GRC Transactions, Vol. 39, 2015

1079

A New Technique and Sensor for Determining Steam Quality Along a Wellbore

Robert Kerr, Brian D. Gleason, Adam Olzick, and Bill Denzel

Scientific Drilling International

KeywordsHigh temperature, steam quality, density, densitometer, pressure, geothermal technique, tuning fork, high temperature transducer, cased hole services, steam injection, steam, prototype, high sensitivity, high resolution, steam quality sensor

ABSTRACT

Current downhole steam quality measurement techniques involve post processing of production logs. These logs are created by recording sensor measurement samples at points along the wellbore including temperature, pressure, and mass or volumetric flow rates using a spinner-type flowmeter. Since steam expands when travelling up a wellbore due to decreasing hydrostatic pressure, the quantification of inflow steam parameters utilizing this technique can be difficult to interpret. This paper presents a new technique for measuring steam quality along a wellbore that utilizes a new high temperature densitometer sensor combined with corresponding temperature or pressure readings. The technique has the benefit of providing a direct measurement of steam quality, thereby eliminating post processing of the production logs and reducing errors during the interpretation. To better understand the benefits of this new densitometer-based approach, this paper discusses existing approaches and presents several alternate techniques that were researched early on in the project. This paper also discusses the theory of the new measurement technique, as well as some preliminary accuracy estimations, their empirical verification, and materials research that was required to develop the new sensor.

Introduction

Steam quality, Q, is an important parameter to measure in geothermal wells. Given a two phase sample of water, it is defined as the mass of the vapor divided by the total mass as shown in Eq. 1.

Q =mvapor

mliquid +mvapor (1)

When combined with temperature or pressure, the steam quality allows the heat energy contained in a sample of wet steam to be computed. In geothermal wells, wet steam may be produced from multiple inflow points along the wellbore. The collective flow and energy content of these inflows are used at the surface to generate power. Some inflow points can be of lower steam quality, thereby diluting the overall value of the produced steam. Identifying the steam quality of all inflow points along a wellbore enables operators to better understand and manage their producing wells.

Survey of Various ApproachesExisting Techniques

The current production log analysis technique for evaluating steam quality is based on the calculation of flow velocity and fluid holdups (the proportion of water in the steam) along the wellbore. Fluid velocity is usually determined from the

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rate of rotation of an impellor, while the fluid holdup is derived from the fluid density along the wellbore. In steam wells, the water at certain depths starts to vaporize into a wet steam. With further heat input or changes in pressure, the wet steam turns into a dry or higher quality steam. The density change from wet steam to dry steam is very small compared to typical oil wells. In practice steam quality is easy to determine between liquid water and 20% steam quality because the density change is from 0.8g/cc to 0.15g/cc. However, between 20% and 100% steam quality the density changes from 0.15g/cc to 0.04g/cc. To measure steam quality between 20% and 100%, a resolution of around 0.005g/cc or greater is required.

In wells above 350°F there are few sensors that can survive. A pressure gradient can be used, but if the well is highly deviated or if the well is unstable then the results will be noisy and unable to achieve the required resolution. This technique must also be corrected for friction effects, which can be a significant source of error.

Possible Alternate Methods and TechnologiesIn a previous SPE conference paper, technologies that could make multi-phase flow measurements were previewed

due to the significance of locating water entries in a producing gas well (Jongkittinarukorn 2011). A number of alternate techniques for measurement of multi-phase flow or steam quality are discussed below (Shouman 1981).

Sonic Measurement. This technique uses the speed of sound. The equations typically used require 100% steam quality and not useable when gas mixtures or water vapor are present. This technique may have some merit, but it is necessary to experimentally measure the relationship between steam density and the speed of sound for it to be viable.

Microware Measurement. Another way to measure steam quality makes use of microwaves. Microwaves are sensitive to the dielectric properties of the material it passes through. In this technique, the dielectric constant or relative permittivity of the medium is measured to determine steam quality. The relative permittivity is a dimensionless number that quantifies a material’s ability to resist an electric field compared to a vacuum. The relative permittivity of water at 100°C at atmospheric pressure is approximately 56 (Uematsu 1980), whereas the permittivity at 100% steam quality is 1.012. In the steam quality range of 50% to 100% the permittivity values vary from 1.080 to 1.012 at 100°C, respectively. The permittivity of steam and water decreases as the temperature increases.

