Patent Publication Number: US-2022213785-A1

Title: Photoacoustic nanotracers

Description:
TECHNICAL FIELD 
     The present disclosure is directed to tracers for subsurface characterization. 
     BACKGROUND 
     Tracers are a practical tool to gather information about the subsurface fluid flow in hydrocarbon reservoirs. Typical inter-well tracer tests involve injecting and producing tracers from multiple wells to evaluate important parameters such as connectivity among wells, flow paths, fluid-fluid and fluid-rock interactions, and reservoir heterogeneity, among other properties of a hydrocarbon reservoir. For this purpose, passive (or conservative) tracers are the preferable choice. The most common passive tracers include radioactive, inorganic elements, alcohols, fluorescent molecules, and fluorinated benzoic acids, all bearing advantages and disadvantages. Within the oil industry, fluorinated benzoic acid tracers are the most popular. Fluorescent tracers, while available in the form of fluorescent molecules, have not been as popular in the oil and gas industry mainly due to their instability at reservoir conditions and significant retention while transporting through the reservoir. 
     SUMMARY 
     An embodiment described in examples herein provides a method for using a photoacoustic nanotracer to characterize a subsurface environment. The method includes forming a solution including a photoacoustic nanotracer, injecting the solution into the subsurface environment, and analyzing produced fluids for the photoacoustic nanotracer. A breakthrough curve is built based, at least in part, on the analysis. 
     Another embodiment described in some examples herein provides a system for characterizing a subsurface environment. The system includes, a pulsed laser, an acoustic detector, and a photoacoustic nanotracer including nanoparticles, wherein the pulsed laser irradiates produced fluids and, when a nanoparticle is in a beam from the pulsed laser, the acoustic detector detects an acoustic signal. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a schematic diagram of a method for using photoacoustic nanotracers to track flow between two wellbores in a subsurface environment, for example, in a reservoir layer. 
         FIGS. 2A-2C  are representative photoacoustic nanotracers that may be used for characterizing a subsurface environment. 
         FIG. 3  is a drawing of a photoacoustic detection system for identifying and quantitating photoacoustic nanotracers in produced fluids flowing from a wellbore. 
         FIG. 4  is a block diagram of a photoacoustic detection system used for the analysis of photoacoustic nanotracers in produced fluids from a wellbore. 
         FIG. 5  is a process flow diagram of a method for characterizing a subsurface environment using photoacoustic nanotracers. 
         FIG. 6  is a process flow diagram of a method for analyzing the produced fluids for tracers. 
     
    
    
     DETAILED DESCRIPTION 
     As described herein, novel photoacoustic nanotracers based on nanoparticles can be used to overcome disadvantages with current tracers. The photoacoustic effect is the formation of sound waves following light absorption in a material sample. This phenomenon can be exploited to create nanoparticles to be used as photoacoustic nanotracers that can be detected by a combination of an electromagnetic source, such as laser light, and one or more acoustic transducers. Among the advantages of nanoparticles as photoacoustic nanotracers is the capability to functionalize the surface to improve the stability in high salinity and temperature environments as well as to decrease the interaction with rock surface. 
     The photoacoustic nanotracers can be used for subsurface characterization. The invention is optimized for the use in hydrocarbon reservoirs. The tracers consist of nanoparticles that emit sound when excited by electromagnetic radiation of a certain frequency range, such as near infrared light. This phenomenon is known as the photoacoustic or optoacoustic effect. Exploiting this effect it is possible to engineer nanoparticles to function as photoacoustic nanotracers for inter-well studies of hydrocarbon reservoirs. The main advantage over conventional fluorobenzoic acid (FBA)-based tracers is a much simpler detection method that requires only a light source, e.g., a laser, with a narrow emission spectrum as the excitation source and acoustic transducers to perform the detection of the tracers. The photoacoustic nanotracers have a number of advantages over fluorescent tracers. For example, the photoacoustic nanotracers are not affected by photobleaching. Further, as the detection of the photoacoustic nanotracers is based on sound rather than light, the background fluorescence of aromatic compounds and other contaminants found in produced water does not interfere with the tracer detection. 
