difference to the water detection threshold and determines that water is present based on the comparison. According to the present invention, the permittivity difference is a difference between a maximum permittivity (εmax) and a minimum permittivity (εmin) during a time period or window period (Δt). The water detector <NUM> determines that the permittivity difference satisfies the water detection threshold based on the permittivity difference being greater (e.g., substantially greater) than the water detection threshold. In some examples, the water detector <NUM> sets a flag (e.g., a water detection flag) when water is detected based on the permittivity, the permittivity difference, etc. As used herein, the flag is an indicator variable in computer and/or machine readable instructions.

In some examples (not according to the present invention), the water detector <NUM> compares a conductivity of the multiphase flow <NUM> to the water detection threshold and determines that water is present based on the comparison. For example, the water detector <NUM> determines that the conductivity satisfies the water detection threshold based on the conductivity being greater (e.g., substantially greater) than the water detection threshold.

The water detector <NUM> compares a conductivity difference to the water detection threshold and determines that water is present based on the comparison. According to the present invention, the conductivity difference is a difference between a maximum conductivity (σmax) and a minimum conductivity (σmin) during a time period or window period (Δt). The water detector <NUM> determines that the conductivity difference satisfies the water detection threshold based on the conductivity difference being greater (e.g., substantially greater) than the water detection threshold. In some examples, the water detector <NUM> sets a flag (e.g., a water detection flag) when water is detected based on the conductivity, the conductivity difference, etc..

In the illustrated example of <FIG>, the water detection manager <NUM> includes the report generator <NUM> to generate a report or a log associated with the multiphase flow <NUM> of <FIG>. In some examples, the report generator <NUM> generates a report including one or more mixture parameters (e.g., the mixture parameters (<NUM>) - (<NUM>)) with respect to time or an oilfield operation. In some examples, the report generator <NUM> generates a report including a water detection determination result, a water detection occurrence frequency (e.g. a quantity of positive water detection flags per <NUM> time period), water salinity, etc., and/or a combination thereof. For example, the report can include an indication that water is detected or not detected for one or more time periods (e.g., measurement time periods). In some examples, the report generator <NUM> generates an alert based on a value of a mixture parameter and/or a water detection determination result. For example, the report generator <NUM> generates an alert (e.g., to flag the need to inject hydrate inhibitor, corrosion inhibitor, etc.) when water is detected in the multiphase flow <NUM>. For example, the alert can include an indication that water is detected or not detected, a water detection occurrence frequency, and/or the salinity of water in the multiphase flow <NUM>. In some examples, the report generator <NUM> transmits the report and/or the alert to another computing device communicatively coupled to the water detection manager <NUM> via the network <NUM>.

In some examples, the report generator <NUM> can set a WLR measured by a multiphase flowmeter (e.g., a gamma-ray based multiple phase flowmeter (MPFM)) to zero based on a no water detection result (e.g., no water detected) in the multiphase flow <NUM>. For example, the report generator <NUM> can set the WLR to zero to avoid and/or otherwise prevent a reporting of non-physical (e.g., negative) time-averaged WLR values to improve an accuracy in flow rate measurements of oil and gas phases made by the MPFM. For example, the report generator <NUM> generates and transmit an alert indicating that water is not detected in the multiphase flow <NUM> to a MPFM communicatively coupled to the network <NUM>. In response to receiving the alert, the MPFM or a control system communicatively coupled to the MPFM can set the WLR to zero. Alternatively, the MPFM may be communicatively coupled to the water detection manager <NUM> without the network <NUM> (e.g., the water detection manager is directly coupled to the MPFM).