This particular technique has been used to measure steam quality in a steam line at a generator plant. It uses an interferometer that measures the differential path length between two transmission lines to determine the change in per-mittivity of the steam as the quality varies (Jean 2007). The sensors are placed in the steam line and the frequency of the source is adjusted so that a null condition is measured at the output. The permittivity is derived from the frequency at which the source is operated. The frequency ranges from 10.346 GHz for 100% steam quality to 10.275 GHz for 50% steam quality. Experimental data was acquired at the Turbomachinery Laboratory at Texas A&M University. The A&M steam system produced accurate steam quality from 50% to 100% (Jean 2007). This data was used to calibrate the instru-ment. This technique works well in a steam line with pure water, but it may not be suitable for a geothermal well due to the presence of chloride in the water. Because salt water is electrically conductive and could be present in a wellbore, it may also cause electrical shorting between the transmitters.

Optical Measurement. This technique uses an optical measurement to determine steam quality. Infrared light has been used to measure the moisture content of air (Partin 2006). Water vapor and liquid water have strong rotational and vibrational modes which are strong absorbers of middle and near infrared signals. This technique uses two beams, one wavelength that is strongly absorbed by water and another wavelength that is not. The second beam is used as a reference to correct for scattering effects. The source consists of five broadband LED’s which span the spectrum and contain strong absorption and transmission bands. The wavelengths were centered at 1.0, 1.2, 1.55, 1.9, and 2.2 microns. The experi-mental setup contained a test chamber which ran from 95 -100% steam quality. The researchers also made an independent measurement of the steam quality with a calorimeter. When the steam quality changed, shown by dips in the calorimeter temperature, large changes in the optical signal were observed.

Nuclear Fluid Density. This technique uses a chemical nuclear source with a gamma detector. Higher density flu-ids attenuate the gamma rays reaching the detector. Increased accuracy is currently needed when compared to a standard nuclear fluid identification module, but the source cannot be moved closer due to resulting decreased sample volume and sensitivity reduction. An acceptable resolution is theoretically possible with longer sample periods, but there are additional difficulties with this technique because the electronics and detector need to be flasked, resulting in the effective sample chamber introducing undesirable effects.

Tuning Fork Density. Scientific Drilling has a tuning fork density sensor that works well in the oil and gas industry (Scientific Drilling 2014). It was designed to replace a nuclear fluid density tool, thereby allowing an operator to avoid the use of a chemical radioactive source. Results from a downhole well where nuclear, pressure, tuning fork, and pressure gradient derived densities shows that the tuning fork density sensor has better than 0.01g/cc repeatability and resolution (Figure 1). Based on that and the fact that the sensor could be packaged to fit a downhole tool, we believe the primary difficulty in adapt-ing this technology to the high temperature geothermal market would be whether the sensor could be made to work at 305°C. On review of the various technology options, this was considered the most promising for further research and development.

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Theoretical Foundations of the Densitometer-Based Approach

In a geothermal well-bore, water exists in one of three states – liquid, vapor (dry steam), or a two phase liquid-vapor mixture known as wet steam. Figure 2 shows a tem-perature-entropy diagram for water. Lines of constant specific volume, which is the inverse of density, are shown in green. Lines of constant pressure are shown in blue. Note that in the two phase liquid-vapor region, temperature and pressure are dependent.

As previously discussed, steam quality, Q, is defined as the mass of the vapor divided by the total mass as shown in Eq. 1. Referencing Figure 2, lines of constant steam quality are shown in red. At 100% steam quality the mixture consists entirely of water vapor or gas. Conversely, at 0% steam quality the mixture consists entirely of liquid. For wet steam, given a temperature (or pres-sure) and a density (inverse of specific volume), one can uniquely determine the steam quality. Graphically, steam quality is determined by where the horizontal bar of a given temperature meets the green line of a given density measurement, which intersects with the red line of the corresponding quality reading. This relationship is unique for a given temperature and density and can be derived symbolically from basic thermodynamic relations.

