Natural gas is sampled and produced throughout the lifespan of a petroleum field. Gas composition and isotope data are critical inputs in the exploration and field development, such as gas show identification, petroleum system analysis, fluid characterization, and production monitoring. On-site gas analysis is usually conducted within a mud gas unit, which is operationally unavailable after drilling. Gas samples need to be taken from the field and shipped back to the laboratory for gas chromatography and isotoperatio mass spectrometry analyses. Results are usually without sufficient resolution to fully characterize the heterogeneity and dynamics of fluids within the reservoir and the production system. In addition, it often takes a considerable time to obtain the results using the traditional method. A novel QEPAS (quartz-enhanced photoacoustic spectroscopy) sensor system was developed to move gas composition analyses to field for quasi-real-time characterization and monitoring. With respect to previously reported QEPAS prototypes for trace gas detection, the new system realized measuring concentrations of methane (C1), ethane (C2), and propane (C3) in gas phase within the percentage range that is typically encountered in natural gas samples from oil and gas fields. A gas mixing enclosure was used to dilute the natural gas-like mixtures in nitrogen gas (N 2 ) to avoid the saturation of QEPAS signals. An iterative analysis based on multilinear regression of QEPAS spectra was developed to filter out the influence of gas matrix variation from multiple hydrocarbon components. The advance in simultaneous measuring hydrocarbon gases and expanded linearity range of QEPAS, with previously reported detection of H 2 S, CO 2 , and gas isotopes ( 12 CO 2 / 13 CO 2 , 13 CH 4 / 12 CH 4 ), opens a way to use the advanced sensing technology for in situ and real-time gas detection and chemical analysis in the oil industry.
Polymer degradation during Enhanced Oil Recovery (EOR) can have large impact on recovery rates during polymer flooding. In the field, few practical solutions exist to perform quality control/assurance (QA/QC) on EOR polymer fluids at surface and no solutions exist for measurements downhole. Here, we present the development of a miniaturized sensor that can be used to detect the onset of polymer degradation by measuring the viscous properties of EOR polymer fluids. The device was tested on samples collected from a polymer flooding operation. We describe its integration into wellsite portable systems and into an untethered logging tool for cost-effective routine measurements downhole. The sensors are based on millimeter-sized piezoelectric tuning fork resonators. The viscosity and density of the fluids was measured from the energy dissipation and the resonant frequency obtained from their vibrational spectra. The devices were specially designed for use in high-salinity polymer fluids. They were tested and validated on samples collected from a single well polymer flood trial. A miniaturized electrical measurement platform was then designed for use at surface in the field and for use in a compact untethered logging tool for quick and inexpensive deployment downhole. The devices were initially calibrated in the laboratory and then tested on samples collected from the field. These two field-collected solutions were used to preflush the formation before injecting surfactant-polymer solution and as a polymer taper to drive the injected surfactant-polymer solution, respectively. The obtained viscosity values correlated very well with those obtained from standard laboratory measurements. Therefore, the changes in viscosity due to reduction in the molecular weight of the polymer, as measured with the miniature devices, can be used to assess whether degradation has taken place. A miniaturized electrical measurement platform was then tested in comparable polymer fluids for use in the field and obtained comparable results. The platforms described here provide a simple, cost-effective, and user-friendly platform for the detection of polymer degradation in the field, thus providing valuable information in real-time during costly polymer flooding operations.