       FIG. 1  is a schematic diagram of a method  100  for using photoacoustic nanotracers to track flow between two wellbores  102  and  104  in a subsurface environment, for example, in a reservoir layer  106 . As shown in  FIG. 1 , the reservoir layer  106  is located in the subsurface environment between the surface  108  and a lower layer, such as a water table  110 . 
     The photoacoustic nanotracers  112  are mixed into a solution at the surface  108  and pumped from surface facilities  114  through an injection well  102  into the reservoir layer  106 . In this embodiment, the surface facilities  114  includes the mixing tanks for mixing the photoacoustic nanotracers  112  into an aqueous solvent and the pump for injecting the photoacoustic nanotracers  112  into the injection well  102 . 
     In the reservoir layer  106 , the photoacoustic nanotracers  112  flow through the pores of the rock of the reservoir layer  106  before reaching a production well  104 . The photoacoustic nanotracers  112  are then carried back to the surface  108 . 
     A production facility  116  at the surface  108  may include a detection system, for example, as described with respect to  FIG. 3 , to directly detect the photoacoustic nanotracers  112 . In some embodiments, the production well  104  will not have a high enough concentration of the photoacoustic nanotracers  112  for reliable detection by an online system. In these embodiments, samples of the production fluid may be taken to a laboratory for concentration of the fluids containing the photoacoustic nanotracers  112  or for direct separation of the photoacoustic nanotracers  112  from the production fluid. 
     Photoacoustic nanotracers  112  are promising for oil reservoir characterization for a number of reasons. The use of electromagnetic excitation is relatively simple. Further, the photoacoustic nanotracers  112  do not have interference from background fluorescence caused by aromatic compounds and contaminants in produced fluids. Further, as described with respect to  FIGS. 2A-2C , adjusting the size, shape, and materials of the nanoparticles can be used to provide multiple unique tracers that can be injected into the subsurface environment in a single mixture or through different wells and differentiated by the excitation wavelengths and emission frequencies, allowing multiplexing of the analysis. For example, different photoacoustic nanotracers may be used in different injection wells and identified from a single production well. The photoacoustic nanotracers  112  are also more stable than fluorescent tracers, decreasing the problem of photobleaching. 
       FIGS. 2A-2C  are representative photoacoustic nanotracers that may be used for characterizing a subsurface environment.  FIG. 2A  is a nanoparticle  202  that is used as a photoacoustic nanotracer in some embodiments. The nanoparticle  202  emits sound when excited by light or, in general, an electromagnetic source of a specific wavelength, for example, with a range of about 25 nm to 75 nm on each side of the peak absorbance. When the nanoparticle  202  is irradiated at the target wavelength, light is absorbed, which leads to a rise in temperature. The temperature increase generates a thermal expansion that increases the local pressure, leading to the formation of sound waves. To observe the photoacoustic effect, the light intensity has to vary over time, either in the form of modulated light or as a light pulse. The mechanism is explained by the formula shown in Equation 1. 
         p   0   =βΔT/k   (1)
 
     In equation 1, p 0  is the pressure increase, β is the thermal expansion coefficient, ΔT is the change in temperature and k is the isothermal compressibility of the nanoparticle. 
     Equation 1 suggests two approaches to magnify the pressure increase and, accordingly, the magnitude of emitted sound. For the instrument design, ΔT can be maximized by choosing the right excitation frequency and by increasing the intensity of the excitation source. For the nanoparticle  202  to function as photoacoustic nanotracers, materials with large β and small k values can be selected. 
     Furthermore, the nanoparticle  202  can be engineered to have a high cross-section area for efficient absorption. Nanoparticles are used as contrast agents in photoacoustic imaging for biological applications due to their high and stable signal and because their surface can be functionalized. Metallic nanoparticles are often used as photoacoustic contrast agents because of their high absorption cross section, which is a measure of the ability of the nanoparticle to absorb a photon of a specific wavelength and polarization. Further, gold and silver nanoparticles are commercially available as colloidal gold and colloidal silver. In addition, the synthesis of metallic particles of particular sizes is known in the art. 
