Appendix B

Anonymized Committee Responses to Charge Questions

1. Were the objectives of the study clearly defined? If not, what are your recommendations for improving the description of this study’s objectives?

• Objectives can be more elaborate. Specific objectives can be reported with steps involved.
• The objective statement is relatively short. It does not clearly outline the actual goal. Perhaps the study’s objectives and the overall expectation the review committee had, were not perfectly aligned.
• According to the authors of the report, the objective was to describe their initial model development approach for the project, generate an experimental set of data on a laboratory scale that could be a source of target information for comparison against model predictions, and then elaborate on the comparison. Their main points to be conveyed were with regard to reproducing the spray experimental results found for water and n-heptane. The second objective was to demonstrate a method to define overall combustion efficiency based upon experiments with a crude. Only a single crude was examined in this part of the work.
• It is not clear if the objective of the study is to develop an “Engineering” model (CFD-Code), that is tested and validated, and can be used by the industry, or if it is basically a preliminary study that helps to identify the issues involved in modeling wellhead fire scenarios. Perhaps it should be stated explicitly by the sponsoring agency (BSEE), and the authors of the study that it is a preliminary work and it will be improved further in the future. To the authors’ credit, they seem to have identified all the physics that one can think of and incorporated them into their code to varying degrees of accuracy, and they also point out where further research is needed.
• The scaling effects for comparison of laboratory results and the practical problem are not clearly discussed. How is the laboratory scale relevant? The confidence level of the computational results should be explained.
• “The objective of this program is to develop and validate computational fluid dynamic models for predicting of wellhead burn efficiency. This requires a detailed understanding of the fundamental gas and liquid fluid mechanics; droplet formation, convection, and evaporation; and the spray combustion behavior of crude oil relevant to wellhead conditions.” page 73 of agenda book

2. Were the assumptions regarding wellhead conditions and two-phase wellbore flow (including film thickness and instability, liquid entrainment, and droplet diameter and its influence on wellhead ejection behavior) adequately characterized? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• There is a very good discussion of wellhead spray combustion scenario at earlier sections. However, the authors of the report did not clearly justify their choices of the submodels, the values of their assumptions or cited adequate references. Some of the description may appear at times simplistic.
• Few assumptions on selection of properties are specified. In the absence of detailed correlations for property estimation, these assumptions are fine. Assumption of flow behavior is in equilibrium and fully developed is made. Also, for lower velocity flows formation of pools or fountains than well-atomized sprays is assumed and annular-mist flow behaviour is planned to be modelled. Modelling

focus is on film thickness, entrainment, and droplet diameter. These should be fine considering the complexity of the problem and validation data.

• The flow within the reservoir is described, but there is no evidence that indeed these flow regimes exist. Authors assume annular-mist flow behavior for the sake of brevity and applicability as these sprays probably atomize well. However, the pools or fountains emerging from lower speed flows may not burn well at all and may be affecting the efficiency of the wellhead oil-burning. Authors have reviewed the literature well and several correlations from literature are being used for film thickness, liquid entrainment, and droplet diameters. It was difficult for the reviewer to know if these correlations are valid for the regimes under consideration. While these correlations for Weber numbers may be valid for the bench scale simulations, it is unclear if they would be applicable for the actual well-head.
• Most of the assumptions are described clearly in the report. However, the reviewer has a concern that, in some cases, clear justifications behind the assumptions are not stated. For example, the choice of heptane as the primary fuel has not been justified in the report. During Q/A session, such justifications were discussed. Perhaps, the authors should add them in the report as well.
• Methods have been demonstrated for the scale of the laboratory experiments conducted on water, n-heptane as fluids. It is likely that this is sufficient in terms of the objectives that were suggested by the authors themselves, which was to be an initiating study rather than a more developed demonstration of results, with an indication of what remains to be progressed to yield a predictive result. A wide range of issues remains to be evaluated in this reviewer’s opinion and there is no discussion of follow on work and its relevance to proofing methodologies. The scale extrapolation of results remains to tested, and the effects of oil/gas/water fraction of the discharge for even steady-state conditions remain to be evaluated.
• The worst-case discharge (WCD) model from Hilcorp is proprietary (per Hilcorp report, Appendix G not provided). Thus, it is difficult to know details of all data (https://spe.widen.net/s/2vjhlrwgrj/spe-174705-tr) , flow correlations and uncertainty ranges of the parameters used in the Hilcorp WCD model. The choice of modeling methods will affect output from these models which are input into the study at hand. That being said, the Hilcorp report includes some reservoir rock and fluid properties (section 4), and well design (section 8) amongst other data that can be used along with analog data and dynamic data as available, to build an independent WCD model to verify output or to cross-validate WCD output amongst different wellbore flow modeling methods to help characterize the wellhead conditions, and determine best method to do so given the problem at hand. At the very least impact of different wellbore models or flow regimes can be included.
• The theory is based on the behavior of an isolated isothermal droplet without consideration of transient droplet heating, shear effects and internal circulation, and group combustion of droplets.
• Strength: Droplet characterization, measured temperature profiles, qualitative agreement between predicted and measured temperatures. Weaknesses: Lack of gas speed measurements, which are essential for validation, discrepancies between predicted and measured temperatures and inadequate discussions about them, the report does not provide data on the computed droplet velocities and how they (and the model that they are based on) compare to the measure ones. Hence, the Lagrangian droplet model is not validated.
• Yes, the justification for the assumptions regarding the wellbore flow (annular liquid film, with fully developed gas phase flow in the center of the wellbore is well described and is based on data and correlations developed in the literature for wellbore flow. The authors acknowledge the assumptions regarding wellbore conditions and that conditions will change as a function of time. The annular flow assumption and corresponding wall film thickness appear valid for the conditions of the Liberty 90 day WCD conditions.

