Real-time drilling mud gas monitoring for qualitative evaluation of hydrocarbon gas composition during deep sea drilling in the Nankai Trough Kumano Basin
- Sebastian B Hammerschmidt†1Email author,
- Thomas Wiersberg†2,
- Verena B Heuer†1,
- Jenny Wendt†1,
- Jörg Erzinger†2 and
- Achim Kopf†1
© Hammerschmidt et al.; licensee Springer. 2014
Received: 13 June 2014
Accepted: 24 November 2014
Published: 16 December 2014
Integrated Ocean Drilling Program Expedition 338 was the second scientific expedition with D/V Chikyu during which riser drilling was conducted as part of the Nankai Trough Seismogenic Zone Experiment. Riser drilling enabled sampling and real-time monitoring of drilling mud gas with an onboard scientific drilling mud gas monitoring system (“SciGas”). A second, independent system was provided by Geoservices, a commercial mud logging service. Both systems allowed the determination of (non-) hydrocarbon gas, while the SciGas system also monitored the methane carbon isotope ratio (δ13CCH4). The hydrocarbon gas composition was predominated by methane (> 1%), while ethane and propane were up to two orders of magnitude lower. δ13CCH4 values suggested an onset of thermogenic gas not earlier than 1600 meter below seafloor. This study aims on evaluating the onboard data and subsequent geological interpretations by conducting shorebased analyses of drilling mud gas samples.
During shipboard monitoring of drilling mud gas the SciGas and Geoservices systems recorded up to 8.64% and 16.4% methane, respectively. Ethane and propane concentrations reached up to 0.03 and 0.013%, respectively, in the SciGas system, but 0.09% and 0.23% in the Geoservices data. Shorebased analyses of discrete samples by gas chromatography showed a gas composition with ~0.01 to 1.04% methane, 2 – 18 ppmv ethane, and 2 – 4 ppmv propane. Quadruple mass spectrometry yielded similar results for methane (0.04 to 4.98%). With δD values between -171‰ and -164‰, the stable hydrogen isotopic composition of methane showed little downhole variability.
Although the two independent mud gas monitoring systems and shorebased analysis of discrete gas sample yielded different absolute concentrations they all agree well with respect to downhole variations of hydrocarbon gases. The data point to predominantly biogenic methane sources but suggest some contribution from thermogenic sources at depth, probably due to mixing. In situ thermogenic gas production at depths shallower 2000 mbsf is unlikely based on in situ temperature estimations between 81°C and 85°C and a cumulative time-temperature index of 0.23. In conclusion, the onboard SciGas data acquisition helps to provide a preliminary, qualitative evaluation of the gas composition, the in situ temperature and the possibility of gas migration.
KeywordsNankai Trough Riser drilling Drilling mud gas monitoring Mud logging Kumano basin IODP NanTroSEIZE Accretionary prism Hydrocarbon gas
Beginning in the 1930s, mud logging became a standard technique on drill rigs worldwide . Besides improving safety during riser drilling, mud logging focuses on formation and reservoir evaluation in real-time . These objectives are accomplished by characterizing the cuttings (i.e. small pieces of the formation) and by analyses of the drilling mud gas composition . Cuttings and drilling mud gas circulate upwards with the drilling mud, where the cuttings are collected at the shale shaker and investigated under the microscope . The gas component is removed from the drilling mud by a degasser, and is then forwarded to the mud gas monitoring unit, where the gas composition is analyzed .
Causes for varying gas concentrations in the drilling mud gas data are difficult to assess, because drilling mud gas is a function of the in situ gas composition, physical and chemical properties of the formation and the drilling mud, and the drilling operation. Gas sources include liberated gas (i.e. gas that is released when the drill bit crushes the rock), produced gas (i.e. gas inflow caused by borehole pressure lower than hydrostatic), atmospheric gas (O2, N2, Ar), and recycled gas (i.e. gas not liberated at the surface when the mud is collected in the mud pits) ,. The amount of liberated gas strongly depends on the porosity and permeability of the penetrated formation, but also on parameters like rate-of-penetration, mud weight, mud flow rate, bit and borehole diameter, and degasser efficiency .
During the last decades, the scientific value of drilling mud gas monitoring was repeatedly highlighted ,,-, and found also its way into the Integrated Ocean Drilling Program (IODP) Nankai Trough Seismogenic Zone Experiment (NanTroSEIZE). During riser drilling with D/V Chikyu, drilling mud gas monitoring was first conducted with third-party tools on IODP Expedition 319 . The third-party installation was later replaced by an onboard scientific drilling mud gas monitoring system (hereafter termed “SciGas system”), which was tested successfully during IODP Exp. 337 for the first time . The SciGas system allows determination of hydrocarbons (methane, ethane, propane, i- and n-butane, propane), stable carbon isotopic composition of methane (δ13CCH4), and non-hydrocarbons (e.g., amongst others, O2, N2, Ar, H2, Xe, He) gases. Tests confirmed that the SciGas system yields accurate δ13CCH4 values (Heuer et al., unpublished data).