     In various embodiments, the size and shape of the nanoparticle  202  can be modified to tune the absorption peak for multiplexing. In general, the absorption maximum of gold nanoparticles shifts toward the red spectrum as size increases. In addition, changing the shape of the nanoparticle changes their absorption properties. For example, spherical and irregular-shaped gold nanoparticles of the same average size exhibit absorption maximum at different wavelengths due to an anisotropic distribution of the surface electron layers in the latter. 
     In some embodiments, the nanoparticle  202  is plasmonic gold and silver nanoparticles with sizes ranging from 20 to 150 nm or from 400 to 900 nm. As used herein, plasmonic indicates that the gold and silver nanoparticles may function in clusters that interact with surrounding molecules to change the absorbance characteristics. The size of the nanoparticle  202  affects the peak absorption of the nanoparticle. In some embodiments, multiple unique photoacoustic nanotracers are made from the same material by changing the size. Accordingly, in these embodiments, different light sources are used, each with a wavelength that corresponds to the peak absorption wavelength of a specific photoacoustic nanotracer. Accordingly, measurements can be multiplexed using this technique. 
     The main criteria for the size of the nanoparticle  202  is the pore-throat size in the subsurface environment. Generally, the nanoparticle  202  is selected to be at least 5-15 times smaller than the smallest pore-throat it has to go through. The size may also control the frequency used to excite the nanoparticle  202 . Accordingly, the frequency of the laser is adjusted for the size of the nanoparticle  202  so that the center frequency of the laser corresponds to the absorption maximum of the nanoparticle. 
     In some embodiments, the nanoparticle  202  is an upconverting nanoparticle (UCNPs). UCNPs may be good photoacoustic nanotracers as they have narrow excitation/emission profiles. UCNPs are typically based on phosphors (e.g. NaYF 4 ) doped with ytterbium (Yb 3+ ), erbium (Er 3+ ) and terbium (Tb 3+ ). Copper and copper sulfide have also been used. In some embodiments, copper sulfide is used, allowing the absorption peak to be tuned. In some embodiments, nanoparticle  202  is formed from single-walled carbon nanotubes (SWCNs). 
     In some embodiments, as shown in  FIG. 2B , a coated nanoparticle  204  is used. For example, the coating  206  may be a silica layer, silica-coated iron oxide nanoparticles, or silica-coated gold nanoparticles. The advantage of silica-coated nanoparticles is that their surface chemistry can be modified to allow for additional functionalization. The material choice will depend on the number of unique tracers required, the reservoir rock type and other reservoir parameters such as salinity, temperature and pH. 
     In some embodiments, the coating is performed by the Stöber process, for example, used to prepare silica-coated iron oxide nanoparticles. In the Stöber process, a reaction mixture consisting of water, ethanol and a catalyst is seeded with iron oxide particles. A silica precursor monomer is added. The hydrolysis and condensation of the precursor monomer results in the deposition of a silica layer on the iron oxide particles. 
     In some embodiments, as shown with respect to  FIG. 2C , a surface functionalized nanoparticle  208  is used. The surface functionalized nanoparticle  208  is functionalized with an absorbed species  210  surfactants or polymers that are adsorbed. For example, surfactants or polymers that are terminated with thiol groups, thiocarboxylic acid, or other moieties comprising sulfur, may be used to functionalize gold nanoparticles. For example, the surface coating may include anionic surfactants, such as SDS, cationic surfactants, such as CTAB, or dextran, among others. Other moieties may be selected depending on the metal chosen. 