3.1 Was the physical model for multi-phase flow adequately developed to capture the liquid droplet phase and the gas-phase flow field? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• Modeling the problem of interest is inherently difficult because of its multiphysics nature. The submodel elements for gas phase (turbulence and combustion), liquid/droplet dynamics, radiation and soot may have been validated independently. However, it is not clear how they perform when coupled like this. There is no discussion of the inherent uncertainty of the combined model. There is limited discussion of the choice or validity of the submodels within the context of the problem of interest. The simplistic nature of these models leaves many constants to either be determined or tweaked to adjust the model predicts to experiments or observations.
• Eulerian Lagrangian formulation is used to model the liquid and gas phases. This is standard practice for large scale applications like the one considered in this study. RANS is used to model the gas phase, while LES would be more accurate, it would also be more expensive. Progress variable approach was used with appropriate closure terms to model the turbulent flame, which is a reasonable approach. Authors could consider performing some higher-fidelity LES to further improve the predictive capability of the simulations to train/improve the RANS modeling approach.
• Strengths: Most of the physical processes have been captured using several sub-models. The model can be computed with reasonable computational cost. Multiphase models are reasonably well tackled. Weakness: The model is primarily developed and validated with lab-scale and medium scale burning. Full-scale wellhead burning may not be accurately captured with the present model. The entrainment model is questionable for wellhead conditions. Omission: In the modeling section, the authors introduced physics-based models to capture various multiphase combustion processes. But, in many instances, they resorted to correlations based on previous studies. The involved multiscale physics is indeed complicated and difficult to formulate. Such complexity justifies the correlation-based models. However, it is not clear why specific values for model constants were selected. For example, on Page 23 (just before Eq. 33), the authors have taken B0=0.61. Was 0.61 taken from a reference? More importantly, it is also not clear if the values will be different for wellhead conditions. Similar is also true for d_P, F, and \beta concerning Eq. 36 on page 26. Errors: Perhaps a detailed uncertainty analysis is needed to assess the “safety limits” if the model is used for wellhead burning.
• The selection of n-heptane as the single component surrogate fuel for crude oil may be inaccurate in terms of predictions of preferential vaporization, and the resulting gas phase flow field and mixture formation.
• There is concern on the part of this reviewer as to whether the effects of surface tension, viscosity, and volatile range covered by actual crudes are well represented in terms of effects on breakup and atomization of the boundary layer pipe flow. The effects of these parameters along with gas/oil fraction of the crude as well as water content remain to be thoroughly envisioned through the current initial experiments.
• The liquid-phase behavior is basically an input parameter to the computations, and semi-empirical correlations are used to estimate them. A rigorous modeling of the liquid phase is lacking.
• Applicability of RANS based modeling to a multiphase jet needs to be justified. Yet, the model is simple enough, allowing multiple tests and fast outcomes.

3.2 Were the soot and radiation models adequately characterized? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• If the size and height of the wellhead jet flame is not represented well by the n-heptane surrogate, and the soot characteristics of n-heptane are different than from crude oil this can affect the radiative energy blockage, i.e. the radiant flux by the core gases which can affect the fuel mass consumption rate.

• First, the experiments with n-heptane as the fuel do not well characterize the magnitude of soot yields expected from the lower boiling range of components in crudes and especially those of aromatic structure. Single species experiments with toluene or with mixtures of low boiling point aromatics available from the commercial solvent industry would yield much higher sooting propensity, hence more radiative effects in terms of experimental observations to test radiation effects on burnout efficiency and modeling predictions. Moreover, crudes contain significant fractions of species with boiling points at atmospheric pressure well above 600 C, and that fraction varies substantially by crude source. Those fractions chemically crack in the liquid phase prior to vaporization from spray droplets, eventually yielding cenospheric coke particulates. The particulate mass and number densities will not likely be predicted well for crude conditions by considering only gas-phase sooting contributions, hence not well representing the radiative effects on crude combustion as a function of crude properties. The latter issues may have been viewed as something to be examined in follow on work, but no mention of its likely scale of contribution to model uncertainties is discussed. The more critical issue is that even the gas phase sooting effects were not well tested by experiments involving only n-heptane.
• Even in the simplest of laminar flames, a one-step soot formation model is unlikely to provide a reasonable representation of soot volume fraction and radiation effects. The conditions being modeled here are highly complex. Soot formation will be influenced by turbulence. In addition, droplet formation and evaporation may have a significant impact on soot formation and optical characteristics. At least some attempt should be made to address potential coupling between soot formation/radiation and turbulence, droplet formation/evaporation, and internal mixing of soot and semi-volatile droplets. In addition, there should be some way to validate this part of the model. If nothing else, there should be consistency between the representation of the radiation effects in the model with the emissivity model used in the soot-temperature measurement analysis in which the particles are assumed to be in the Rayleigh regime with an emissivity proportional to 1/λ.