Natural gas is sampled or produced throughout the lifespan of a field, including geochemical surface survey, mud gas logging, formation and well testing, and production. Detecting and measuring gas is a common practice in many upstream operations, providing gas composition and isotope data for multiple purposes, such as gas show, petroleum system analysis, fluid characterization, and production monitoring. Onsite gas analysis is usually conducted within a mud gas unit, which is operationally unavailable after drilling. Gas samples need be taken from the field and shipped back to laboratory for gas chromatography and isotope-ratio mass spectrometry analyses. Results take a considerable time and lack the resolution needed to fully characterize the heterogeneity and dynamics of fluids within the reservoir. We are developing and testing advanced sensing technology to move gas composition and isotope analyses to field for near real-time and onsite fluid characterization and monitoring. We have developed a novel QEPAS (quartz-enhanced photoacoustic spectroscopy) sensor system, employing a single interband cascade laser, to measure concentrations of methane (C1), ethane (C2), and propane (C3) in gas phase. The quartz fork detection module, laser driver, and interface are integrated as a small sensing box. The sensor, sample preparation enclosures and a computer are mounted in a rack as a gas analyzer prototype for the bench testing for oil industry application. Software is designed for monitoring sample preparation, collecting data, calibration and continuous reporting sample pressure and concentration data. The sensor achieved an ultimate detection limit of 90 ppb (parts per billion), 7 ppb and 3 ppm (parts per million) for C1, C2, and C3, respectively, for one second integration time. The detection limit for C2 made a record for QEPAS technique, and measuring C3 added a new capability to the technique. However, the linearity of the QEPAS sensing were previously reported in the range of 0 to 1000 ppm, which is mainly for trace gas detection. In the study, the prototype was separately tested on standard C1, C2, and C3 with different concentrations diluted in dry nitrogen (N2). Good linearity was obtained for all single components and the ranges of linearity were expanded to their typical concentrations (per cent, %) in natural gas samples from oil and gas fields. The testing on the C1-C2 mixtures confirms that accurate C1 and C2 concentrations in % level can be achieved by the prototype. The testing results on C1-C2-C3 mixtures demonstrate the capability of simultaneous detection of three hydrocarbon components and the probability to determine their precise concentrations by QEPAS sensing. This advancement of simultaneous measuring C1, C2 and C3 concentrations, with previously demonstrated capability for hydrogen sulfide (H2S) and carbon dioxide (CO2) and potential to analyze carbon isotopes (13C/12C), promotes QEPAS as a prominent optical technology for gas detection and chemical analysis. The capability of measuring multiple gas components and the advantages in small sensor size, high sensitivity, quick analysis, and continuous sensing (monitoring) open the way to use QEPAS technique for in-situ and real-time gas sensing in oil industry. The iterations of QEPAS sensor might be applied in geochemical survey, on-site fluid characterization, time-lapse monitoring of production, and gas linkage detection in the oil industry.
With the increase of automation and process control requirements, a good real-time grasp of the drilling fluid rheology has repeatedly been flagged as a key requirement. Unfortunately, drilling fluid rheology is still mostly measured manually and reported only twice a day. Fluctuations in fluid composition and rheology due to wellbore/fluid interaction and temperature/shear/solids effects are generally missed. This paper describes the field implementation and testing of an inline-design pipe rheometer that operates autonomously to continuously measure rheological properties of the drilling fluid in the rig's mud tanks. This data can be used to monitor the stability or indicate changes in these drilling fluids. The system employs a progressive cavity pump to draw drilling fluid from the mud tank and propel it, at varying controlled rates, through two different sizes of pipe. Differential pressure transducers are used to measure the pressure drop over a fixed length in each size of pipe, and this data, along with flow rate, is used to calculate fluid viscosity. All components are installed within a standard ISO shipping container for ease of transport and deployment at the wellsite. It is positioned next to the mud tanks where it continuously samples and measures the drilling fluid. Field test results of the system are presented. The system was operated autonomously on location in Saudi Arabia for an entire drill stage (3.5 days) of 5-7/8" section for gas drilling. In this section, oil based mud was used and measured by the system. The system was controlled remotely via WiFi connection. During the test period, manual viscosity and density measurements were also taken using the Fann-35 and mud balance methods. Subsequent comparison shows excellent agreement between the automated and manual measurements.
Travel time measurements from an acoustic array interrogating a fluid within the cross-section of a pipe include systematic errors: from mispositioning of array elements, group delays from the transceiver circuits at each element, and acoustic propagation effects between transmitter/receiver pairs. An enhanced calibration model is described which includes the influence of these error sources, and a recursive least squares solution is applied to find calibration travel-time corrections that minimize systematic errors. This enhanced calibration model is applied in-situ to an acoustic transducer array, resulting in increased accuracy and precision of acoustic travel-time measurements. Tomographic images of fluid velocities are derived from these travel-time measurements. The fluid velocities are mapped to known velocities of individual fluid phases, resulting in tomographic images of multiphase flows.
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