       FIG. 3  is a drawing of a photoacoustic detection system  300  for identifying and quantitating photoacoustic nanotracers  302  in produced fluids flowing from a wellbore  304 . It can be noted that the photoacoustic detection system  300  shown in  FIG. 3  is generally used when the concentration of the photoacoustic nanotracers  302  is high enough to be detected by an online system in a direct flow. In other embodiments, the produced fluids are sampled and concentrated for off-line analysis. In some embodiments, the photoacoustic nanotracers can be detected at a concentration of parts-per-billion (ppb), for example, depending on the excitation frequency, the pulse energy, heat capacity of the fluid, or the thermal expansion coefficient, among other factors. 
     In this embodiment, the produced fluids including the photoacoustic nanotracers  302  flow from the wellbore  304  through a sampling tubular  306 . The sampling tubular  306  may be a section of piping that includes an optical port  308  to allow a beam  310  of electromagnetic (EM) radiation, such as a laser beam, to be introduced into the production fluids from an excitation source  312 . 
     The most common excitation range for photoacoustic techniques ranges between 680 and 1100 nm, which falls within the near infrared (NIR) region. Further, NIR is the preferred option for biological applications because it has greater penetration in biological systems than wavelengths corresponding to the visible region. Accordingly, in some embodiments, the excitation source  312  is a neodymium/yttrium-aluminum-garnet (Nd/YAG) laser. Higher power lasers may be used to increase signal amplitude. The wavelength of the laser is selected to match the peak absorbance of the nanoparticle. For example, and Nd/YAG laser may be frequency doubled to obtain a 532 nm beam. Further, other wavelengths may be obtained by frequency doubling, a frequency comb, secondary laser excitation, laser detuning, or other techniques. 
     Further, for photoacoustic nanotracer detection and quantification in hydrocarbon systems, other types of EM radiation may be used, since the depth of penetration may be higher in a hydrocarbon solvent. In some embodiments, the excitation source  312  may use EM radiation that includes radio frequencies, microwave frequencies, and x-ray frequencies to excite the photoacoustic nanotracers  302 . In some embodiments, EM radiation in a second NIR window (termed NIR II), which ranges between 1000 and 1500 nm, is used as less absorption and scattering may occur. In some embodiments, the beam  310  includes pulses of EM radiation, for example, in the nanosecond range. In some embodiments, the beam  310  is a millisecond-long coded continuous wave (CW) source. In some embodiments, the power of the excitation source  312  is around 1 W, 5 W, 10 W, or higher, although higher or lower powers may be used, depending on whether the photoacoustic nanotracers  302  have a substantial response to the EM radiation. In some embodiments, the excitation sources are at much higher powers, such as 500 W, 1 kW, 5 kW, or higher, allowing the detection of much smaller amounts of particles. 
     One or more acoustic detectors  314  may be installed in contact with the sampling tubular  306 , or pass through ports on the sampling tubular  306  to allow direct contact with the produced fluids. When the photoacoustic nanotracers  302  are excited by the beam  310 , they will produce acoustic waves  316  having a pattern that is similar to the pattern of the EM radiation used for excitation, e.g., pulse separation, etc. The acoustic waves  316  are detected by the acoustic detectors  314 . In some embodiments, the acoustic detectors  314  are ultrasonic transducers, for example, in an array of multiple acoustic detectors  314 . Ultrasonic transducers that may be used in embodiments are commercially available. In an embodiment, the acoustic detectors  314  include a 64-element ultrasonic transducer array from Ultrasonix (now Analogic), for example, with a central frequency of 3.5 MHz, 80% bandwidth at −6 dB and 0.254 mm pitch. The specifications of the acoustic detectors  314  are selected based on the sound waves generated by each kind of photoacoustic nanotracer  302 . In another embodiment, the transducer array is an SU-107 model from Sonic Concepts of Bothell, Wash., USA. 
     Information from the acoustic detectors  314  may be used to identify and quantitate the different photoacoustic nanotracers  302 . In some embodiments, the frequency and amplitude of the acoustic waves  316  are analyzed and compared to calibration curves to estimate the concentration of the different photoacoustic nanotracers  302 . 
