IEG 환경지질연구정보센터

전체 글

(1)CSIRO PUBLISHING www.publish.csiro.au/journals/eg. Copublished paper, please cite all three:. Exploration Geophysics, 2010, 41, 24–30; Butsuri-Tansa, 2010, 63, 24–30; Jigu-Mulli-wa-Mulli-Tamsa, 2010, 13, 24–30. Assessing the repeatability of reflection seismic data in the presence of complex near-surface conditions CO2CRC Otway Project, Victoria, Australia Yousuf Al-Jabri1,2,3 Milovan Urosevic2,3 1. Petrulum Development Oman, Oman, Curtin University of Technology and CO2CRC, Perth, WA 6845, Australia. 2 Department of Exploration Geophysics, Curtin University of Technology, GPO Box: U1987 Perth, WA 6845, Australia. 3 Corresponding authors. Email: [email protected]; [email protected]. Abstract. This study utilises repeated numerical tests to understand the effects of variable near-surface conditions on timelapse seismic surveys. The numerical tests were aimed at reproducing the significant scattering observed in field experiments conducted at the Naylor site in the Otway Basin for the purpose of CO2 sequestration. In particular, the variation of elastic properties of both the top soil and the deeper rugose clay/limestone interface as a function of varying water saturation were investigated. Such tests simulate the measurements conducted in dry and wet seasons and to evaluate the contribution of these seasonal variations to seismic measurements in terms of non-repeatability. Full elastic pre-stack modelling experiments were carried out to quantify these effects and evaluate their individual contributions. The results show that the relatively simple scattering effects of the corrugated near-surface clay/limestone interface can have a profound effect on time-lapse surveys. The experiments also show that the changes in top soil saturation could potentially affect seismic signature even more than the corrugated deeper surface. Overall agreement between numerically predicted and in situ measured normalised root-mean-square (NRMS) differences between repeated (time-lapse) 2D seismic surveys warrant further investigation. Future field studies will include in situ measurements of the elastic properties of the weathered zone through the use of ‘micro Vertical Seismic Profiling (VSP)’ arrays and very dense refraction surveys. The results of this work may impact on other areas not associated with CO2 sequestration, such as imaging oil production over areas where producing fields suffer from a karstic topography, such as in the Middle East and Australia. Key words: time-lapse/near-surface conditions.. Introduction The depleted Naylor Gas Field, located in the onshore Otway Basin of Australia (Figure 1), is currently utilised as a CO2 sequestration demonstration project. Carbon dioxide has been injected into the Waarre C sandstone over a 2-year period. The gas mixture injected consists of 80% CO2 and 20% CH4. The reservoir zone into which the CO2 mixture was injected has residual gas saturation of around 20%. Consequently we expect that the injection of the gas mixture will produce very subtle changes in the elastic properties of the reservoir rock, and hence result in very small measurable 4D seismic effects. High seismic repeatability is therefore of critical importance to the monitoring at this site. Unfortunately, initial 2D field tests suggest that it will be hard to achieve good repeatability at this site. Time-lapse or 4D seismic data are used increasingly to study and image the changes in the seismic response induced by the production of hydrocarbons or the injection of CO2, water or steam into a reservoir. Such studies often proved to be very effective. However, practically all of these studies were conducted offshore. On land, unfortunately, time-lapse seismic changes are also produced by variations in the near-surface conditions, source signature variation, acquisition geometry (positioning and spacing), acquisition equipment, recording fidelity differences between the surveys, processing methods, and ambient noise. The confidence level in interpreting any Ó ASEG/SEGJ/KSEG 2010. seismic changes depends on how good the seismic repeatability is. The residual differences in the repeated timelapse data that do not represent changes in the subsurface geology impact the effectiveness of the time-lapse seismic methodology. It is widely accepted that time-lapse repeatability of land seismic is, in general, low. It is, however, less understood which factors are critically important for time-lapse land surveys. In the case of the Naylor CO2 injection test site area, the presence of sinkholes and karst topography in the nearsurface zone make seismic non-repeatability investigations challenging but also interesting (Figure 2). In such geological terrain, the degree of signal scattering caused by the top rugose limestone surface and caverns is greatly dependent on the depth to the water table. This is because if the water level drops to a level below the rugose limestone surface, then the degree of signal scattering caused by the rugose limestone surface is increased (Al-Jabri et al., 2008a). Consequently, repeated 2D seismic test lines have been acquired at the Naylor location before the 3D baseline seismic acquisition and certainly before CO2 injection commenced at this field. These seismic lines were recorded with mini-vibroseis and weight-drop in both wet and dry conditions. The aim of this work was to assess nonrepeatability due to the variations in soil conditions (Urosevic et al., 2007, 2008). To help understand field observations we 10.1071/EG09010. 0812-3985/10/010024.