3.3 Were Lagrangian droplet dynamics and thermophysics adequately incorporated into the model? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• Usual assumption and standard correlations are used in Lagrangian model. The model’s capability to simulate denser particle regimes has to be made clear, as EL model is often used for coarser particle laden flows.
• Relevant droplet dynamics are represented through the Lagrangian formulation and sub-models for evaporation, break-up, collisions and coalescence, etc. A single component formulation is assumed for the liquid phase, which in my opinion is not justified. Thermophysical characteristics of a single component will vary significantly from the actual crudes at the well-head. If the actual crude composition was available, it would have been useful to use a surrogate formulation based on the crude composition. The authors have chosen n-heptane since it is one of the components of the crude, but perhaps it is too light to represent crude and hence the sooting characteristics will not be accurate as well.
• In the governing equation for droplet velocity (Newton’s law of motion) as well as in the gas-phase equations there is no gravitational (buoyancy) term. One would expect buoyancy to slow the droplet motion in the vertical direction. It is not clear to me why that term is omitted here. For small flames (bench-top), and at high flow rates momentum controls the flow, however, in large scale flames buoyancy will play a critical role in establishing the flow field. Also in the bench-top experiments, a fairly high co-flow surrounding the main fuel-injection tube is used, which prevents buoyant entrainment of ambient air. The report tries to capture the evaporative behavior of a typical crude oil by choosing a single pure n-alkane fuel (n-heptane) as a surrogate. The sooting characteristics, and the thermophysical properties of n-heptane is considerably different for n-heptane compared to crude oil. Other phenomena, such as preferential evaporation and swelling need to be

incorporated in the future work. The “d-square” type single- component evaporation model is certainly inadequate for crude oil evaporation. The authors do state that they are planning to model a typical crude oil at a later stage.

• Again, transient heating of droplet, internal circulation, and group combustion were not considered.
• Strength: Attempt to include thermal and dynamic effects. Weakness: Adequacy of the drag model is questionable. The model was not validated or compared to data.
• An Eulerian Lagrangian approach was used for the gas and droplets, which is fine. The soot and droplet models (and others) include the relevant formation and oxidation mechanisms; however, the models are semi-empirical and were not developed or tested for oil well fires, so there is likely a high level of uncertainty. The models are adequately described or referenced; however, the applicability is not always well documented, e.g., the droplet breakup model was developed for flow in a pipe. Is it appropriate for Liberty oil and gas conditions? The combination of several semi-empirical models without a sensitivity analysis to understand the impact of the modeling approaches and input parameters is a significant weakness.

4. Does the droplet injection model adequately simulate realistic diameters and velocities of two-phase, high-speed flows that would occur during a wellhead blowout event? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• A simplified droplet injection model is used that takes care of droplet stripping and liquid-sheet breakup through correlations. Secondary breakup, droplet dynamics and deformations are not included due to the complexities. For the gross data modelled, these should be fine.
• The experiments and simulations were performed under significantly scaled down conditions. It is unclear if the droplet diameters and velocities considered under the lab-scale flames will mimic the actual well-head. Depending of the Weber numbers in the actual well-head, droplets may be in different break-up regimes than the ones considered in the lab scale tests. In the absence of experimental data inside the pipe and injection plane, the authors have made certain assumptions, and have clearly stated them. In the reviewers’ humble opinion, the authors have been very transparent in their approach and assumptions. Without sufficient data about the pipe flow and injection conditions, it is very difficult to initiate the spray flame simulations using the droplet injection model. KH instability is assumed to be the primary aerodynamic break-up mechanism. However, there could be significant cross-flow/gust of air which may result in different dominant breakup mechanisms such as those encountered in gas turbines (jet in cross flows).
• Strengths: Most of the physical models are in place. Weakness: The breakup models are questionable under the wellhead condition. In particular, the authors commented that the compressibility effect would be vital in certain flow conditions. The used KH-type breakup model may not be sufficient enough under such conditions. Omission: The rationale behind some of the model constants was not discussed. (e.g. see between Eqns 37 and 38 in page 27). Detailed simulation of intermediate-scale burning has not been done. Errors: Perhaps a detailed uncertainty analysis is needed to assess the “safety limits” if the model is used for wellhead burning.
• The drop injection model may not adequately simulate particle mean diameter and size distributions in a two-phase high speed flow. In a wellhead blowout event, there may exist cross flow winds that would modify the entrainment patterns and droplet size distributions.
• My opinion is that extrapolating the experimental efforts to the scale of the actual problem of interest remains an unknown at this point, especially considering the limited information presently acquired on the effects of crude surface tension viscosity, gas/oil fraction, and boiling range of components, particularly the heavier component fractions and their aromaticity.
• Here, reference is assumed to be on the initial size and velocity, not the predicted values in time.