The SciGas system is relatively new onboard D/V Chikyu, and with increasing importance of the riser drilling technology for future drilling operations, it is necessary to analyse and evaluate the scientific value and limitations of drilling mud gas monitoring. With this work we hope to support and contribute to future studies working with drilling mud gas data obtained onboard D/V Chikyu.
North-west directed subduction of the Philippine Sea plate (PSP) beneath the Eurasian Plate at a rate of ca. 4.1 – 6.5 cm/yr formed the Nankai Trough accretionary complex ,. The northern part of the PSP comprises sediments from the Shikoku Basin, which formed during backarc spreading of the Izu Bonin Arc ca. 23 Ma ago . Subduction and accretion started around 15 Ma, stopped at ca. 12 Ma and continued ca. 6 Ma -.
Overview of depth intervals for units I to V and subunits at Site C0002
0 - 135.8
135.8 - 826.3
135.8 - 826.3
200 – 505
200 – 505
475 - 512.5
834.0 - 921.7
875.5 – 1025.5
902 - 926.7
875.5 - 975.5
921.7 - 1052.5
1025.5 – 1740.5
1100.5 - 1120
975.5 - 1665.5
1025.5 – 1140.5
1140.5 – 1270.5
1270.5 – 1420.5
1420.5 – 1600.5
1600.5 – 1740.5
1740.5 – 2004.5
1665.5 - 2325.5
1965.5 - 3058.5
Results of shipboard analyses
Results of shorebased analyses
Results for shore-based analysis of drilling mud gas samples
Sample ID 338-C0002F-00
Total depth (mBRT)
lag depth (mbsf)
δD CH4(‰, VSMOW)
Although concentrations of C2-GC are up to four orders of magnitude smaller compared to the concentrations of C1-GC, both components show a similar distribution with depth (Figure 2) and are positively correlated with R = 0.94 (Figure 4). The highest values for C1-GC and C2-GC were found at 1100 mbsf, with 1.03% and 18 ppmv, respectively. Both components experience an overall decrease downhole. C1-GC is hardly correlated with C3-GC (R = 0.25), but shows a slightly negative trend (Figure 2) with minor variations downhole. After C3-GC decreases from 4 to 1 ppmv between 850 and 1200 msbf, it slightly increases again with depth to 3 ppmv.
C1-QMS shows a positive correlation with C1-GC (R = 0.93), and at depths greater 1000 mbsf, both C1-QC and C1-QMS experience similar variations and concentrations with depth (Figure 2A, B). In the depth interval between 900 and 1000 mbsf, however, C1-QMS dominates the gas show with almost 5%, whereas C1-GC decreases to 0.42 ppmv (Figure 4B). This deviation might result from gas depletion in the sample vial after the initial total gas analyses carried out with the QMS. The Bernard parameter (i.e. C1/(C2 + C3), ) varies between 1708 at 900 mbsf and 92 at 1998.2 mbsf, indicating a relative increase in thermogenic components downhole.
The hydrogen isotopic composition of CH4 was uniform; δD-values ranged from -171‰ to -164‰ and averaged around -167 ± 2‰ (Figure 5). The standard deviation of duplicate measurements was on average 2‰.
Comparison between shipboard and shorebased drilling mud gas data
A comparison between shorebased GC, QMS and onboard GC-NGA and Geoservices data  is shown in Figures 2 and 3, and Additional file 1: Figures S1 and S2 in the supplementary material). Above 1300 mbsf, drilling mud gas monitoring by Geoservices showed higher methane and ethane concentrations than GC and QMS (C1-GC, C1-QMS, both on the upper x-axis in Figure 3; C2-GC in Figure 2B). Below 1300 mbsf, concentrations correspond to the real-time values (Figures 2A and 3, Additional file 1: Figure S1). The small data coverage for C3-GC prevents a thorough comparison, and adds to the low correlation in Additional file 1: Figure S1F, but the available shorebased and shipboard C3 concentrations are in the same order of magnitude.
Though shorebased GC-measurements yielded lower methane concentrations than shipboard mud-gas monitoring by SciGas and Geoservices, overall trends are similar in all three data sets (Figure 2A-D; Additional file 1: Figure S1A-D). Ethane and propane, however, show no clear correlation (Additional file 1: Figure S1E, F). By contrast, the Bernard parameter based on online GC-NGA data corresponds with the Bernard parameter from shorebased measurements (Figure 2D, Additional file 1: Figure S1G). Except for an outlier at 1500 mbsf, relative changes in the gas composition are well reproduced by onshore measurements, and give the same qualitative estimation of thermal maturity (Figure 2D).