In the illustrated example of <FIG>, the water detection manager <NUM> includes the database <NUM> to record data (e.g., EM data, mixture parameters, water detection determination results, water salinity, excitation frequencies of the EM sensor(s) <NUM>, <NUM>, etc.). The database <NUM> can be implemented by a volatile memory (e.g., a Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM), etc.) and/or a non-volatile memory (e.g., flash memory). The database <NUM> can additionally or alternatively be implemented by one or more double data rate (DDR) memories, such as DDR, DDR2, DDR3, mobile DDR (mDDR), etc. The database <NUM> can additionally or alternatively be implemented by one or more mass storage devices such as hard disk drive(s), compact disk drive(s) digital versatile disk drive(s), etc. While in the illustrated example the database <NUM> is illustrated as a single database, the database <NUM> can be implemented by any number and/or type(s) of databases. Furthermore, the data stored in the database <NUM> can be in any data format such as, for example, binary data, comma delimited data, tab delimited data, structured query language (SQL) structures, etc. In some examples, the database <NUM> can be cloud-based to enable synchronous retrieving and updating.

While an example manner of implementing the water detection manager <NUM> of <FIG> is illustrated in <FIG>, one or more of the elements, processes, and/or devices illustrated in <FIG> may be combined, divided, re-arranged, omitted, eliminated, and/or implemented in any other way. Further, the example collection engine <NUM>, the example measurement configurator <NUM>, the example parameter calculator <NUM>, the example water detector <NUM>, the example report generator <NUM>, the example database <NUM>, and/or, more generally, the example water detection manager <NUM> of <FIG> may be implemented by hardware, software, firmware, and/or any combination of hardware, software, and/or firmware. Thus, for example, any of the example collection engine <NUM>, the example measurement configurator <NUM>, the example parameter calculator <NUM>, the example water detector <NUM>, the example report generator <NUM>, the example database <NUM>, and/or, more generally, the example water detection manager <NUM> could be implemented by one or more analog or digital circuit(s), logic circuits, programmable processor(s), programmable controller(s), graphics processing unit(s) (GPU(s)), digital signal processor(s) (DSP(s)), application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)), field programmable gate array(s) (FPGA(s)), and/or field programmable logic device(s) (FPLD(s)). When reading any of the apparatus or system claims of this patent to cover a purely software and/or firmware implementation, at least one of the example collection engine <NUM>, the example measurement configurator <NUM>, the example parameter calculator <NUM>, the example water detector <NUM>, the example report generator <NUM>, and/or the example database <NUM> is/are hereby expressly defined to include a non-transitory computer readable storage device or storage disk such as a memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc., including the software and/or firmware. Further still, the example water detection manager <NUM> of <FIG> may include one or more elements, processes, and/or devices in addition to, or instead of, those illustrated in <FIG>, and/or may include more than one of any or all of the illustrated elements, processes, and devices. As used herein, the phrase "in communication," including variations thereof, encompasses direct communication and/or indirect communication through one or more intermediary components, and does not require direct physical (e.g., wired) communication and/or constant communication, but rather additionally includes selective communication at periodic intervals, scheduled intervals, aperiodic intervals, and/or onetime events.

<FIG> depicts an example graph <NUM> generated by the water detection manager <NUM> of <FIG> and/or <NUM> to implement the examples disclosed herein. In <FIG> (according to the present invention), the water detection manager <NUM> generates the graph <NUM> based on a maximum permittivity (εmax) and a permittivity difference (εmax - εmin) with respect to time. In <FIG>, the graph <NUM> is based on the multiphase flow <NUM> of <FIG> where the multiphase flow <NUM> is a wet-gas flow with a GVF of <NUM>% and with increasing WLR over time. In <FIG>, the water detection manager <NUM> detects the presence of water when water-volume fraction (WVF) (e.g., WVF = WLR * (<NUM>-GVF)) is increased from a WVF of <NUM> to <NUM> parts per million (ppm) (and higher), by determining one or more mixture parameters, comparing the one or more mixture parameters to a threshold, and determining that the one more mixture parameters satisfy the threshold based on the comparison.

In the illustrated example of <FIG>, the water detection manager <NUM> calculates mixture parameters including the maximum permittivity and the permittivity difference at a chosen or determined time interval (e.g., a determined relatively short time interval). For example, the water detection manager <NUM> can determine the mixture parameters every <NUM>, <NUM>, etc., based on raw EM data rapidly acquired at a data acquisition rate of <NUM> from the EM sensor(s) <NUM>, <NUM> of <FIG>. In <FIG>, the water detection manager <NUM> during a first example time period from <NUM>:<NUM> to <NUM>:<NUM> calculates values for the maximum permittivity and the permittivity difference and compares the values to an example water detection threshold <NUM>.