(2) CO2CRC Otway Project, Victoria, Australia. Exploration Geophysics. 25. Fig. 1. Location of the Naylor Field in the south-east of Australia (Otway Basin).. Clay Limestone. Fig. 2. Corrugated top limestone in the near-surface of the western Otway Basin.. conducted different numerical simulations. Then, comparing the results of the numerical tests with field data clearly showed that the changes in saturation at the near-surface have a very profound effect on seismic repeatability. Motivation As shown (mainly qualitatively) from early 2D field tests (Figure 3), the depth of penetration of seismic energy and frequency characteristics of the seismic wavelet will be different in dry and wet periods of the year (Urosevic et al., 2007). Furthermore these tests showed clearly that seasonal variations have a first-order effect on the seismic signature, while the source type and positioning accuracy of the. recording instruments have secondary and tertiary effects on time-lapse studies, respectively. Consequently the effect of the near-surface zone on the seismic signature was analysed by splitting it into two components: i) top soil (agricultural part ~0.5 m thick) and ii) shallow (2–10 m thick) and irregular karstic topography (Al-Jabri et al., 2008b). A relatively simple scattering effect from the karst (corrugated clay/limestone interface) was expected due to the large velocity contrast (400–500 m/s). The effect of the agricultural soil (elasto-plastic zone) is harder to model and at this stage, before further field tests are carried out, and can only be approximately modelled. Figure 3 shows the difference in the source footprint for the wet and dry case. Similarly the difference in the signal strength and hence signal-to-noise (S/N) ratio between wet and dry 2D.

(3) Exploration Geophysics. Y. Al-Jabri and M. Urosevic. Non-Repeatability (%). 26. The Non-Repeatability for Wet and Dry conditions of the Near surface at Naylor field 100 80 60 40 20 0. Non-Repeatability (%). 0. 5 10 15 20 25 30 35 40 45 50 CDP. Fig. 3. 2D seismic data recorded at the Naylor site with weight-drop: near-surface is wet (left), near-surface is dry (middle), and their difference (right). Weight Drop foot-print for wet and dry top soil is shown below. The lower right corner graph shows non-repeatability between wet and dry surveys computed for Clifton Formation within the red time window.. stacks is obvious (Figure 3). Clearly, to improve the repeatability for detection of time-lapse changes due to CO2 injection, the effect of the near-surface on seismic repeatability needs to be evaluated. Only then can attempts to compensate for the variability in the signal character by specialised field measurements be carried out. The data in Figure 3 show clearly the impact that water table variations can have – large non-repeatability due to a saturation change in the top soil and hence the magnitude of accompanying plastic effect (top soil compression) (Al-Jabri and Urosevic, 2008). This is true even for the best case scenario (marker reflection that is high S/N and within a narrow computation window). The magnitude of elastic changes, however, are less clear, particularly at the target level. To explain it we deployed full pre-stack elastic modelling which shared the same survey geometry with field data. Methodology It is anticipated that the non-repeatability issues are, to the first order of approximation, related to variations of the properties of the top soil and underlying clay/limestone units. The modelling. experiments were aimed at evaluating the contribution of each of these two factors to non-repeatability. The near-surface changes at the Naylor Field were therefore modelled by assuming three different scenarios: 1) Top soil + corrugated clay/limestone interface 2) As for 1, no corrugations 3) As for 1, thin (zero thickness) top soil layer Dry and wet variations are assumed to cause changes in the elastic properties as shown in Table 1. Model-1: Representing the case of the near-surface at the Naylor Field consisting of top soil (0.5 m thick) and corrugated top surface of the limestone (Figure 4). This enabled us to assess the total effect of the near-surface on the seismic non-repeatability to be assessed. Model-2: Representing a simpler case of flat limestone topography (Figure 5) and used to assess the contribution of the top soil to seismic non-repeatability. Model-3: Representing the case of top soil being absent, this model was used to analyse the contribution of limestone corrugations on seismic non-repeatability (Figure 6).. Table 1. Thicknesses, top sub-surfaces, densities, velocities and (Q) absorptions for each unit of the Otway Basin models at Naylor-1. Formation. Soil Clay dry Limestone Gellibrand marl Clifton formation Clay. Thickness (m). Top sub surface (m). 0.5 3.5 118 335 17 –. 0 0.5 4.0 122.0 457.0 474.0. Wet near-surface Model Velocity Absorption Density (m/s) (Q) (kg/m3) 1300 1800 2430 2500 2700 2346. 500 1600 1900 2100 2600 2985. 50 80 100 120 140 160. Dry near-surface Model Density Velocity Absorption (kg/m3) (m/s) (Q) 1100 1400 2430 2500 2700 2346. 250 1250 1900 2100 2600 2985. 25 40 100 120 140 160.