A comparison between the C1/C2, C1/C3 and C2/C3 ratios of the shipboard (GC-NGA only) and shorebased measurements is given in the supplementary material (Additional file 1: Figure S2). Shipboard and shorebased datasets are well correlated for C1/C2 ratios, (R = 0.87), but deviate considerably from each other with respect to C1/C3 (R = 0.36) and C2/C3 ratios (R = 0.41).
Similar findings arise when comparing the Geoservices data with the shorebased GC data (Figure 3A). While the C1/C2 ratios correspond well with a correlation coefficient of R = 0.95 (by disregarding the single outlier), C2/C3 ratios have a negative correlation with R = −0.5, and C1/C3 ratios show data scatter with R = 0.16 (see Additional file 1: Figure S3 in the supplementary material).
During IODP Exp. 338, the mud-gas monitoring system from Geoservices recorded distinctly higher absolute hydrocarbon gas concentrations than the recently installed SciGas system . The lower gas recovery of the latter are likely due to the technical configuration  that can only be adjusted and optimized during riser drilling operations. As a consequence, relative changes are less pronounced, and differentiation between formation- and/or drilling-related artefacts is more difficult . In addition, the comparison of data sets that result from analyses of discrete samples and continuous on-line monitoring, respectively, is complicated by the synchronization of measurements. This is particularly true for analyses with long run-times. For example, GC-NGA analysis require 20 minutes  and, with drilling proceeding at an average rate of 30 m penetration per hour, interpolate over a corresponding depth range of 10 m. This issue becomes obvious in the low correlation of higher hydrocarbon gases in shorebased and shipboard datasets (see Additional file 1: Figure S1E for ethane and Additional file 1: Figure S1F for propane concentrations, Additional file 1: Figure S2A-C for C1/C2, C2/C3, and C1/C3 ratios). For C2 and C3, concentrations differed significantly between the depths where the gas was sampled for onshore analyses and where the last shipboard measurement took place. For C1, the problems were of minor importance, because concentrations were high and relatively stable.
Ratios of hydrocarbon gases are commonly used to evaluate relative variations, e.g. pixler plots , star/spider diagrams ,, and parameters such as hydrocarbon wetness, balance and character . Most of these methods require reliable estimations of higher hydrocarbons (i.e. C5+), which cannot be derived by conventional degassing methods due to inefficient liberation of higher hydrocarbons. At in situ temperature and pressure, individual gaseous components can be in solution with the drilling fluid and/or the seawater (e.g. -), and the solubility increases with increasing number of hydrocarbon gases . During ascend of the drilling mud, pressure and temperature decrease, which reduces the solubility of the hydrocarbon gases, and increases the potential to be extracted by the degasser. However, due to their boiling points < 0°C, only C1 to C4 remain in gas phase at atmospheric conditions. Efficient extraction of C5+ requires heating of the drilling mud during degassing. Although such instruments exist (e.g., FLAIR, see ) none were available during IODP Expedition 338 . Additionally, our results suggest that simple gas-to-gas ratios are not sufficient to orderly evaluate the SciGas system (Additional file 1: Figures S2 and S3; Additional file 2: Table S1). The relatively good correlation of R = 0.95 with the Geoservices system (Additional file 1: Figure S3A) with respect to the C1/C2 ratios is contrasted with a bad correspondence of C2/C3 and C1/C3 ratios, and thus, the comparison is ambiguous (Additional file 1: Figure S3B, C). Therefore, for a qualitative evaluation, we focus also on the Bernard parameter  and the hydrocarbon wetness, which is expressed as total wet gas fraction (TWG), i.e. (∑ C2 + C3)/(∑ C1 – C3) × 100) ,,-. At a TWG ≤ 5.0%, the gas composition is dominated by methane, either because temperature and time were insufficient to produce higher-order hydrocarbons, or the hydrocarbons are overmature . Our samples show a TWG of ≤ 1.15% and are in good agreement with the TWG derived from shipboard GC-NGA measurements (supplementary material, Additional file 2: Table S1). TWG for the Geoservices data is, with up to 2.4%, more than twice as high as the shorebased GC data, but still below the 5.0% threshold. At depths > 1950 mbsf, all three datasets show an increase in TWG (supplementary material, Additional file 2: Table S1). Individual TWG values imply a good correlation (see supplementary material, Additional file 1: Figure S4A, R = 0.81, Additional file 1: Figure S4B, R = 0.95) and all three datasets confirm the overall absence of wet gas, despite being acquired by different instruments.
Following the results for the TWG and the Bernard parameter, the SciGas as well as the Geoservices datasets allow us to qualitatively evaluate the gas composition despite the different degassing systems. Nonetheless, both the TWG and the Bernard parameter point to generally higher ethane and propane concentrations using the Geoservices degassing system (Figure 6, Additional file 1: Figure S5; Additional file 2: Table S1). Reasons for the underestimation of ethane and propane with the SciGas system are manifold. Most likely, the configuration of the SciGas degasser caused insufficient gas liberation from the drilling mud . At times of low mud pump activity, the mud level in the flow line declined. Contrary to the degassing system from Geoservices, it was impossible to adjust the SciGas degasser in height in real-time. This caused insufficient stirring of the drilling mud, thus the gas phase was less efficiently liberated and more likely to be contaminated by atmospheric gases. Consequently, the SciGas only detected concentrated gases, which degass readily without further stimulation.