• The authors attempt to introduce a realistic phenomenological model of the multiphase. The adequacy of this model needs to be validated/proven. The relevance to the full scale system is questionable
• This part of the model seems largely conjecture, which is understandable considering the lack of information to support developing a droplet injection process for a well bore blowout. I did not see a lot of data comparing the model results to wellhead blowout events.

5. Does the validation process capture the controlling physical properties to a sufficient level of accuracy including transport and boundary conditions at the bench- and intermediate-scales for both gas-phase and two-phase turbulent spray? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• The experiments provide a very nice database for further model development and a starting point to implement a more realistic choice of fuels that mimic the performance of crude oil. However, and given the above comments, it is not clear to the reviewer based on the limited validation data whether the models are adequate or not. Also, it would have been helpful to read information about the scope of the CFD predictions. Are they designed to predict the experiments or the actual wellhead burning scenarios within prescribed error bar or simply predict trends (e.g. what happens if the discharge rate is increased or decreased)? Addressing this question could have provided a better appreciation of the value of the CFD modeling and whether higher fidelity modeling approaches are needed.
• I think that the sequence of the experiments that were described was logical. The authors first investigated as gas phase flame (GPF) with a propane jet in a vitiated co-flow provided by a lean premixed hydrogen/air flame. They then progressed to a two-phase jet with “bench-scale spray flame” (BSSF) with a gas phase flow of ethane and liquid injection of heptane. The BSSF flow conditions were configured such that the system was in the annular flow regime. Finally they investigated an intermediate scale experiment (ISE) with gas flows of methane and propane and a liquid flow of crude oil. The progression from very fundamental flames to a flame with crude oil injection has the advantages of providing validation data for the models that are being developed and gaining confidence both in the modeling and the experimental techniques on the GPF and BSSF systems before moving on to an investigation of the ISE.
• The validation of bench scale study in terms of comparison of measured and predicted temperatures has been reported. There are discrepancies, however, the overall agreement seems to be satisfactory. Intermediate scale results from experiments are shown, but not an explicit comparison with prediction. For several measurements made, few more parametric validations could have been done.
• While the reviewer is not an expert, the authors have done a good job in coming up with a detailed experimental campaign with well-established boundary conditions in the experiments.
• The quantitative validation between experimental and simulation is somewhat limited. Only temperature fields were validated, which show reasonably good agreement.
• See my above discussions with regard to the limited range properties and choice of a low shooting propensity liquid fuel for evaluating radiation loss contributions to combustion burnout efficiency.
• The bench-scale experiment uses a very small injection tube (less than 1 mm) and it is clearly not a model for capturing oil well blowout scenarios. However, it can be used to validate general turbulent-jet flames with dispersed droplets – a problem reasonably well understood. The intermediate-scale experiment still has a fuel injection tube diameter of 0.25”, still small compared to real wellhead configuration and scaling of these results to wellhead fires are difficult, particularly with regard to radiation.
• This is not my expertise, but I had a related question. I am unclear on how the scaling from the WCD model was done to bench and intermediate scale initial and boundary conditions.

• The validation process neglects soot abundance measurements, which is very important for validating the soot formation model and soot radiation effects.
• Weaknesses: 1. Lack of gas velocity measurements prevents validation of the basic RANS tool. 2. Limited resolution of the back-illuminating imaging system. 3. The report does not provide a comparison between the PDA and imaging results. 4. There is no comparison between the modeled and measured droplet behavior.
• Heptane properties were used for the liquid phase of the model. However, oil is a blend of heavier and lighter components. I expect this assumption to be quite impactful on the droplet dynamics, e.g., evaporation rates, droplet diameter, etc. The assumption of a single component liquid is likely a weakness of the model, but it is unclear on how significant the impact is without sensitivity analysis. How was the stagnation pressure selected for the exit plane of the well head? The rationale for the progression from the lab scale modeling and experiments to the actual well bore conditions is not well explained or justified. What scaling relationships are assumed?

6. Were the phase doppler anemometry and diffuse back-light illumination imaging diagnostic methods (6.1 and 6.2 below) for the droplet behavior measurements appropriately designed, clearly described, and adequate to capture droplet behavior for the Gas Phase and Two-Phase Spray Flame? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

6.1 Phase Doppler Anemometry

• The phase Doppler anemometry (PDA) experimental system was described well and the experiments appear to have been performed in a very competent manner. The system included two PDA systems, one for measuring velocities in the x- and z- directions (this system used 660-nm and 785-nm beams) , and one for measuring velocities in the y-direction (this system used 632-nm beams. The system used information from all three beam crossings to determine droplet size. This is a more sophisticated system than a PDA system I have used which has only two wavelengths.
• More details on uncertainty analysis should be useful.
• The technique utilized, experimental arrangements etc. are adequately described. A couple of comments regarding the interpretation of the data: (1) Page 61(under Fig. 32), it was commented that outside r=+/-4mm, no droplets were observed. However, measurements were provided beyond this radius e.g. Fig. 32). (2) Page 62 last sentence: Authors stated, “..so there is likely a slight increase in ethane density….”. One should note that a change in spray cone angle will also change the mean velocity.
• Where it can be implemented, PDA is adequate. However, it has a limited range.
• The diagnostic methods were well described.