     The photoacoustic detection system  300  may include a controller  318  used to control the excitation source  312  and monitors the signals from the acoustic detectors  314 . For example, control lines  320  from the controller  318  to the excitation source  312  may be used to start, stop, or adjust the pulse or emission frequency of the excitation source  312 . The control lines  320  may also include power lines to power the excitation source  312 . Sensor lines  322  may couple the controller  318  to the one or more acoustic detectors  314 . A communications line  324  may couple the controller  318  to external devices, such as a distributed control system (DCS), cloud communication system, an intranet, or the Internet. The communications line  324  may be used to provide alerts to users to inform them that photoacoustic nanotracers  302  have been detected in the produced fluids. The controller  318  is described further with respect to  FIG. 4 . 
     After flowing through the sampling tubular  306 , the produced fluids flow into a production line  326 . The production line  326  carries the produced fluids to downstream equipment, such as water separation units, gas separation units, distillation units, pipelines, and the like. 
       FIG. 4  is a block diagram of a photoacoustic detection system  400  used for the analysis of photoacoustic nanotracers  302  in produced fluids from a wellbore  304 . Like numbered items are as described with respect to  FIG. 3 . It can be noted that the photoacoustic detection system  400  described with respect to  FIG. 4  may be used in an off-line analysis in which the acoustic waves  316  are omitted from a nanoparticle in a concentrated sample of produced fluids. The photoacoustic detection system  400  includes the controller  318 , acoustic detectors  314 , and the excitation source  312 . In some embodiments, the controller  318  is a microcontroller, for example, mounted in an enclosure at the wellbore  304 . In other embodiments, the controller  318  is a virtual controller running on a processor in a DCS, on a virtual processor in a cloud server, or using other real or virtual processors. 
     The controller  318  includes a processor  402 . The processor  402  may be a microprocessor, a multi-core processor, a multithreaded processor, an ultra-low-voltage processor, an embedded processor, or a virtual processor. In some embodiments, the processor  402  may be part of a system-on-a-chip (SoC) in which the processor  402  and the other components of the controller  318  are formed into a single integrated electronics package. In various embodiments, the processor  402  may include processors from Intel® Corporation of Santa Clara, Calif., USA, from Advanced Micro Devices, Inc. (AMD) of Sunnyvale, Calif., USA, or from ARM Holdings, LTD., Of Cambridge, England. Any number of other processors from other suppliers may also be used. 
     The processor  402  may communicate with other components of the controller  402  over a bus  404 . The bus  404  may include any number of technologies, such as industry standard architecture (ISA), extended ISA (EISA), peripheral component interconnect (PCI), peripheral component interconnect extended (PCIx), PCI express (PCIe), or any number of other technologies. The bus  404  may be a proprietary bus, for example, used in an SoC based system. Other bus technologies may be used, in addition to, or instead of, the technologies above. 
     The bus  404  may couple the processor  402  to a memory  406 . In some embodiments, such as in analytical instrument controllers, PLCs, and other process control units, the memory  406  is integrated with a data store  408  used for long-term storage of programs and data. The memory  406  include any number of volatile and nonvolatile memory devices, such as volatile random-access memory (RAM), static random-access memory (SRAM), flash memory, and the like. In smaller devices, such as PLCs, the memory  406  may include registers associated with the processor itself. The data store  408  is used for the persistent storage of information, such as data, applications, operating systems, and so forth. The data store  408  may be a nonvolatile RAM, a solid-state disk drive, or a flash drive, among others. In some embodiments, the data store  408  will include a hard disk drive, such as a micro hard disk drive, a regular hard disk drive, or an array of hard disk drives, for example, associated with a DCS or a cloud server. 
     The bus  404  couples the processor  402  to a sensor interface  410 . The sensor interface  410  connects the controller  402  to the acoustic detectors  314 . In some embodiments, the sensor interface  410  is a bank of high-speed, analog-to-digital converters (ADCs) used to convert analog signals from the acoustic detectors  314  into digital signals. In some embodiments, the sensor interface  410  is an I2C bus, a serial peripheral interface (SPI) bus, or a Fieldbus®, and the like. As described herein, the acoustic detectors  314  may include ultrasonic detector arrays, micro-electromechanical systems (MEMS) detectors, surface acoustic wave (SAW) detectors, quartz crystal microbalance (QCM) detectors, and film bulk acoustic resonators (FBARs), among others. 