Origin of gases
At depths greater 1950 mbsf, the Bernard parameter, the δD-δ13CCH4 plot and the TWG ratios point to a relative increase in thermogenic gases (Figures 5 and 6, Additional file 1: Figure S4). At the same time, no wet gas composed of C2+ > 5% (i.e., > 50000 ppmv; e.g., ) was encountered (Figures 2 and 3; Table 1). Wet gas is generated at elevated thermal maturity, which can be evaluated using vitrinite reflectance Ro (, and references therein). The latter is estimated by the shipboard δ13CCH4 values using the empirical relationship δ13CCH4 (‰) = 15.4 log10 %Ro - 41.3 (, and references therein). Computing the vitrinite reflectance led to values below 0.6, i.e. below a maturation indicative for the onset of the oil and gas window (supplementary material, Additional file 2: Table S1).
In general, the C1/C2-TOC-temperature relationship is based on the assumption that the hydrocarbon gases were produced in situ . Therefore, migration of thermogenic gases and mixing with hydrocarbon gases that were produced in situ easily compromises the interpretation derived by the C1/C2-TOC-temperature relationship. At the same time, the temperature estimate is easily influenced by the degasser configuration and the drilling operation, mainly due to the selective detection of C2 (cf. section “Technical Considerations”). For these reasons and given the small amount of data points, it might be misleading to discuss the individual temperature gradients separately. Applying a simple linear fit to both datasets points to an in situ temperature between 81°C and 85°C (Figure 7) at 2000 mbsf, which is in agreement with the estimations provided by . Although hydrocarbon generation already starts at 50°C, higher hydrocarbons are usually encountered at temperatures > 100°C (e.g., ).
Temperature and time intervals for calculating the time-temperature index
Temp. interval (°C)
0 - 10
10 - 20
20 - 30
30 - 40
40 - 50
50 - 60
60 - 70
70 - 80
80 - 82
Consequently, following our estimations for R0, in situ temperature and the TTI, in situ production of significant amounts of higher hydrocarbons is unlikely at depths < 2000 mbsf. Beside in situ production, gases tend to follow the pressure gradient and migrate in adjacent rocks along faults or fractures, or via inter-granular diffusion. For shallower gas accumulations, this can lead to mixing of biogenic and thermogenic gas. The TWG allows first qualitative estimations, but identifying secondary effects such as mixing remains difficult. Indeed, the Bernard diagram points to a gas composition, which is affected by mixing rather than showing a clear biogenic or thermogenic signal (Figure 6). Mixing can occur in different ways, either due to active gas migration along faults or fractures, or the gas mixture was derived by diffusive migration leading to isotope fractionation . For methane, diffusive migration would lead to an enrichment of the light carbon isotope, and thus, the migrated gas would plot in the biogenic or mixed regime despite being derived from a thermogenic source .
At Site C0002, a fault zone is indicated between 1500 and 1640 mbsf based on resistivity data obtained during logging-while-drilling . This corresponds to an increase in TWG of the Geoservices and the shorebased dataset at 1600 mbsf, pointing to active or recently active migration of higher hydrocarbons from greater depths and subsequent mixing (Additional file 2: Table S1). Detailed analyses of possible gas migration and mixing will be covered in future studies evaluating data from the recently finished IODP Exp. 348 using noble gas isotopes from Holes C0002F and C0002N.
In conclusion, shipboard and shorebased analyses allow the same qualitative estimation about the genetic origin of the drilling mud gas. Differences in absolute concentrations of the SciGas and Geoservices degassing systems are most likely caused by the different configurations of the individual degassers, which led to an underestimation of higher hydrocarbons when using the SciGas system. Comparison of the individual datasets by simple gas ratio analysis was ambiguous, therefore we chose the Bernard parameter and the total wet gas ratio to qualitatively analyze and compare the individual datasets. Eventually, we showed that, beside the technical problems encountered during IODP Exp. 338, the SciGas system produced reliable data, which helped to qualitatively estimate temperature, maturity, and possible mixing of the hydrocarbon gases. We found that microbial methane was present to up to 1600 mbsf, with thermogenic gas production probably not starting at depths shallower 2000 mbsf. Consequently, the SciGas system onboard D/V Chikyu is suitable for detecting qualitative changes, and allows a first estimation of the contribution of biogenic and thermogenic hydrocarbon gas.