(4) CO2CRC Otway Project, Victoria, Australia. Stratigraphic lithology. Exploration Geophysics. 27. Lithology interval. Soil. 0.5 m. Clay. 3.5 m. Limestone. 118.0 m. Gellibrand marl. 335.0 m. Clifton formation. 17.0 m. Wet. Dry. Differences. Top Clifton Formation. Clay. Fig. 4. Model-1 which represents wet and dry cases for top soil plus corrugated top limestone surface. Shown from left to right are: depth model, synthetic data for dry and wet cases and their difference. Window for computation of non-repeatability is also shown.. Stratigraphic lithology. Lithology interval. Soil. 0.5 m. Clay. 3.5 m. Limestone. 118.0 m. Gellibrand marl. 335.0 m. Clifton formation. 17.0 m. Dry. Differences. Wet. Top Clifton Formation. Clay. Fig. 5. Model-2 which represents the wet and dry cases for both top soil plus a flat top limestone surface. Shown from left to right are: depth model, synthetic data for dry and wet cases and their difference. Window for computation of non-repeatability is also shown.. Lithology interval. Stratigraphic lithology. 4m. Clay. Dry Limestone. 118.0 m. Gellibrand marl. 335.0 m. Clifton formation. 17.0 m. Clay. Differences. Wet. Top Clifton Formation. Non-Repeatability (%). Fig. 6. Model-3 which represents the wet and dry case for absent top soil but a corrugated top limestone surface present. Shown from left to right are: depth model, synthetic data for dry and wet cases and their difference. Window for computation of non-repeatability is also shown.. 100 90 80 70 60 50 40 30 20 10 0 0. 10. 20. 30. 40. 50. CDP Fig. 7. The non-repeatability as measured for model-1 and model-2, assuming wet condition of the near-surface. The normalised root mean square computed expresses the difference between flat and corrugated top limestone surface..

