Estimation of the Relative Contributions of Different Hydrocarbon Charges to the Sw Qaidam Basin Accumulations Using Micro-Spectroscopy Analysis of Petroleum Inclusions
Bibliographic record
Abstract
Abstract In a series of paper, the characteristics of petroleum inclusions described by ?max from the UV and CH2/CH3 ratio from the FT-IR spectra. On the basis of optical microscopic, microthermometric, fluorescence spectroscopic and FT-IR spectroscopic analyses three types of hydrocarbon inclusions are identified in the study area: namely yellow fluorescencing oil inclusions,blue fluorescencing oil inclusions andgas inclusions, representing two episodes of oil charges and one gas charge possibly related to readjustment of the associated gases down dip. The first episode of oil charge is represented by the predominantly yellow fluorescencing oil inclusions trapped prior to the quartz overgrowth, whereas the second episode is marked by the blue fluorescencing fluid inclusions occurred after the precipitation of dolomite. Both the UV fluorescence and the FT-IR spectra show two distinct oil inclusion groups (yellow and blue) with ?max at 540 nm and 475 nm, respectively and corresponding CH2/CH3 ratios of 1.2 and 2.3, respectively. Microthermometric data indicate that the two groups of oil inclusions have different homogenisation temperatures (Th), corresponding to oil charge around 25 Ma and 10 Ma, respectively for the Gasi and Hongliuquan oilfields, 10 Ma and 5 Ma, respectively for the Yingdong Oilfield, SW Qaidam Basin. The yellow fluorescencing oil inclusions have relatively low maturity and API gravity compared with the blue fluorescencing ones. The current accumulations in the oilfields have maturity and API gravity similar to that of the yellow fluorescencing inclusions. It is concluded that the earlier hydrocarbon charge is thus the predominant contribution to the current accumulations. Introduction Hydrocarbon inclusions are minute petroleum fluids trapped during reservoir diagenesis [1–6]. They provide pristine compositional information of the hydrocarbons present at the time of charge that may offer important clues for understanding hydrocarbon charge history and reservoir fluid evolution. Hydrocarbon inclusions are currently being extensively used to investigate hydrocarbon charge timing and bulk physio-chemical compositions. Due to the minute amount of the fluids within individual inclusions and the complicated extraction procedure, despite of a number of attempts by various authors, so far there is no reported successful case on differentiating the physio-chemical compositions among individual inclusions that may represent different charges using GCMS. In this paper we report detailed characterisation of individual petroleum inclusions using micro-spectroscopy that recently pioneered by Pradier et al. In a series of paper, the micro-spectroscopic analytical methods include both the UV fluorescence spectroscopy and FT-IR spectroscopy. Parameters derived from the micro-spectroscopy such as ?max from the UV fluorescence spectra and CH2/CH3 ratio from the FT-IR spectra can be used to determine the characteristics of the physio-chemical compositions of individual petroleum inclusions including aromatic content, thermal maturity and API gravities with proper calibrations. The TSF parameter is uesd to describe the feature of oil and hydrocarbon inclusion, the R1 parameter is a ratio between TSF emission intensity at 360nm and 320nm at a Excitation wavelength of 270nm, R has closely related to the API and maturity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".