In <FIG>, the water detection threshold <NUM> is described below in Equation (<NUM>): <MAT> In the example of Equation (<NUM>) above, εoil represents the permittivity of the oil phase of the multiphase flow <NUM>, εgas represents the permittivity of the gas phase of the multiphase flow <NUM>, and δεnoise represents the permittivity noise. In <FIG>, the permittivity noise is set to <NUM> to account for an uncertainty in oil/gas permittivity values. Alternatively, the permittivity noise may be set to any other value. In other examples, the permittivity noise is much less than <NUM> when related to the measured mixture permittivity standard deviation εstd(Δt) induced by measurement noise of the EM sensor(s) <NUM>, <NUM> and/or EM electronics receiving the EM data from the EM sensor(s) <NUM>, <NUM> (e.g., the collection engine <NUM> of <FIG>). For example, measurement noise in the EM sensor(s) <NUM>, <NUM> and/or EM electronics can be determined based on the permittivity average and standard deviation values when performing static gas or static oil measurements.

In the illustrated example of <FIG>, the water detection manager <NUM> determines that no water is detected during the time period <NUM>:<NUM> to <NUM>:<NUM> based on the permittivity difference (εmax - εmin) not being greater than the water detection threshold <NUM>. In <FIG>, the water detection manager <NUM> determines that water is detected during the time periods of <NUM>:<NUM> to <NUM>:<NUM>, <NUM>:<NUM> to <NUM>:<NUM>, and <NUM>:<NUM> to <NUM>:<NUM> by determining that the permittivity difference is greater than the water detection threshold <NUM>. In some examples, the increasing permittivity difference (εmax - εmin) indicates an increase in the liquid WLR.

Flowcharts representative of example hardware logic, machine readable instructions, hardware implemented state machines, and/or any combination thereof for implementing the water detection manager <NUM> of <FIG> and/or <NUM> are shown in <FIG>. The machine readable instructions may be an executable program or portion of an executable program for execution by a computer processor such as the processor <NUM> shown in the example processor platform <NUM> discussed below in connection with <FIG>. The program may be embodied in software stored on a non-transitory computer readable storage medium such as a CD-ROM, a floppy disk, a hard drive, a DVD, a Blu-ray disk, or a memory associated with the processor <NUM>, but the entire program and/or parts thereof could alternatively be executed by a device other than the processor <NUM> and/or embodied in firmware or dedicated hardware. Further, although the example program is described with reference to the flowcharts illustrated in <FIG>, many other methods of implementing the example water detection manager <NUM> may alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined. Additionally or alternatively, any or all of the blocks may be implemented by one or more hardware circuits (e.g., discrete and/or integrated analog and/or digital circuitry, an FPGA, an ASIC, a comparator, an operational-amplifier (op-amp), a logic circuit, etc.) structured to perform the corresponding operation without executing software or firmware.

As mentioned above, the example processes of <FIG> may be implemented using executable instructions (e.g., computer and/or machine readable instructions) stored on a non-transitory computer and/or machine readable medium such as a hard disk drive, a flash memory, a read-only memory, a compact disk, a digital versatile disk, a cache, a random-access memory, and/or any other storage device or storage disk in which information is stored for any duration (e.g., for extended time periods, permanently, for brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the term non-transitory computer readable medium is expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media.

<FIG> depicts example source code <NUM> representative of example computer readable instructions that can be executed to implement the example water detection manager <NUM> of <FIG> and/or <NUM> that can be used to implement the examples disclosed herein. For example, the source code <NUM> can be used to implement the process of <FIG>. In the source code <NUM>, the water detection manager <NUM> executes an example function or process (int getWaterDetection) to determine whether water is detected in the multiphase flow <NUM> of <FIG>.

In the source code <NUM> of <FIG>, the water detection manager <NUM> makes water detection determination results immune to potentially small drifts in the multiphase flow measurement system <NUM> by comparing one or more mixture parameters to at least two different water detection thresholds. For example, the water detection manager <NUM> immunizes potential drifts in one or both EM sensors <NUM>, <NUM> of <FIG>, EM sensor electronics included in the water detection manager <NUM>, etc., by comparing the one or more mixture parameters to at least two different water detection thresholds as depicted in the source code <NUM>.