(5) 28. Exploration Geophysics. Y. Al-Jabri and M. Urosevic. Non-Repeatability (%). 100 90. Real data. 80. Model-1. 70. Model-2 Model-3. 60 50 40 30 20 10 0 0. 5. 10. 15. 20. 30. 25. 35. 40. 45. 50. CDP Fig. 8. The non-repeatability curve computed for wet and dry case for the field data of weight-drop source for a window of 40 ms around the Clifton Formation against the non-repeatability curves computed for three models across a range of traces and within the same window: black line represents the non-repeatability for wet and dry case for the field data of weight-drop source, blue line represents the non-repeatability for wet and dry case for model-1, green line represents the nonrepeatability for wet and dry cases for model-3 and red line shows non-repeatability for model-2.. These models have been simulated with stress-velocity finite difference formulation (Vireaux, 1988) which is implemented in TesseralCS-2D Full Wave Modelling software. Information from logs, cores and surface seismic measurements were used as input for the simulations (Table 1). The three cases have been designed to evaluate the contribution of each of the selected factors (top soil and corrugations) plus their total effect on the seismic signature. Generated shot records for the three different models were processed and analysed for non-repeatability. Results One of the conventional measures of time-lapse seismic effectiveness is through a computation of normalised rootmean-square (NRMS) difference between repeated datasets. The non-repeatability of seismic amplitudes in two traces, at and bt, can be measured by NRMS difference, defined in time gate t by the RMS of the difference between at and bt normalised by the mean RMS of the two traces and expressed as a percentage. We measured NRMS for the Clifton Formation because the seismic event has the highest S/N ratio (the best case scenario for the Naylor Field) and assumes that seismic strength is adequate for the deeper reservoir target. The window of 40 ms was selected for computation via the equation provided by Calvert (2005): 200 RMSðat bt Þ : NRMS ¼ RMSðat Þ þ RMSðbt Þ. ð1Þ. A non-repeatability modelled case for the wave scattering by a corrugated limestone interface is illustrated in Figure 7. The NRMS difference between flat and corrugated interfaces accounts for ~15%. Total non-repeatability for all three models together with the measured field data is shown in Figure 8. The nonrepeatability between wet and dry for Model 1 is ~46%; nonrepeatability between wet and dry for Model 2 is ~38% and non-repeatability between wet and dry for Model 3 is ~30%. The real data (average ~52% variation) fits close to Model 1. Conclusion Numerical tests verified that the time-lapse seismic surveys should be conducted under the same near-surface conditions to maximise repeatability (this applies for both surface seismic. and Vertical Seismic Profiling [VSP]). Changes in the water table can influence the seismic response through increased scattering by the corrugated interface at the top of the limestone. It appears that the effect of the weathered zone on the seismic signature can be split into two components: i) a complex effect of the agricultural soil (elasto-plastic zone); and ii) the relatively simple scattering effect of the corrugated near-surface clay/limestone interface (purely elastic zone). The first is more difficult to simulate, hence the need for further field experiments. From our models we can conclude that: i) 30% of non-repeatability comes from the change of the near-surface saturation; and ii) 15% of non-repeatability results from the scattering related to corrugated surface of the limestone. An agreement between numerically predicted and measured NRMS values encourages further numerical tests and also incorporation of numerical predictions into the process of monitoring design for future sequestration sites. Future experiments include in situ measurements of the elastic properties of the near-surface (soil and underlying clay) and scattering effects of the corrugated top limestone interface. For that we will use ‘micro VSP’ arrays and very dense refraction surveys. Acknowledgment The authors would like to thank CO2CRC, for the full access to Otway Basin Pilot Project (OBPP) database. In particular we acknowledge help provided by Dr A. Kepic and Dr D. Sherlock with field data design and acquisition. Petroleum Development Oman (PDO) is acknowledged for providing Yousuf with a PhD scholarship. We are grateful to Tesseral Technologies Inc., Hampson & Russell Software Services and Landmark Graphics for providing software packages and support.. References Al-Jabri, Y., and Urosevic, M., 2008, The applicability of vibroseis sources for the land seismic time-lapse surveys; CO2 sequestration field: CO2CRC Otway Project, Victoria, Australia: Vibroseis Workshop 2008, Prague, Czech Republic, 13–15 October 2008. Al-Jabri, Y., Urosevic, M., Evans, B., and Sherlock, D., 2008a, Understanding seismic repeatability in the presence of irregular near-surface conditions (karst): CO2CRC Otway Project, Victoria, Australia: SEG & EAGE Summer Research Workshop 2008, Vancouver, Canada, 7–12 September 2008..

(6) CO2CRC Otway Project, Victoria, Australia. Al-Jabri, Y., Urosevic, M., and Kepic, A., 2008b, The effects of the nearsurface weathered zone on the CO2 time-lapse monitoring program at Naylor-1, CO2CRC Otway Project, Victoria, Australia: CO2CRC Symposium 2008: Queenstown, New Zealand, 1–5 December 2008. Calvert, R., 2005, Insights and methods for 4D reservoir monitoring and characterization: Society of Exploration Geophysicists. CGG, 2000, Final Report: Seismic Data Processing OCV00 Curdie Vale 3D; period: May September for Santos, Ltd. Urosevic, M., Sherlock, D., Kepic, A., and Dodds, K., 2007, “Land seismic acquisition repeatability for time-lapse monitoring of CO2 sequestration”: 19th International Conference of Australian Society of Exploration Geophysics, Perth, WA.. Exploration Geophysics. 29. Urosevic, M., Sherlock, D., Kepic, A., Nakanishi, S., and Tcherkashnev, S. K., 2008, “Time lapse VSP program for Otway basin CO2 sequestration pilot project”: 70th EAGE Conference & Exhibition – Rome, Italy. Vireaux, J., 1986, P-SV wave propagation in heterogeneous media: Velocitystress finite difference method: Geophysics, 51, 889–901.. Manuscript received 11 February 2009; accepted 14 December 2009..