While position and configuration of the degasser of the SciGas system precluded any height adjustment (Figure 8, position D1), the extracted drilling mud gas was subject to a broader range of measurements. After having bypassed the sampling line, the gas was dried with a mist and moisture remover . For δ13CCH4 analysis isotope fractionation potentially caused by the mist and moisture remover is negligible . Afterwards, the gas composition was first analyzed by a methane carbon isotope analyzer (MCIA), followed by a GC-natural gas analyzer (GC-NGA), a detector that counts radioactive decay of radon, and a process gas mass spectrometer (PGMS) (for detailed information about the instruments and measurement specifications, please see ).
In this manuscript, shipboard data used for further evaluation of and comparison with the shorebased data include the MCIA and GC-NGA datasets. Precision (expressed as relative standard deviation, RSD) of measurements with the MCIA and GC-NGA were 0.4% and 1.4 – 1.5% RSD, respectively. The data produced by Geoservices will be included as well to highlight the differences of the Geoservices and SciGas monitoring systems. δ13CCH4 values are reported in notion to the Vienna Peedee belemnite (VPDB) standard in parts per mil (‰) .
Drilling Mud Gas sampling and analyses
During IODP Exp. 338, before being analyzed by onboard instruments, the gas phase flowed through a third-party sampling line and the onboard Isotube sampling system . Sampling took place between 850 and 1998.5 mbsf using glass flasks and copper (Cu) tubes for the third-party flow line, and Isotubes for the Isotube system (Table 2). All samples were taken before the gas passed the mist and moisture remover (Figure 8).
In total, 23 of the drilling mud gas samples collected during IODP Exp. 338  were subject to shore-based analyses by the QMS (Pfeiffer Omnistar) and the GC (SRI-8610) equipped with a Haysep D column and a flame ionization detector. Detection of methane with the QMS is often subject to isobaric interference with 16O, therefore we focused on m/z = 15. The signal strength was still 85%, which allowed the measurement of relative changes in the gas concentrations. For both the QMS and the GC, the detection limit for hydrocarbon gases was set to 1 parts per million by volume (ppmv). The relative errors for the QMS and QC measurements are listed in Additional file 3: Table S2.
Stable hydrogen isotope analysis of methane
Out of the 23 samples taken, 14 were subject to hydrogen isotope analysis. Methane concentrations were high enough for reliable stable hydrogen isotope analysis in 12 of the 14 samples taken (Table 2). Prior to the analysis, samples were given time to adjust to room temperature. The stable hydrogen isotopic composition of CH4 was analyzed by isotope ratio monitoring gas chromatography/mass spectrometery (irm-GC/MS) using a Thermo Finnigan Trace Ultra GC, connected to a Thermo Finnigan DELTA V Plus mass spectrometer via Thermo Finnigan GC-Isolink interface as reported previously . The analysis involved online transfer of samples from a high temperature conversion reactor (containing an empty ceramic tube covered with graphite layer that was kept at a temperature of 1440°C) in which compounds were pyrolyzed to molecular hydrogen, carbon, and carbon monoxide, prior to their transfer into the mass spectrometer via Conflow IV interface. The Trace Ultra GC was equipped with a Carboxen column (30 m length, 0.32 mm inner diameter). The carrier gas was helium (1.2 mL min−1), the split ratio 1:8, and the temperature of the GC oven and injector were 60°C (isotherm) and 200°C, respectively. The primary standardization of the DELTA V Plus was based on multiple (three to six) injections of reference H2 from a lab tank (δD = -96.4 ± 0.3‰ vs VSMOW, 3.2 ± 0.3 V at m/z 2) at the beginning and end of the analysis of each sample. Lab tank H2 was calibrated against the certified CH4 standard T-iso2 (2.5 vol% CH4 in a balance of dry, synthetic air; δ 13CCH4 = -38.3 ± 0.2‰ vs VPDB; δDCH4 = −138‰ vs VSMOW). We assessed the precision of our analysis by repeated analysis of the standard. The precision was better than 2‰ (1σ). Stable hydrogen isotope analysis of methane requires a peak amplitude of 1 V or higher at m/z 2. Depending on CH4 concentration, ~300 μL to ~3000 μL of sample were injected per analysis. All analyses were carried out in duplicate.
Stable hydrogen isotope ratios are reported in δD notation (per mil, ‰) relative to the Vienna Standard Mean Ocean Water (VSMOW), with δD = [(Rsample-RVSMOW)/RVSMOW] · 103, where R = 2H/1H and RVSMOW = (155.76 ± 0.05) × 10−6 .
Samples and/or data were provided by IODP. Funding was provided by IODP Germany. Special thanks belongs to Sean Toczko, Lena Maeda, the Chikyu laboratory technicians of Marine Works Japan, the shipboard crew of Mantle Quest Japan, and the rest of the crew onboard D/V Chikyu for providing excellent support during IODP Expedition 338. Yusuke Kubo is acknowledged for significantly improving the drilling mud gas system onboard D/V Chikyu. The authors also want to thank Ana Maia from Cardiff University for valuable and constructive discussions. Kai-Uwe Hinrichs kindly provided the resources for stable isotope analyses at MARUM.