6.2 Diffuse Back-Illumination Imaging

• The diffuse back-illumination imaging (DBI) results were crucial for qualitative understanding of the structure of the liquid flow in the two-phase system and for proper interpretation of the PDA measurements. The type of information obtained from the DBI measurements as shown in Figs. 38 and 39 provides a great deal of insight into the flow structure. The reason why PDA measurements could not be performed near the tube exit becomes perfectly clear upon examination of these figures. The time-dependent behavior as revealed by the high-speed DBI measurements shown in Fig. 39 was very interesting.
• The technique utilized, experimental arrangements etc. are adequately described. The extensive postprocessing analyses of the data set taken are still pending. The approach does show initial promise.

• The high-speed back-illuminated imaging does provide sufficient information to study the droplet dynamics. Only preliminary results are provided and the detailed analysis is left to future investigations.
• A difficult measurement to perform, analysis based on thresholded images raises questions about accuracy. Although mentioned as a possibility, the authors did not measure the droplet velocity from the images.
• This section in general is not written well, with repetitions and is missing an uncertainty analysis, accuracy and precision information. Additionally, issues of volumetric versus planar measurements and phenomena are not discussed.

7. Were the diagnostic methods (7.1 and 7.2 below) for the temperature measurements appropriately designed, clearly described, and adequate to capture temperature for the Gas Phase and Two-Phase Spray Flame? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

7.1 Coherent Anti-Stokes Raman Spectrometry-based Thermometry (CARS)

• The CARS temperature measurements have been performed in a competent manner. I am somewhat concerned that the average temperatures that were reported were determined from averaged CARS spectra; the CARS spectra were average for 300 to 500 shots for the gas-phase flames, for example. In a gas flow with significant temperature fluctuations due to turbulence, the temperature determined from an averaged CARS spectrum will be biased towards lower temperatures because CARS signals will be stronger from the higher density, lower temperature gases. In extreme cases with very significant temperature fluctuations it will not be possible to extract an average temperature from an averaged CARS spectrum because it will not be possible to fit a theoretical single-temperature spectrum to the averaged CARS spectrum. For the spectra shown by the authors this does not seem to be the case, it appears the temperature fluctuations were not that severe. However, the rigorous way to analyze the CARS data is to fit the single-shot CARS spectra and then to determine the average temperature from the average of the single-shot temperatures. There are two disadvantages to this more rigorous approach. The first is that the single-shot spectra are noisier than the averaged spectra and thus are more difficult to fit. The authors did not show any single-shot spectra so the quality (SNR) of the single-shot spectra is hard to evaluate. The authors do indicate on page 153 that “The signal-to-noise ratio in the CARS spectra for some of the conditions in Table 4 was sufficient to perform a shot-to-shot analysis of the distribution in temperature.” I believe that the authors are trying to show the comparison of the average temperature determined from the single-shot spectra analysis and the averaged spectrum analysis in Fig. 53. I believe that the open circles in Fig. 53 are the average temperature determined from the averaged CARS spectrum although this is not explicitly stated and the open circles are labeled “Measurement.” The second disadvantage is that it takes much longer to fit 300 to 500 single-shot spectra than a single averaged spectrum. The fitting time can be reduced with library fitting routines, but considerable expertise is required to develop the required computational framework. However, for future CARS measurements in this group, it is essential to further develop the computational framework for analysis of single-shot CARS spectra.
• The temperature data obtained here can be used to draw logical conclusions in a relative manner on various parameters.
• There is an odd mix of really detailed (and somewhat superfluous) information and lack of specifics in the CARS section of the report. What are the uncertainties and error bars associated with fitting the CARS spectra? The comparison of temperature data (e.g., Fig. 28, Fig 30, etc.) is meaningless without error bars. Fig 45 includes error bars, but does not define their origin.

7.2 3-Color High-Speed Pyrometry

• I am much less familiar with the color high-speed pyrometry (CHSP) technology. The assumption of inverse dependence of the emissivity on wavelength is reasonable, and the rough agreement of the CARS and CHSP temperatures in the BSSF tests is encouraging. CHSP as pointed out by the authors is much easier to apply than CARS and it is much easier to obtain very high data rates. CHSP temperatures must always be regarded somewhat skeptically because of the path averaged nature of the measurement. The authors also point out difficulties due to the optically dense nature of the intermediate scale flames.
• The temperature data obtained here can be used to draw logical conclusions in a relative manner on various parameters.
• The 3CHIP method for temperature analysis of soot has some issues, as does the interpretation of the results. First, the emissivity of soot changes dramatically with maturity. Lower in the flame, where the soot is less mature, the dispersion exponent will be much larger the one, i.e., the emissivity is proportional to 1/λ^ξ, where ξ >>1 for young soot. Using a value of ξ that is too small will lead to an overprediction of the temperature. Soot will age and mature with increasing height in the flame. In normal diffusion flames, soot is also often more mature at the flame front at higher radial distances. At full maturity, the dispersion exponent is less than one (ξ <1), and using the value of unity, will lead to an underprediction in temperature. Thus, the trend in temperature may be the opposite of that suggested in Fig. 30 for the particulates as a function of height in the flame, consider the change in optical properties with soot maturity. Along the edges of the flame, optical dispersion effects may highly perturb the 3CHIP measurements because of the refractive index changes with temperature. Finally, it is highly unlikely that soot will have a different temperature from the gas phase at atmospheric pressure because conductive heat transfer equilibrates temperatures on timescales of nanoseconds at such pressures. In addition, if there are interactions between less volatile crude oil and soot particles, optical properties of the internally mixed particles will deviate from those of mature soot and look more similar to young soot, leading to larger deviations from a 1/λ dependence of the emissivity and significant errors in inferred temperatures. Furthermore, for high-sooting conditions, luminosity measurements need to be corrected for reabsorption.
• The data is qualitative at best.
• See last comment on CARS measurements. No uncertainties or standard deviation data are reported to define accuracy or uncertainties of the pyrometry measurements.