(7) 30. Exploration Geophysics. Y. Al-Jabri and M. Urosevic. ⶄ㔀⴫ጀ⁁ᘒਅߢߩ෻኿ᴺ࿾㔡តᩏߩౣ⃻ᕈ⹏ଔ㧦 ࠝ࡯ࠬ࠻࡜࡝ࠕ࡮ࡆࠢ࠻࡝ࠕᎺ %1%4%ࠝ࠻࠙ࠚࠗࡊࡠࠫࠚࠢ࠻ Yousuf Al-Jabri1࡮Milovan Urosevic1 1 ࠞ࡯࠹ࠖࡦᎿ⑼ᄢቇ . ⷐ ᣦ㧦 ᧄ⎇ⓥߢߪ‫⴫ޔ‬ጀ⁁ᘒߩᄌൻ߇➅ࠅ㄰ߒ࿾㔡តᩏߦ෸߷ߔᓇ㗀ࠍℂ⸃ߔࠆߎߣࠍ⋡⊛ߣߒߚ‫ࠅ➅ޔ‬㄰ߒᢙ୯ታ㛎 ࠍታᣉߒߚ‫⋆ࠗࠚ࠙࠻ࠝޕ‬࿾ߦ޽ࠆࡀࠗ࡜࡯ࠨࠗ࠻ߦ߅޿ߡታᣉߐࠇߚੑ㉄ൻ὇⚛㓒㔌ࠍ⋡⊛ߣߒߚࡈࠖ࡯࡞࠼ታ㛎ߦߡ᷹ⷰ ߐࠇߚ᦭ᗧߥᢔੂ⃻⽎ࠍౣ⃻ߔࠆߎߣ߇‫ޔ‬ᢙ୯ታ㛎ߩ⋡⊛ߢ޽ࠆ‫ޔߌࠊࠅߣޕ‬᳓㘻๺₸ߩᄌൻߦ઻߁‫⴫ޔ‬࿯ߣߘߩਅㇱߦሽ࿷ ߔࠆ⿠ફߩ޽ࠆ☼࿯/⍹ἯጤႺ⇇ߩᒢᕈ․ᕈߩᄌൻࠍㅊⓥߒߚ‫ߥ߁ࠃߩߎޕ‬ᢙ୯ታ㛎ߦࠃࠅ‫ޔ‬㔎ᦼ޽ࠆ޿ߪੇᦼߦታᣉߐࠇࠆࡈ ࠖ࡯࡞࠼᷹ቯࠍᮨᡆߒ‫ߥ߁ࠃߩߎޔ‬ቄ▵ᄌൻ߇࿾㔡ᵄ᷹ⷰߩ㕖ౣ⃻ᕈߦߤࠇߊࠄ޿ነਈߔࠆ߆ࠍ⹏ଔߔࠆ‫ߩࠄࠇߎޕ‬ᓇ㗀ࠍቯ ㊂ൻߒ‫ߚ߹ޔ‬ฦ‫ߩ⚛ⷐߩޘ‬ነਈࠍ⹏ଔߔࠆߚ߼ߦ‫ޔ‬ᒢᕈᵄേ႐ߩోᵄᒻࡕ࠺࡝ࡦࠣࠍⴕߞߚ‫⚿ޕ‬ᨐߣߒߡ‫⴫ޔ‬ጀઃㄭߦሽ࿷ߔ ࠆ⿠ફߩ޽ࠆ☼࿯/⍹ἯጤႺ⇇ߦ⿠࿃ߒߚᢔੂലᨐߪ‫ࠅ➅ޔ‬㄰ߒ࿾㔡តᩏ⸥㍳ߦᄢ߈ߥᓇ㗀߇޽ࠆߎߣ߇ࠊ߆ߞߚ‫ޔߦࠄߐޕ‬ᷓ ㇱߩ⿠ફߦࠃࠆᢔੂߩᓇ㗀ߦᲧߴߡ‫⴫ޔ‬࿯ߩ᳓㘻๺₸ߩᄌൻߩᣇ߇࿾㔡ᵄ⸥㍳ߦࠃࠅᄢ߈ߥᓇ㗀ࠍ෸߷ߔน⢻ᕈ߇޽ࠆߎߣ߽ ␜ߒߚ‫ޕ‬ੑᰴరߩ➅ࠅ㄰ߒ࿾㔡តᩏ⸥㍳㑆ߦ߅ߌࠆᱜⷙൻߐࠇߚ RMS Ꮕಽߦ߅޿ߡ‫ޔ‬ᢙ୯⊛ߦ੍ᗐߐࠇߚ߽ߩߣࡈࠖ࡯࡞࠼ ᷹ቯߐࠇߚ߽ߩߣ߇᭎ߨ৻⥌ߒߡ߅ࠅ‫⺞ࠆߥࠄߐߪߣߎߩߎޔ‬ᩏߩᱜᒰᕈࠍ଻㓚ߔࠆ‫ޕ‬዁᧪ߩࡈࠖ࡯࡞࠼⺞ᩏߢߪ‫ޔ‬ዊⷙᮨߥ VSP ⺞ᩏ߿㜞ኒᐲዮ᛬ᴺߦࠃࠆ㘑ൻᏪߩᒢᕈᵄ․ᕈ⸃᣿߇ታᣉߐࠇࠆ੐ߦߥࠆߢ޽ࠈ߁‫⎇ᧄޕ‬ⓥߩ⚿ᨐߪੑ㉄ൻ὇⚛㓒㔌ಽ㊁ ߩߺߥࠄߕ‫߫߃଀ޔ‬ਛ᧲߿⽕Ꮊߦ߅ߌࠆࠞ࡞ࠬ࠻࿾ᒻࠍ᦭ߔࠆᴤ↰࿾Ꮺߢߩࠗࡔ࡯ࠫࡦࠣಣℂߥߤ߳ߩነਈ߇޽ࠈ߁‫ޕ‬ ࠠ࡯ࡢ࡯࠼㧦➅ࠅ㄰ߒ࿾㔡តᩏ⴫ጀ᧦ઙ. 懻沧穢͑ 熢抆割浶穞櫖昢͑ 愞斲憛͑ 痊昷砒沖巒汞͑ 愞懻昷櫖͑ 堆穢͑ 磏儆͑͝ ͑ 笾渂͑͝ 捋皦庲橊͑͝ʹ΀ͣʹ΃ʹ͑΀ΥΨΒΪ͑ 稊嵢洣瞾͑ Yousuf Al-Jabri1, Milovan Urosevic1 1 䅂䔒Ὃὒ╖䞯ὒG . 殚͑ 檃౐G → ⪊ሆᜮ ❶႞ヂ㕞○㞦㕪╆⩪ រ㧶 ㄶ√⹚㧲ሆⴊ⯲ ⪛㨿⯞ ∞▷㧲ዊ ⮞㨎 ₲↏ⲛⰒ ⚲㋲ὂ㪯❾㩲⯞ Ⰾ⭃㧲⪚᝾. ⚲㋲ ❾㩲⯲ ὃⲛ⯚ Otway ∞⹚⩪ Ⱒᜮ Naylor ⹚⪇⩪▶ CO2 ᅃṆḖ ὃⲛ⯖ᳶ ⚲㨣 ᢶ 㪞ⰿ ❾㩲⩪▶ ᆚナᢶ ⶖ⬮㧶 ╊ᰚ㞦᥾⯞ ⱆ╷○㧲ᜮ ᄝⰎ᝾. 