The total volume of a mixture, V, is the sum of the volumes of the liquid and the vapor phases,

V =Vliquid +Vvapor (2)

To obtain a relationship for the average specific volume, v, the equation above is divided by the total mass of the mixture, m,

v = Vm=Vliquidm

+Vvaporm (3)

In a two-phase mixture, the liquid phase is a saturated liquid and the vapor phase is a saturated vapor, so Vliquid = mliquidv f and Vvapor = mvaporvg , where vf and vg are the specific volumes for the saturated liquid and vapor phases. Upon substitution we obtain,

v =mliquidm

⎛⎝⎜

⎞⎠⎟v f +

mvapor

m⎛⎝⎜

⎞⎠⎟vg (4)

Recall that the steam quality, Q, is Q =mvaporm

and can also be rearranged as mliquidm

= 1−Q. Substitution then leads to the following useful relationship for specific volume,

v = 1−Q( )v f +Qvg = v f +Q vg − v f( ) (5)

Noting that the specific volumes are the inverse of the densities, this equation can be rearranged as,

Figure 1. Fluid density sensor comparison log showing five different types of density measurement techniques, from left to right, dielectric capacitance sensors with two types of electrodes, a tuning fork density sensor, a nuclear fluid density sensor, and a pressure gradient density measurement.

Figure 2. Temperature-entropy diagram for water showing the two-phase water vapor region where, x, steam quality, varies from 0-100%. (X=0.0-1.0).

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ρ =ρgρ f

ρg +Q ρ f − ρg( ) (6)

Furthermore, this equation can be rearranged to solve for the steam quality, Q, solely in terms of average density, ρ, and the saturated liquid and vapor phase densities, ρl and ρg , which are well known and are exclusively functions of temperature or pressure. To compute steam quality, this equation can be implemented directly in the downhole electron-ics or within the surface system software to be applied in real-time with wireline data or applied post job to data stored in memory.

Q =ρgρ f

ρ ρ f − ρg( ) −ρg

ρ f − ρg (7)

Note that a useful approximation is obtained if the liquid density ρf is always much larger than the vapor density ρg ,

Q =ρgρ

(8)

Although the above approximation is not needed when computing steam quality, it does provide some insight be-cause it reveals that the steam quality is approximately equal to the ratio of the vapor density ρg and the average density ρ.

Theory of Operation for the Vibrating Tuning Fork Densitometer

The tuning fork densitometer is composed of two coupled mechani-cal resonator tines as shown in Figure 3.

When placed in a liquid, gas, or multi-phase mixture, the resonance frequency and damping factor of the system are changed due to the inter-action of the vibrating tines with the fluid. This system is approximately described by the simple model of a damped harmonic oscillator, where m is the inertia (mass of the fork tine plus the mass of the interacting fluid), F is the applied force, v is a damping constant related to viscosity, and k is the spring constant.

m !!x = F − v !x − kx (9)

As the vibrating tines interact with the fluid, an additional virtual mass is added to the system. When coupled with the fluid viscosity effects, the result is a change in the tines’ resonance frequency and damping characteristics. In general, the change in resonance frequency of the tines is inversely proportional to the change in density (denser fluid = more added mass = lower resonance frequency). The tuning fork sensor has a higher resonance frequency in air than it does when immersed in water.

A high temperature transducer, which is an integral part of the sensor assembly, applies a force to the system, caus-ing the tines to vibrate. The sensor’s electronics control the transducer’s drive frequency such that a desired relationship relative to a resonance frequency is maintained regardless of the properties of the fluid that the sensor is immersed in. The electronics measure that frequency and temperature and then convert it into a calibrated density measurement. For wet steam applications, further processing according to Eq. 7 can be implemented to convert the density and temperature measurements into steam quality. Note that the tuning fork densitometers are calibrated over different temperature and density ranges to ensure accurate readings regardless of the measurement conditions and to reduce any inaccuracies due to mathematical mis-modeling of the relationships between parameters.

Theoretical Evaluation and Experimental Verification of Sensor Accuracy, Sensitivity, and Repeatability

The density range required to accurately measure steam quality is substantially smaller than what is normally measured in typical downhole oil and gas density measurement applications. It requires nearly an order of magnitude improvement in resolution from the density sensor. Assuming that the performance of the existing sensor translates to the higher temperatures required for geothermal operations, we used the existing sensor’s accuracy to model the anticipated performance under the new conditions. The results from the model were deemed acceptable (Figure 4).