In the source code <NUM> of <FIG>, the water detection manager <NUM> compares a permittivity difference during a time window Δt (εmax(Δt) - εmin(Δt)) to a first water detection threshold ((εoil(p, T) - εgas(p, T)) + δεnoise) determined at the measured multiphase-flow pressure p and temperature T. For example, the water detector <NUM> of <FIG> can compare the permittivity difference to the first water threshold and determine that water is present in the multiphase flow <NUM> based on the comparison.

The water detection manager <NUM> uses the mixture permittivity maximum (εmax(Δt)) to capture a water-rich data point and uses the mixture permittivity minimum (εmin(Δt)) to capture a gas-rich data point for, in some examples, at least <NUM> data points rapidly acquired during the time window Δt. In the source code <NUM>, oil and gas permittivity pressure-volume-temperature (PVT) models are used to track the changes in the oil permittivity (εoil(p, T)) and the gas permittivity (εgas(p, T)) of the multiphase flow <NUM>. The PVT models are generated based on obtaining and/or otherwise determining the densities and chemical compositions of the oil and gas included in the multiphase flow <NUM>. For example, the densities and chemical compositions can be determined by performing gas chromatograph analysis of samples of oil and gas included in the multiphase flow <NUM>.

In the source code <NUM> of <FIG>, if the water detection manager <NUM> determines that the permittivity difference is greater than the first water detection threshold, then the water detection manager <NUM> sets the water detection flag (waterDetectionFlag) to true indicating that water is present in the multiphase flow <NUM>. If the water detection manager <NUM> determines that the permittivity difference is not greater than the first water detection threshold, then the water detection manager <NUM> compares the maximum permittivity during the time window (εmax(Δt)) to a second water detection threshold (εoil(p, T) + δεoil). In some examples, the uncertainty in the oil permittivity (δεoil) is chosen to include an absolute (RF electronics) baseline drift in the permittivity measurement (e.g., by choosing δεoil to be in a range of <NUM> to <NUM>). In the source code <NUM> of <FIG>, if the water detection manager <NUM> determines that the maximum permittivity is greater than the second water detection threshold, then the water detection manager <NUM> sets the water detection flag to true indicating that water is present in the multiphase flow <NUM>. If the water detection manager <NUM> determines that the maximum permittivity is not greater than the second water detection threshold, then the water detection manager <NUM> sets the water detection flag to false indicating that water is absent from and/or otherwise present in a negligible amount in the multiphase flow <NUM>. In response to setting the water detection flag, the source code <NUM> returns a value of the water detection flag. In some examples, the quantity of true water detection occurrences can be accumulated over a specified time duration (e.g., every <NUM>, every <NUM>, etc.) to calculate and/or otherwise determine a water detection occurrence frequency.

<FIG> is a flowchart representative of example machine readable instructions <NUM> that can be executed to implement the water detection manager <NUM> of <FIG> and/or <NUM> to detect a presence of water in the multiphase flow <NUM> of <FIG>. The machine readable instructions <NUM> begin at block <NUM>, at which the water detection manager <NUM> configures electromagnetic sensor(s). For example, the measurement configurator <NUM> of <FIG> can configure one or both EM sensors <NUM>, <NUM> of <FIG> to excite EM energy into the multiphase flow <NUM> at a specified RF/microwave frequency.

At block <NUM>, the water detection manager <NUM> obtains electromagnetic data associated with a multiphase flow. For example, the collection engine <NUM> of <FIG> can obtain EM data from one or both EM sensors <NUM>, <NUM> associated with the multiphase flow <NUM>.

At block <NUM>, the water detection manager <NUM> calculates mixture parameter(s) associated with the multiphase flow. For example, the parameter calculator <NUM> can calculate one or more of the mixture parameters (<NUM>) - (<NUM>) as described above.