8.1 Do the results adequately characterize evidence of the droplet characteristics including droplet breakup, the droplet size (diameter), droplet speed, and the duration of droplet in fire (bench- and intermediate-scales)? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• The answer is yes for the bench-scale spray flames due to the PDA and DBI measurements. However, it does not appear that these techniques were applied to the intermediate scale flames.
• Only droplets’ SMD distributions are presented in detail. Results on droplet speed, droplet breakup, heterogeneous combustion etc., have not been reported.
• The benchtop experiments have provided detailed measurements of film breakup, atomization etc. However, it is not clear if such insights can directly be translated to the wellhead burning. The wellhead flow conditions, pressures etc., are different and may not exhibit similar breakup dynamics. Modeling and simulation, on the other hand, did not provide microscale/droplet-level information. As such, it is not possible to judge if it predicts the conditions beyond the validated range.

• The high speed backlit imaging of the droplet provides sufficient data on droplet dynamics. In this report no direct comparison between the experiments and the simulation are shown. Future studies should address this.
• The experimental data, e.g. the droplet size distributions are presented, but are not used for evaluating the droplet models at all.
• No, most of these parameters were not considered in the report descriptions of the experiments and modeling.

8.2 Does the research product accurately expand predictions of droplet diameters beyond current limited validated ranges? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• There is no clear discussion of this in the report.
• Accurate measurements of droplet diameters are extremely challenging and authors have performed a thorough experimental campaign. It would have been useful to have error bars in their measurements. Fig 34 a, at Z=10 mm, Eth 0.2/Hept 0.4 measurement does seem to show a weird spike at the center line. The reason for this behavior was not explained.
• The range of experimental characterization, the liquids were chosen to be used in the evaluation, in my opinion, limit the extrapolation of results to the scales required for application.
• The authors point out how the high speed images can be further analyzed to extract the underlying physics of the processes involved.
• Scaling trends are hardly discussed.
• No, most of these parameters were not considered in the report descriptions of the experiments and modeling.

9. Does the research product accurately characterize the impact of two-phase flow regimes (bubble, slug, and churn) on the effluent plume (bench- and intermediate-scales)? Were there any apparent strengths, weaknesses, omissions, or errors? Provide an explanation for your answers.

• The answer is not an absolute NO; but, it may be difficult from the experimental standpoint to capture this impact.
• Bench scale temperature data has been validated. Intermediate scale data needs validation. Data on gas-phase are sufficient. More work is required to reveal two-phase characteristics. Demonstration of the numerical model with EL approach to reveal the two-phase aspects has not been explicitly done as validation is shown in terms of temperature data.
• For the simulations, authors assume annular-mist flow behavior for the sake of brevity and applicability as these sprays probably atomize well. Based on the experimental conditions in table 5, the reviewer is unable to determine the two-phase flow regime in the bench and intermediate scales.
• Yes. The model will work within the range over which the correlations sub-models are valid. However, a big concern is if those models will work for actual well-head burning conditions. A detailed uncertainty analysis perhaps is needed. I would defer this point to other committee members who have more experience in this particular area.
• The impact of two-phase flow regimes on the effluent plume is not addressed in detail. Only annular-mist flow regime is considered aligned based on WCD output results for the Liberty Project.
• It appears that the authors explicitly state that bubble, slug, and churn regimes are not addressed for the sake of brevity. On P 77, they state “it is unclear what kind of flow structures form when bubbly, plug, or churn flows are expelled through a wellhead. It is reasonable to assume that these lower velocity flows are more likely to form pools or fountains than well-atomized sprays.

Therefore, for the sake of brevity and applicability, we will focus on the annular-mist flow behavior.”

• This was not clearly explained
• These flow regimes are extremely difficult to model, and the report does not provide any evidence that they are accounted for adequately
• I don’t believe the different flow regimes were considered in the modeling approach? Only misty flow. In the experiments, again, I believe only one regime was considered and it is not clear which regime it was.

10. Does the research product adequately address how the wellbore flow would influence the ejected spray plume behavior, which directly influences how the oil and gas burns and how much will either fall back to the surface or remain vapor? Were there any apparent strengths, weaknesses, omissions, or errors? Explain your answers.