     The bus  404  couples the processor  402  to a control interface  412  that is used to couple the controller  318  to a power supply/controller  414  for the excitation source  312 . In some embodiments, the control interface  412  is a simple relay, MOSFET power controller, or other device to activate the power supply/controller  414  to start the excitation source  312 . In some embodiments, the controller interface  412  is a serial bus, such as a USB, serial peripheral interface (SPI) bus, or a Fieldbus®, and the like, used to provide more complex parameters to the power supply/controller  414 , such as pulse rate, excitation frequency, and the like. 
     The bus  404  couples the processor  402  to a network interface controller (NIC)  416 . The NIC  416  couples the controller  318  to external systems  418 , such as external control systems used for the production systems, including a DCS, PLC, a logging computer, or a SCADA transmitter, intranets, or the Internet, among others. For off-line systems used for analyzing concentrated production fluids, the external systems  418  may include laboratory computers, research networks, intranets, or the Internet, among others. 
     The data store  408  includes blocks of stored instructions that, when executed, direct the processor  402  to implement the functions of the controller  318 . In some embodiments, the data store  408  includes a block  420  of instructions to direct the processor  402  to control the excitation source  312 . In various embodiments this is performed, for example, by activating a relay in the controller interface to activate the power supply/controller  414 , activating a MOSFET in the controller interface to activate the power supply/controller  414 , or by sending instructions over a bus to a control unit in the power supply/controller  414 . In some embodiments, the block  420  of instructions may direct the processor to communicate parameters to the power supply/controller  414  for the excitation source  312 , such as pulse rate, excitation frequency, and the like. 
     In some embodiments, the data store  408  includes a block  422  of instructions to direct the processor to monitor the acoustic detectors  314 , for example, through the sensor interface  410 . The block  422  of instructions may direct the processor to initiate monitoring after the excitation source  312  has been started. 
     In some embodiments, the data store  408  includes a block  424  of instructions to direct the processor  402  to analyze the frequency response from the acoustic detectors  314  to identify the type of photoacoustic nanotracer detected. This may be used, for example, when an ensemble of different photoacoustic nanotracers, such as from different injection wells, is expected. 
     In some embodiments, the data store  408  includes a block  426  of instructions to direct the processor  402  to quantify each of the different types of photoacoustic nanotracers present in the produced fluids. The block  426  of instructions may direct the processor  402  to count the individual number of nanoparticles detected of each type of photoacoustic nanotracer. In some embodiments, the block  426  of instructions may direct the processor  402  to compare the amplitude of the acoustic signal to a calibration curve. 
     In some embodiments, the data store  408  includes a block  428  of instructions to direct the processor  402  to calculate a breakthrough time, for example, as a flow from an injection well reaches a production well. 
       FIG. 5  is a process flow diagram of a method  500  for characterizing a subsurface environment using photoacoustic nanotracers. The method begins at block  502 , with the creation of a solution that includes one or more types of photoacoustic nanotracers, as described herein. The solution may be water-based or oil-based depending on the material being tracked. 
     At block  504 , the solution is injected into a subsurface environment through an injector well of interest. In some applications, different photoacoustic nanotracers are injected through different injector wells. 
     At block  506 , the produced fluids at the producer well of interest are monitored for the presence of photoacoustic nanotracers. As described herein, in some embodiments, this is performed by an online detector. 
     In some embodiments, the produced fluids are monitored by performing sampling followed by concentration of the sample of produced fluids followed by off-line analysis. In some embodiments, the produced fluids are treated to separate any photoacoustic nanotracers that may be present from the produced fluids. In both of these embodiments, off-line analysis may be used to determine the types and amounts of photoacoustic nanotracers present. 
     At block  508 , the results of the analyses, online or off-line, are used to build a breakthrough curve to determine the timing of flow between the injection well in the production well. 