- Ablard P, Bell C, Cook D, Fornasier I, Poyet J-P, Sharma S, Fielding K, Lawton G, Haines G, Herkommer MA, Mccarthy K, Radakovic M, Umar L: The expanding role of Mud logging. Oilf Rev. 2012, 24: 24-41.Google Scholar
- Erzinger J, Wiersberg T, Zimmer M: Real-time mud gas logging and sampling during drilling. Geofluids. 2006, 6: 225-233.Google Scholar
- Hammerschmidt S, Toczko S, Kubo Y, Wiersberg T, Fuchida S, Kopf A, Hirose T, Saffer D, Tobin H, the Expedition 348 Scientists: Influence of drilling operations on drilling mud gas monitoring during IODP Exp. 338 and 348 [abstract]. Geophysical Research Abstracts EGU General Assembly 2014, 16E:EGU2014-5904. http://meetingorganizer.copernicus.org/EGU2014/EGU2014-5904.pdf.
- Hilton DR, Craig H: The Siljan deep well: helium isotope results. Geochim Cosmochim Acta. 1989, 53: 3311-3316. 10.1016/0016-7037(89)90110-5.View ArticleGoogle Scholar
- Aquilina L, Baubron J-C, Defoix D, Dégranges P, Disnar J-R, Marty B, Robé M-C: Characterization of gases in sedimentary formations through monitoring during drilling and core leaching (Balazuc borehole, deep geology of France programme). Appl Geochem. 1998, 13: 673-686. 10.1016/S0883-2927(98)00008-0.View ArticleGoogle Scholar
- Ellis L: Mud gas isotope logging (MGIL) assists in oil and gas drilling operations. Oil Gas J. 2003, 101: 32-41.Google Scholar
- Ellis L, Berkman T, Uchytil S, Dzou L: Integration of mud gas isotope logging (MGIL) with field appraisal at horn mountain field, deepwater gulf of Mexico. J Pet Sci Eng. 2007, 58: 443-463. 10.1016/j.petrol.2007.03.001.View ArticleGoogle Scholar
- Erzinger J, Wiersberg T, Dahms E: Real-time mud gas logging during drilling of the SAFOD Pilot Hole in Parkfield, CA. Geophys Res Lett 2004, 31:L15S18.,Google Scholar
- Wiersberg T, Erzinger J: A helium isotope cross-section study through the San Andreas Fault at seismogenic depths. Geochem Geophys Geosyst 2007, 8:Q01002.,Google Scholar
- Wiersberg T, Erzinger J: Origin and spatial distribution of gas at seismogenic depths of the San Andreas Fault from drill-mud gas analysis. Appl Geochemistry. 2008, 23: 1675-1690. 10.1016/j.apgeochem.2008.01.012.View ArticleGoogle Scholar
- Wiersberg T, Erzinger J: Chemical and isotope compositions of drilling mud gas from the San Andreas Fault Observatory at Depth (SAFOD) boreholes: Implications on gas migration and the permeability structure of the San Andreas Fault. Chem Geol. 2011, 284: 148-159. 10.1016/j.chemgeo.2011.02.016.View ArticleGoogle Scholar
- Expedition 319 Scientists: Site C0009. Proc IODP 319. Edited by: Saffer D, McNeill L, Byrne T, Araki E, Toczko S, Eguchi N, Takahashi K. 2010, Integrated Ocean Drilling Program Management International, Inc, Tokyo, doi:10.2204/iodp.proc.319.104.2010Google Scholar
- Inagaki F, Hinrichs K-U, Kubo Y, the Expedition 337 Scientists: Deep coalbed biosphere off Shimokita - microbial processes and hydrocarbon system associated with deeply buried coalbed in the ocean. IODP Prel Report 2013, 337. doi:10.2204/iodp.pr.337.2012.,Google Scholar
- Screaton EJ, Kimura G, Curewitz D, the Expedition 316 Scientists: Expedition 316 Summary. Proc IODP 316. Edited by: Kinoshita M, Tobin H, Ashi J, Kimura G, Lallemant S, Screaton EJ, Curewitz D, Masago H, Moe KT. 2009, Integrated Ocean Drilling Program Management International, Inc, Washington D.C., doi:10.2204/iodp.proc.314315316.131.2009Google Scholar
- Seno T, Stein S, Gripp AE: A model for the motion of the Philippine Sea plate consistent with NUVEL-1 and geological data. J Geophys Res 1993, 98:8.,Google Scholar
- Miyazaki S, Heki K: Crustal velocity field of southwest Japan: subduction and arc-arc collision. J Geophys Res. 2001, 106: 4305-4326. 10.1029/2000JB900312.View ArticleGoogle Scholar
- Okino K, Ohara Y, Kasuga S, Kato Y: The Philippine Sea: New survey results reveal the structure and the history of the marginal basins. Geophys Res Lett. 1999, 26: 2287-2290. 10.1029/1999GL900537.View ArticleGoogle Scholar