At block <NUM>, the water detection manager <NUM> compares mixture parameter(s) to water detection threshold(s). For example (not according to the present invention), the water detector <NUM> compares the permittivity difference to the first water detection threshold as described above in connection with the source code <NUM> of <FIG>. In other examples, the water detector <NUM> compares the maximum permittivity to the second water detection threshold as described above in connection with the source code <NUM> of <FIG>.

At block <NUM>, the water detection manager <NUM> determines whether a water detection threshold has been satisfied. For example, the water detector <NUM> determines that the permittivity difference satisfies the first water detection threshold based on the difference. In such examples, the water detector <NUM> determines that the first water detection threshold is satisfied based on the permittivity difference being greater than the first water detection threshold.

If, at block <NUM>, the water detection manager <NUM> determines that the water detection threshold has not been satisfied, control proceeds to block <NUM> to set a water detection flag. For example, the water detector <NUM> can set the water detection flag to false indicating that water is not detected in the multiphase flow <NUM>. If, at block <NUM>, the water detection manager <NUM> determines that the water detection threshold has been satisfied, then, at block <NUM>, the water detection manager <NUM> detects water in the multiphase flow. For example, the water detector <NUM> determines that water is detected in the multiphase flow <NUM>.

In response to detecting water in the multiphase flow, the water detection manager <NUM> sets the water detection flag at block <NUM>. For example, the water detector <NUM> can set the water detection flag to true indicating that water is detected in the multiphase flow <NUM>. In response to setting the water detection flag at block <NUM>, the water detection manager <NUM> determines whether to continue monitoring the multiphase flow at block <NUM>. For example, the collection engine <NUM> can determine to continue obtaining EM data from the EM sensor(s) <NUM>, <NUM> associated with the multiphase flow <NUM>.

If, at block <NUM>, the water detection manager <NUM> determines to continue monitoring the multiphase flow, control returns to block <NUM> to obtain electromagnetic data associated with the multiphase flow. If, at block <NUM>, the water detection manager <NUM> determines not to continue monitoring the multiphase flow, then, at block <NUM>, the water detection manager <NUM> generates and transmits a report and/or an alert. For example, the report generator <NUM> can generate a report including the water detection determination result (e.g., a value of the water detection flag), one or more mixture parameters, the graph <NUM> of <FIG>, etc., and/or a combination thereof. In such examples, the report generator <NUM> generates an alert indicating whether water is detected in the multiphase flow <NUM>. In such examples, the report generator <NUM> can transmit the report and/or the alert to an external computing device via the network <NUM> of <FIG>. In such examples, a MPFM communicatively coupled to the network <NUM> can set a WLR used by the MPFM to calculate flow rate measurements of the multiphase flow <NUM> to zero when water is not detected for a relatively long duration (e.g. every <NUM>, every <NUM>, etc.) to improve an accuracy of the calculated measurements.

In response to generating and transmitting the report and/or the alert, the machine readable instructions <NUM> conclude. Alternatively, the machine readable instructions <NUM> can be executed using mixture parameters based on mixture conductivity data (e.g., σmin(Δt), σmax(Δt), etc.) when water with a conductivity value larger than a threshold is used (e.g., a threshold of <NUM>/m, <NUM>/m, <NUM>/m, etc.).

<FIG> is a block diagram of an example processor platform <NUM> structured to execute the instructions of <FIG> to implement the water detection manager <NUM> of <FIG> and/or <NUM>. The processor platform <NUM> can be, for example, a server, a personal computer, a workstation, a self-learning machine (e.g., a neural network), a mobile device (e.g., a cell phone, a smart phone, a tablet such as an iPad™), a personal digital assistant (PDA), an Internet appliance, a headset or other wearable device, or any other type of computing device.

For example, the processor <NUM> can be implemented by one or more integrated circuits, logic circuits, microprocessors, GPUs, DSPs, or controllers from any desired family or manufacturer. The hardware processor may be a semiconductor based (e.g., silicon based) device. In this example, the processor <NUM> implements the example collection engine <NUM>, the example measurement configurator <NUM>, the example parameter calculator <NUM>, the example water detector <NUM>, and the example report generator <NUM> of <FIG>.

The volatile memory <NUM> may be implemented by Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory (RDRAM®), and/or any other type of random access memory device.