       FIG. 6  is a process flow diagram of a method  600  for analyzing the produced fluids for tracers. In this example, a sample is collected at block  506  for the analysis. The method begins at block  602 , with the concentration of the produced fluids. In some embodiments, the photoacoustic nanotracers are separated from the produced fluids before the analysis. It may be noted that in some embodiments, the produced fluids are used without further concentration, for example, when an online detector is impractical or uneconomical. 
     At block  604 , the sample is irradiated with a pulsed or time-changing EM signal, for example, at the peak absorbance frequency of a photoacoustic nanotracer. At block  606 , and acoustic detector is used to record the sound generated by the sample. At block  608 , the sound is analyzed for amplitude and frequency. For example, the frequency may be used to identify the type of photoacoustic nanotracer detected. At block  610 , calibration curves are used to determine the concentration of the photoacoustic nanotracers identified based, at least in part, on the measured signal from the acoustic detectors. The method  600  as described from block  604  to block  610  may also be used for the online detection system. 
     An embodiment described herein provides a method for using a photoacoustic nanotracer to characterize a subsurface environment. The method includes forming a solution including a photoacoustic nanotracer, injecting the solution into the subsurface environment, and analyzing produced fluids for the photoacoustic nanotracer. A breakthrough curve is built based, at least in part, on the analysis. 
     In an aspect, the solution is formed to include a number of photoacoustic nanotracers. In an aspect, the solution is injected into the subsurface environment through an injection well. In an aspect, the produced fluids are removed from the subsurface environment through a production well. 
     In an aspect, the method includes irradiating the produced fluids with a time changing electromagnetic signal at an absorbance frequency for the photoacoustic nanotracer, and using an acoustic transducer to record sound generated by the produced fluids. In an aspect, the produced fluids are irradiated in a section of a production line. 
     In an aspect, the produced fluids are concentrated before irradiating the produced fluids. In an aspect, the photoacoustic nanotracer is separated from the produced fluids. 
     In an aspect, the sound is analyzed for amplitude and frequency. In an aspect, the method includes determining a concentration of the photoacoustic nanotracer based, at least in part, on the analyzed sound. In an aspect, the method includes identifying the photoacoustic nanotracer in a number of photoacoustic nanotracers by the frequency. 
     In an aspect, the method includes using a nanoparticle as the photoacoustic nanotracer. In an aspect, the method includes functionalizing a surface of the nanoparticle with a surfactant. In an aspect, the method includes forming a coating over a surface of the nanoparticle. 
     Another embodiment described herein provides a system for characterizing a subsurface environment. The system includes, a pulsed laser, an acoustic detector, and a photoacoustic nanotracer including nanoparticles, wherein the pulsed laser irradiates produced fluids and, when a nanoparticle is in a beam from the pulsed laser, the acoustic detector detects an acoustic signal. 
     In an aspect, the system includes an online sampling system. In the online sampling system, the pulsed laser is configured to irradiate the produced fluids in a tubular from a wellbore, wherein the acoustic detector is configured to detect the acoustic signal from the nanoparticles in the tubular. 
     In an aspect, the system includes a controller coupled to the pulsed laser and the acoustic detector. The controller includes a processor and a storage system. The storage system includes code configured to direct the processor to monitor the acoustic detector, and send a message when the acoustic detector detects the acoustic signal. 
     In an aspect, the storage system includes code configured to direct the processor to activate a power supply to the laser. 
     In an aspect, the system includes a second acoustic detector, wherein the second acoustic detector is configured to detect the acoustic signals at a different frequency from the acoustic detector. 
     In an aspect, the storage system includes code configured to direct the processor to identify different types of photoacoustic nanotracers based, at least in part, on the different frequency. In an aspect, the storage system includes code configured to direct the processor to count nanoparticles detected by acoustic signals. In an aspect, the storage system includes code configured to direct the processor to calculate a breakthrough curve. 
     Other implementations are also within the scope of the following claims.