- Taira A, Hill I, Firth J, Berner U, Brückmann W, Byrne T, Chabernaud T, Fisher A, Foucher J-P, Gamo T, Gieskes J, Hyndman R, Karig D, Kastner M, Kato Y, Lallemant S, Lu R, Maltman A, Moore G, Moran K, Olaffson G, Owens W, Pickering K, Siena F, Taylor E, Underwood M, Wilkinson C, Yamano M, Zhang J: Sediment deformation and hydrogeology of the Nankai Trough accretionary prism: Synthesis of shipboard results of ODP Leg 131. Earth Planet Sci Lett. 1992, 109: 431-450. 10.1016/0012-821X(92)90104-4.View ArticleGoogle Scholar
- Taira A: Tectonic evolution of the Japanese Arc system. Annu Rev Earth Planet Sci. 2001, 29: 109-134. 10.1146/annurev.earth.29.1.109.View ArticleGoogle Scholar
- Kimura G, Hashimoto Y, Kitamura Y, Yamaguchi A, Koge H: Middle Miocene swift migration of the TTT triple junction and rapid crustal growth in southwest Japan — a review. Tectonics. 2014, 33: 1219-1238. 10.1002/2014TC003531. doi:10.1002/2014TC003531View ArticleGoogle Scholar
- Strasser M, Moore GF, Kimura G, Kitamura Y, Kopf AJ, Lallemant S, Park J-O, Screaton EJ, Su X, Underwood MB, Zhao X: Origin and evolution of a splay fault in the Nankai accretionary wedge. Nat Geosci. 2009, 2: 648-652. 10.1038/ngeo609.View ArticleGoogle Scholar
- Expedition 315 Scientists: Site C0002. Proc IODP 314/315/316. Edited by: Kinoshita M, Tobin H, Ashi J, Kimura G, Lallemant S, Screaton EJ, Curewitz D, Masago H, Moe KT. 2009, Integrated Ocean Drilling Program Management International, Inc, Washington D.C., doi:10.2204/iodp.proc.314315316.124.2009Google Scholar
- Strasser M, Dugan B, Kanagawa K, Moore GF, Toczko S, Maeda L, the Expedition 338 Scientists: Site C0002 . Proc IODP 338. Edited by: Strasser M, Dugan B, Kanagawa K, Moore GF, Toczko S, Maeda L. 2014, Integrated Ocean Drilling Program Management International, Inc, Tokyo, doi:10.2204/iodp.proc.338.103.2014,Google Scholar
- Scientists E 348, Participants S: Expedition 348 preliminary report NanTroSEIZE stage 3: NanTroSEIZE plate boundary deep riser 3. IODP Prelim Rep 2014, 348:71.,Google Scholar
- Strasser M, Dugan B, Kanagawa K, Moore GF, Toczko S, Maeda L, the Expedition 338 Scientists: Methods. Proc IODP 338. Edited by: Strasser M, Dugan B, Kanagawa K, Moore GF, Toczko S, Maeda L. 2014, Integrated Ocean Drilling Program Management International, Inc, Tokyo, doi:10.2204/iodp.proc.338.102.2014Google Scholar
- Whiticar MJ: Correlation of Natural Gases with Their Sources. The Petroleum System - From Source to Trap. Edited by: Magoon L, Dow W. 1994, AAPG, Tulsa, Oklahoma, USA, 261-283.Google Scholar
- Bernard BB, Brooks JM, Sackett WM: Light hydrocarbons in recent Texas continental shelf and slope sediments. J Geophys Res Ocean. 1978, 83: 4053-4061. 10.1029/JC083iC08p04053.View ArticleGoogle Scholar
- Pixler BO: Formation evaluation by analysis of hydrocarbon ratios. J Pet Technol. 1969, 21: 665-670. 10.2118/2254-PA.View ArticleGoogle Scholar
- Prinzhofer A, Mello MR, Takaki T: Geochemical characterization of natural Gas: a physical multivariable approach and its applications in maturity and migration estimates. Am Assoc Pet Geol Bull. 2000, 84: 1152-1172.Google Scholar
- Dessay J, Torres O, Sharma S: Real Time Formation Characterization from Advanced Mud Gas Analyses for Improved Geological Operations Decisions [extended abstract]. In 73rd EAGE Conf Exhib. Vienna, Austria: 2011. abstract # DO22, doi:10.3997/2214-4609.20149082.Google Scholar
- Haworth J, Sellens M, Whittaker A: Interpretation of hydrocarbon shows using light ( C1–C5) hydrocarbon gases from Mud-Log data. Am Assoc Pet Geol Bull. 1985, 69: 1305-1310.Google Scholar
- Dhima A, de Hemptinne J-C, Moracchini G: Solubility of light hydrocarbons and their mixtures in pure water under high pressure. Fluid Phase Equilib. 1998, 145: 129-150. 10.1016/S0378-3812(97)00211-2.View ArticleGoogle Scholar