The interface circuit <NUM> may be implemented by any type of interface standard, such as an Ethernet interface, a universal serial bus (USB), a Bluetooth® interface, a near field communication (NFC) interface, and/or a PCl express interface.

The input device(s) <NUM> can be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, a button, a mouse, a touchscreen, a track-pad, a trackball, an isopoint device, and/or a voice recognition system.

The output devices <NUM> can be implemented, for example, by display devices (e.g., a light emitting diode (LED), an organic light emitting diode (OLED), a liquid crystal display (LCD), a cathode ray tube display (CRT), an in-place switching (IPS) display, a touchscreen, etc.), a tactile output device, a printer, and/or speaker. The interface circuit <NUM> of the illustrated example, thus, typically includes a graphics driver card, a graphics driver chip, and/or a graphics driver processor.

The communication can be via, for example, an Ethernet connection, a digital subscriber line (DSL) connection, a telephone line connection, a coaxial cable system, a satellite system, a line-of-site wireless system, a cellular telephone system, etc. The network <NUM> implements the example network <NUM> of <FIG> and/or <NUM>.

The machine executable instructions <NUM> of <FIG> may be stored in the mass storage device <NUM>, in the volatile memory <NUM>, in the non-volatile memory <NUM>, and/or on a removable non-transitory computer readable storage medium such as a CD or DVD.

In the specification and appended claims: the terms "connect," "connection," "connected," "in connection with," and "connecting" are used to mean "in direct connection with" or "in connection with via one or more elements;" and the term "set" is used to mean "one element" or "more than one element. " Further, the terms "couple," "coupling," "coupled," "coupled together," and "coupled with" are used to mean "directly coupled together" or "coupled together via one or more elements. " As used herein, the terms "up" and "down," "upper" and "lower," "upwardly" and downwardly," "upstream" and "downstream;" "above" and "below;" and other like terms indicating relative positions above or below a given point or element are used in this description to more clearly describe some embodiments of the disclosure.

From the foregoing, it will be appreciated that example methods, apparatus, and systems have been disclosed that detect water in multiphase flows. The above-disclosed examples describe detecting the presence of water in a multiphase or a wet-gas flow stream by interpreting mixture parameters including mixture permittivity and/or mixture conductivity obtained at high data sampling or acquisition frequencies by one or more electromagnetic sensors. The above-disclosed examples improve an accuracy of flow rate measurements of individual phases of the multiphase flow by setting a WLR to zero when water is not detected in the multiphase flow. The above-disclosed examples also improve flow assurance and/or water processing facility planning of oilfield gas-oil production operations, by transmitting alert of the risks of hydrate formation (blockage) and/or corrosions in the flowline when water is detected in the multiphase flow. Alternatively, the above-disclosed methods and apparatus can be applicable to other electromagnetic measurement techniques, such as sensors based on (local) RF/microwave transmission measurement, (local) electrical impedance (e.g., capacitance, conductance, inductance, etc.) measurement, etc., and/or a combination thereof.

Claim 1:
An apparatus (<NUM>), comprising:
a conduit (<NUM>; <NUM>) including:
an inlet (<NUM>) to receive a multiphase flow (<NUM>); and
an electromagnetic sensor (<NUM>; <NUM>) coupled to a liquid-rich region of the conduit (<NUM>) to obtain a plurality of permittivity or conductivity measurements of the multiphase flow (<NUM>); and
a water detection manager (<NUM>) configured to determine that water is detected in the multiphase flow (<NUM>) based on the permittivity or the conductivity,
characterized in that the water detection manager (<NUM>) further includes:
a parameter calculator (<NUM>) configured to determine a maximum of the plurality of permittivity (εmax) or conductivity (σmax) measurements and a minimum of the plurality of permittivity (εmin) or conductivity (σmin) measurements, and a difference between the maximum permittivity and the minimum permittivity or a difference between the maximum conductivity and the minimum conductivity; and
a water detector (<NUM>) configured to compare the difference to a water detection threshold (<NUM>); and to determine that water is detected in the multiphase flow (<NUM>) based on the comparison.