㝓㰢, ⚲㢆㫮ᡞḖ ⅚㫮❶㎶ ႚἎ▶ ╛√㘺⨫ᆖ ➆√⯲ ⶖḞ⹞ Ⲫ㘺/▷㬦⧮ ᅗᅞἎ⯲ 㕞○ ○⹢᥾⯲ ⅚㫮Ḗ ᆚナ㧲⪚᝾. Ⰾᲆ㧶 ❾㩲⯞ 㙏㨎▶ ᄎዊ ₩ ⭊ዊ ᅞⲢ⩪ 㨣㨎⹞ ㊻ⲯ㋲Ḗ ὂ╆㧲⪚ᅺ, ᅞⲢ⯲ ⅚㫮ႚ 㕞○㞦㊻ⲯ⩪ ₒ㋲ᜮ ⪛㨿⯞ ⋞₲↏○ ᆚⲪ⩪▶ 㡣ႚ㧲⪚᝾. Ⰾ ⪛㨿᥾⩪ រ㧶 ⲯᱣ㫮⫚ ႛႛ⯲ ዊ⪆ᡞḖ ㊻ⲯ㧲ዊ ⮞㨎▶ 㕞○㞦㞦ᡳ⃃ⲯ❷⯞ Ⰾ⭃㧶 ⚲㋲ὂ᠒ṛⰎ ⚲㨣ᢲ⩢᝾. ⚲㋲ὂ᠒ṛ ᅊᆖᜮ ㄶ√⯲ Ⲫ㘺/▷㬦⧮⯲ ⶖḞ⹞ ᅗᅞἎ⩪▶⯲ ╛រⲛ⯖ᳶ ႞គ㧶 ∞╊ 㭂ᆖ᥾Ⰾ ❶႞ヂ㕪╆⩪ រ㧶 ╛ន㧶 ⪛㨿⯞ ₒ㌂⯞ ↎⪆ⶖ⩢᝾. ᪪㧶, ╛√ 㘺⨫⩪▶⯲ 㢆㫮ᡞ⯲ ⅚㫮ᜮ ➆⹚⩎ ➆√⯲ ⶖḞ⹞ ᅗᅞἎ↎᝾ᡞ ៮ 㕞○㞦 ❺㫒⩪ ⰺⱆⲛ⯖ᳶ ⪛㨿⯞ ₒ㋺ ⚲ Ⱒ᝾. 㪞ⰿ⩪▶ ㊻ⲯᢶ ₲↏ᢶ (❶႞ヂ) 2ヂ⭪ 㕞○㞦㕪╆ Ⱚᵦ᥾ ╆Ⰾ⯲ ⲯቶ㫮ᢶ RMS (Root-mean-square) ヂⰎ⫚ ⚲㋲ⲛ⯖ᳶ ᅞ╊ᢶ ヂⰎ⫚⯲ ⲞㅎⲛⰒ Ⱆ㋲ᜮ ៮ Ṩ⯚ ⪊ሆႚ 㧞⬮㨂⯞ ⧦ ⚲ Ⱒ᝾. 㨿㭞 ⹞㨣ᢺ ⪊ሆᜮ micro VSP ⃊⪎ᆖ Ṿ⭊ ⴊₚ㧶 ሎⲢℯ 㕪╆Ḗ Ⰾ⭃㨎▶ 㤧㫮 ⹚⪇⯲ 㕞○ ○⹢⯞ 㪞ⰿ⩪▶ ㊻ⲯ㧲ᜮ ᄝⰎ᝾. → ⪊ሆ⯲ ᅊᆖᜮ ⶫᡳⰎᔲ 㫒ⶖ⫚ ႳⰎ ㌎Ḏ✾㝒 ⹚㪯⯖ᳶ ╷╊⩪ ⩎Ჾ⭚Ⰾ ᧊Ḏᜮ ⹚⪇⯲ ▷⮺ ╷╊ ⪛╛㫮⫚ Ⴓ⯚ CO2 ⹚ⶫᅃṆ⫚ ╛ᆚⰎ ⩠ᜮ ∞⨖⩪ᡞ 㭂ᆖႚ Ⱒ⯞ ᄝⰎ᝾. 渂殚檺౐㔲ṚTἓὒSG 㻲⿖G ㌗䌲G. http://www.publish.csiro.au/journals/eg.

(8)