• The answer is not an absolute NO. The authors did establish that the worst case spill scenario does not correspond to a high discharge rate. However, it is not clear that accounting for real wellhead conditions and crude oil properties and burning behavior has been adequately addressed to extrapolate this trend from experiment to wellhead conditions.
• As the real process is quite complex, the approach here has been to use surrogate liquid as well as gas fuels. Obviously, n-heptane will not reveal the characteristics of the crude oil. The droplet formation and its dynamics can be quite different. Thus, burn efficiency data may not be extrapolatable.
• Several assumptions were made regarding the flow conditions inside the pipe. While in bench and intermediate scale experiments, there was evidence that fallout of large droplets at the periphery of the plume, falls back to the surface, resulting in reduced burn efficiency, it is unclear if simulations actually captured this trend. The connection between pipe flow and ejected spray plume behavior is weak. The only way to improve this connection will be to perform detailed simulations of the pipe flow under different conditions and use the simulations as boundary conditions for the corresponding Eulerian-Lagrangian simulations. In the absence of multi-phase diagnostics within the pipe flow or simulations, the semi-empirical correlations are not sufficient to describe the spray flame behavior.
• The report does not provide detailed information on the fraction of fuel being burned vs. aerosolized vs. deposited/settled due to gravity. A proper estimation of these numbers will be difficult to evaluate for the wellhead conditions from the benchtop or intermediate-scale experiments, in the reviewer’s opinion.
• The CFD model has considerable uncertainty in its components which have not been characterized. Assumptions for the combustion model based on a single progress variable and presumed shape pdf for the partially premixed flames based on marginal pdfs for the 2 mixture fractions and progress variable have not been validated. The coherent flame model also has a lot of tunable constants. It is unclear which submodel affects the burning rate the most without some sort of sensitivity or UQ analysis.
• I do not believe that the current cursory work which in the authors’ opinions was to initiate the process of building a predictive tool is sufficiently advanced in either development or experimental testing to answer this question.
• Wellbore flow or WCD modeling is not detailed or provided (Appendix G), and it is difficult to know the uncertainties associated with the results which are down-scaled for input into the bench-scale problems. The Hilcorp report includes some reservoir rock and fluid properties (section 4), and well design (section 8) amongst other data that can be used along with analog and dynamic data as available to build an independent WCD model to verify output or to cross-validate WCD output amongst different wellbore flow modeling methods. The Endicott reservoir (Ali et al., 1994)

could be used as analog. This would help provide confidence to the WCD work, and the output thereof. A related question is also the impact of wellbore modeling method on the two-phase flow characterization at the wellhead, used as input to study at hand.

• The attempt to explore scaling trends is commendable. The results and comparisons are limited. Relevance to full scale system is questionable.
• The report does include a strong foundation of modeling and experimental studies of some of the physical and chemical mechanisms relevant to wellbore ignition and combustion, but the effects of wellbore flow are not considered in a broad way. Similarly, the sources of combustion inefficiency are only identified in a general way, lacking quantitative measurements over a robust range of conditions, and/or justification for the limited conditions studied.

11. Does the research product accurately predict the length of fire plume, location of flame anchoring, height of flame, width/angle, expansion, etc.? Were there any apparent strengths, weaknesses, omissions, or errors? Explain your answers.

• This is not an absolute YES. The authors could have made their comparisons clearer by using tables reporting the different quantities and by presenting the results of the computational and experimental studies in one section. The second issue is the interpretation of what “accurately” means. The authors claim consistency in trends and values; but, a quantification of the compared values is certainly better.
• The gas-phase overall features can be satisfactorily understood. Apart from the gross features, droplet dynamics, heterogeneous droplet flames etc. require more work.
• For Propane fuel, these parameters are reasonably well predicted, but results with the surrogate fuel assumed (heptane), are not presented. While the simulations can capture reasonable trends, quantitative values of temperature profiles at different locations upstream and downstream locations of the flame lift-off length for different propone flow rates are not well captured. Capturing flame lift-off length, height, size etc. has been a challenge for the spray-flame community for decades, especially for high co-flow conditions. While there may be several reasons for this mis-match, the reviewer believes that the two-phase flow mixture at the pipe flow exist needs to be better characterized to initialize the spray flame more accurately. The choice of turbulence model is also known to be important and the reviewer expects that LES would do a better job.
• The modeling may not be predictive due the many assumptions made, and the lack of understanding of the sensitivity of the characterization of the plume (burning rate, height, flame lift off, spread angle, etc) to the many model assumptions. For example, are f1, f2, c, and H_bar statistically independent such that product of the independent pdfs is the same as their joint pdfs? The laminar flame speed model used in the source term for the progress variable is questionable as it is based on tabulated high-temperature propane-air mixture flame speeds which may not be representative of the flame speed correlations of the mixtures of well gases and volatile oil species over the range of conditions encountered in the wellhead. It is also uncertain whether the normal flame propagation term P4 in the extended coherent model accounts for flame stretch correlations. It seems that the submodels needed to be better validated individually, before being validated collectively.
• I do not believe that the current cursory work which in the authors’ opinions was to initiate the process of building a predictive tool is sufficiently advanced in either development or experimental testing to answer this question.
• Only qualitative trends are provided. For the bench-scale model a co-flow of water vapor, oxygen, and nitrogen at 1400 k with an axial flow velocity of 2 m/s is specified. The authors note that the flame cannot be stabilized without this co-flow. This leads to a question, if a stable burning configuration is even possible when the gas flow rates are high in a real situation. Perhaps an upper limit to the well-gas velocity should be calculated and presented as one of the worst case scenarios.