- Chapoy A, Mokraoui S, Valtz A, Richon D, Mohammadi AH, Tohidi B: Solubility measurement and modeling for the system propane–water from 277.62 to 368.16 K. Fluid Phase Equilib. 2004, 226: 213-220. 10.1016/j.fluid.2004.08.040.View ArticleGoogle Scholar
- Reddy CM, Arey JS, Seewald JS, Sylva SP, Lemkau KL, Nelson RK, Carmichael CA, McIntyre CP, Fenwick J, Ventura GT, Van Mooy BAS, Camilli R: Composition and fate of gas and oil released to the water column during the deepwater horizon oil spill. Proc Natl Acad Sci. 2012, 109: 20229-20234. 10.1073/pnas.1101242108.View ArticleGoogle Scholar
- James AT: Correlation of natural gas by use of carbon isotopic distribution between hydrocarbon components. Am Assoc Pet Geol Bull. 1983, 67: 1176-1191.Google Scholar
- Schoell M: Genetic characterization of natural gases. Am Assoc Pet Geol Bull. 1983, 67: 2225-2238.Google Scholar
- Abrams MA: Significance of hydrocarbon seepage relative to petroleum generation and entrapment. Mar Pet Geol. 2005, 22: 457-477. 10.1016/j.marpetgeo.2004.08.003.View ArticleGoogle Scholar
- Schoell M: The hydrogen and carbon isotopic composition of methane from natural gases of various origins. Geochim Cosmochim Acta. 1980, 44: 649-661. 10.1016/0016-7037(80)90155-6.View ArticleGoogle Scholar
- Whiticar MJ: Carbon and hydrogen isotope systematics of bacterial formation and oxidation of methane. Chem Geol. 1999, 161: 291-314. 10.1016/S0009-2541(99)00092-3.View ArticleGoogle Scholar
- Heuer VB, Pohlman JW, Torres ME, Elvert M, Hinrichs K-U: The stable carbon isotope biogeochemistry of acetate and other dissolved carbon species in deep subseafloor sediments at the northern Cascadia Margin. Geochim Cosmochim Acta. 2009, 73: 3323-3336. 10.1016/j.gca.2009.03.001.View ArticleGoogle Scholar
- Lopatin NV: Temperature and geologic time as factors in coalification. Izv Akad Nauk SSSR, Ser Geol. 1971, 3: 95-106.Google Scholar
- Waples D: Time and temperature in petroleum formation: application of Lopatin’s method to petroleum exploration. Am Assoc Pet Geol Bull. 1980, 64: 916-926.Google Scholar
- Harris RN, Schmidt-Schierhorn F, Spinelli G: Heat flow along the NanTroSEIZE transect: Results from IODP Expeditions 315 and 316 offshore the Kii Peninsula, Japan. Geochem Geophys Geosystems 2011, 12:Q0AD16.,Google Scholar
- JOIDES PPSP: Ocean drilling guidelines for pollution prevention and safety. JOIDES J. 1992, 18: 1-30.Google Scholar
- Seewald JS: Organic–inorganic interactions in petroleum-producing sedimentary basins. Nature. 2003, 426: 327-333. 10.1038/nature02132.View ArticleGoogle Scholar
- Killops SD, Killops VJ: Introduction to Organic Geochemistry. 2005, Blackwell Publishing Ltd, Oxford, UKGoogle Scholar
- Underwood MB, Saito S, Kubo Y, the Expedition 322 Scientists: Expedition 322 Summary. Proc. IODP 322. Edited by: Saito S, Underwood MB, Kubo Y. 2010, Integrated Ocean Drilling Program Management International, Inc, Tokyo, doi:10.2204/iodp.proc.322.101.2010Google Scholar
- Marcaillou B, Henry P, Kinoshita M, Kanamatsu T, Screaton E, Daigle H, Harcouët-Menou V, Lee Y, Matsubayashi O, Kyaw Thu M, Kodaira S, Yamano M, Expedition 333 Scientists: Seismogenic zone temperatures and heat-flow anomalies in the Tonankai margin segment based on temperature data from IODP expedition 333 and thermal model. Earth Planet Sci Lett. 2012, 349–350: 171-185. 10.1016/j.epsl.2012.06.048.View ArticleGoogle Scholar
- Prinzhofer A, Pernaton É: Isotopically light methane in natural gas: bacterial imprint or diffusive fractionation?. Chem Geol. 1997, 142: 193-200. 10.1016/S0009-2541(97)00082-X.View ArticleGoogle Scholar
- Gonfiantini R: Standards for stable isotope measurements in natural compounds. Nature. 1978, 271: 534-536. 10.1038/271534a0.View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.