To verify these modeled results, we created a calibration test fixture that allowed for safe and easy simultaneous testing of three tuning fork sensors at various densities (Figure 5). Using the ideal gas law, various steam densities were achieved by increasing or decreasing the pressure of high purity argon gas inside a pressure vessel that was held nominally at room temperature. Based on product requirements, we limited our testing to steam qualities in the range of 50 to 95% at 305°C.

Figure 3. Tuning fork densitometer showing two coupled mechanical resonators or tines.

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Figure 6 shows the raw and nor-malized resonance frequencies obtained from the testing over the density range of interest. Variations in mechanical build tolerances result in the initial resonance frequency variations shown in the raw frequency plot. Once calibrated, the reso-nance frequency data from all three of the tuning forks overlay on top of each other as shown in the normalized plot. The data follows a simple trend that can be mathematically modeled and used to correct sensor errors, thereby enabling a high resolution measurement capable of measuring densities encountered in a geothermal or steam injec-tion wellbore. After applying the calibration curves and testing several additional steam quality densities in the test apparatus, the results show that the steam quality errors were generally less than 1% over the full tested measurement range (Figure 7).

Figure 4. Modeled Steam Quality Sensor Accuracies Based on Existing Sensor Accuracy Limits.

Figure 5. Argon gas test fixture used to empirically verify modelled results (right) and a graph showing the required argon pressures that were required to simulate 50-100% steam quality at 305°C (left).

Figure 6. Raw (left) and normalized (right) sensor resonance frequencies obtained using the argon gas test fixture over various steam qualities at 305°C.

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Materials Research for High Temperature Densitometer Sensor

As described earlier, the tuning fork den-sitometer sensor utilizes a transducer to apply a force to the tines, which causes them to vibrate. Unfortunately, a typical commercial transducer will not operate properly at the temperatures seen in a geothermal well. To enable the sensor to operate in the high temperatures encountered in geothermal applications, custom transducers using proprietary high temperature materials were fabricated. Testing of prototype trans-ducers in the first quarter of 2015 confirmed their ability to operate the tuning fork sensor at 305°C. Additional ongoing testing is focused on understanding how temperature cycling and long term exposure to elevated temperatures affects sensor performance and reliability.

Conclusions

After evaluation of various technologies and methods of steam quality measurement, we conclude that the tuning fork densitometer sensor shows the greatest promise. A theoretical model of the tuning fork sensor was created to ensure that the oil and gas industry version of the tuning fork sensor had the accuracy, sensitivity, and repeatability to function in a steam environment. After validation of this model, we were able to conclude that the sensor had the capability of measuring steam quality at pressures and temperatures seen in a geothermal or steam injection well. To verify the theoretical model, we performed an argon gas test on three tuning fork sensors. Through this argon gas test we determined that the current tuning fork sensor has sufficient resolution to decipher extremely small changes in steam quality at 305°C. However, to enable Scientific Drilling International’s tuning fork densitometer sensor to operate in geothermal and steam injection environments a new transducer with high temperature proprietary materials had to be developed. We are also in the process of developing analysis software that will display the energy inflows at each zone and the total energy along the wellbore.

A complete prototype steam quality measurement tool is expected to be phased into the commercialization stage by the end of 2015. Early in 2016 we anticipate pilot testing of a small number of tools in a geothermal well.

Acknowledgements

Tom Burnett and Bob Moore at Scientific Drilling International were contributing researchers on this technology. Parts of Figure 2 were generated courtesy of Markus Schweiss under the Creative Commons Attribution-Share Alike 3.0 Unported license.

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dx.doi.org/10.1109/TIM.2007.913821.Jongkittinarukorn, K. and Kerr, R. 2011. Flow Model Selection for Production Logging Interpretation of Gas Wells. Presented at the SPE Annual

Technical Conference and Exhibition 2011, Denver, 30 October- 2 November. SPE-145579. http://dx.doi.org/10.2118/145579-MS.Partin, J.K. and Davidson, J.R. 2006. Development of Optical Technologies for Monitoring Moisture and Particulate in Geothermal Steam. Idaho

National Laboratory INL/EXT-06-11705.Scientific Drilling. 2014. Case History: Real-time Flow Logging System Delivers Efficient & Cost Effective Results. Resources, December 2014,

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Figure 7. Sensor measurement error spread from the argon gas test was generally less than ±1% across 50-100% steam quality at 305°C.