For the intermediate-scale model the domain vertical size is truncated at 2.5 m and the flame extends past this value, and no direct comparisons are possible.

• The theory for the two-phase flow has not been fully utilized.
• The report does not provide a comparison between the measured and modeled plume length, etc.
• The model may predict these characteristics, but the simulations were not quantitatively or qualitatively validated for all these metrics.

12. Does the research product determine the primary mechanism driving burn efficiency?

• The research product highlights and provides critical details of the physical processes underlying the wellhead burning. However, the multi-scale, multi-physics problems are difficult to tackle effectively. Thus, the efforts of the present research were intentionally kept in understanding the physics in lab-scale or intermediate-scale experiments, which allowed them to validate the developed numerical models at least in a qualitative sense. In that way, the research does provide critical information on primary mechanisms of wellhead burning. However, one should also be careful in extending these results directly in wellhead conditions where the flow parameters, the fuel characteristics, well-hear pressure can be significantly different, leading to very different burn efficiency.
• The authors conclude that the annular fluid film that escapes the injection tube without being entrained into the main flow is the primary cause driving the burn efficiency. But this conclusion seems to be limited to the worst case scenario of lower gas flow rate postulated in the study. At high gas flow rates it may not be possible to intentionally ignite the oil/gas jet.
• A clear explanation was not seen
• No, not without sensitivity analysis of the sub-models used in the overall modeling.

13.1 Were the conclusions based on the OSRR 1063 study findings in the report logical and appropriate based on the results? What other conclusions related to the study were made and are appropriate?

• Note that the Yes response is made related to the studies presented in the report. It is not clear if a strong case is made to extrapolate the conclusions to wellhead burning.
• As mentioned earlier, the data from this study can form validation data for a numerical model. The model can also be improved upon several aspects. Conclusions about actual scale scenario cannot be drawn within this study.
• In the “executive summary” the authors’ claim that with the CFD tool that has been established (based on bench and intermediate scale experiments), if the characteristics of the well (e.g., mass flow rate and oil properties) are known, fall out fractions can be estimated. In reviewers’ opinion this claim may not be substantiated since even for a single component bench scale experiments, simulations do not capture the flame characteristics very well. While the procedure may be transferable, the model is not robust enough to mimic a well-head where there may be other physical factors affecting the spray flame. The intermediate scale experiment provides a way to estimate the burn efficiency. However, the experiments are performed under well controlled conditions and assuming certain pipe flow regime. It is unclear if the burn efficiency methodology is transferable either.
• Future work is needed to address the physical and chemical properties of more representative crude oil surrogates in the modeling effort. The experiments identified mechanisms for reduced burn efficiency due to the fall out of large droplets formed at the periphery of the plume from the unentrained film of the wellbore flow.
• I answer yes above, but the conclusions themselves are very limited in value in terms of assessing the adequacy of the current first-order modeling conceptualization to address the issue of

predictively modeling combustion efficiency well for various well-head geometries, flow rates, and crude properties.

• The main conclusion seems to be that the liquid film that forms on the periphery of the plume is the major cause of lowering the burn efficiency.
• Seem reasonable (although CFD is not my area of expertise, and so this comment is general). Impact of different flow regimes through time (for wellbore) could be included/expanded.
• As the conclusions indicate, the study is not complete. The scope of the validation is limited to temperature measurements, the modeled and measured droplet statistics are not compared, the gas velocity is not measured, the droplet velocities are partially measured, the plume scales are not compared.
• Given the objective of the report was to define burn efficiency of the wellhead flow, it seems imperative to include the details on the burn efficiency measurements in the body of the report, and not as an appendix. Conversely, the secondary considerations (turbulence features) could be relegated to an appendix along with the lengthy descriptions of diagnostic details. Instead the diagnostic sections should include descriptions of rigorous uncertainty and repeatability analysis of the experimental methods. The conclusion about droplet fallout contributing significantly to low combustion efficiency at lower wellhead flows is important, but needs validation and discussion in terms of scaling to an actual wellhead.

13.2 Are there any additional study findings or conclusions that could be drawn from the study? Provide an explanation for your answers.

• This study is an excellent first step and in fact motivates both additional experimental and computational studies. Also getting more field data on the well-head and crude oil characteristics will be extremely useful next steps.
• A significant conclusion as regards the computational model is the need for full coupling between the gas and liquid phases, their thermodynamics and chemistry such that their momentum, energy, mass transport and reaction are coupled. Further analysis of the assumptions made in the various submodels quantifying their accuracy is needed. Better understanding of the propagation of uncertainties and sensitivities of the plume parameters to the various modeling assumptions is needed.
• I believe it would be important to have more elaboration as to the basis in the first-order model conceptualization, a discussion of what the next steps in revising it should be, and what additional submodel considerations need to be significantly refined to consider full range crude property effects on combustion efficiency at full-scale conditions.
• The experimentally observed oscillations of the fire plume seems noteworthy and deserves further analysis. The feasibility of developing a computational model to study oil wellhead fires is demonstrated, though in a limited range of conditions. Future improvements are warranted.