Acid-Extracted Hydrocarbon Anomalies and Significance in the Chaoshan Depression of the Northern South China Sea

Abstract

To predict the favorable zones and the types of reservoirs, acid extraction has been used in the Chaoshan depression to detect trace amounts of light hydrocarbons, heavy hydrocarbons, and the δ ¹³C (‰) of methane. As a result, two integration anomalous zones for exploration activity were blocked out in the northeastern and southwestern parts of the Chaoshan Depression, respectively. By analyzing the differentiation law and structural characteristics of hydrocarbon gases, as well as the stable carbon isotope ratio of methane, the underlying reservoirs were predicted to be gas reservoirs, and the seismically interpreted Dongsha-A (DS-A) structure was predicted to be a gas-rich structure. By correlating the seismic profile and geochemical anomalies, it was determined that fault planes and micro-fractures are the main controlling factors for the occurrence of the seabed’s geochemical anomalies. A composite formation mechanism of “lower generation, upper accumulation and micro fractures leaking” is proposed for the control of the underlying petroleum reservoirs, as well as for the micro-fracture control of permeability and surface adsorption control. Acid-extracted hydrocarbon anomalies have favorable indicating significance for exploration activity.

1. Introduction

The Chaoshan Depression is a Mesozoic residual depocenter in the northeast of the South China Sea. The deposit has favorable exploration activity potential but complex oil and gas accumulation. Accurate identification of favorable exploration areas and reservoirs is the key to successful exploration. Drilling data in the South China Sea reveal a marine Mesozoic development [1], making it an ideal area for studying fossils in the South China Sea. The tectonic framework of the South China Sea exerts strong control over the expansion and evolution of the Cenozoic South China Sea, and also determines the generation, migration, accumulation, and preservation processes of oil and gas. Understanding the geological structure of fossils in the South China Sea is of great significance for a comprehensive understanding of the Southeast Asian marginal seas, especially regarding the Mesozoic and Neozoic tectonic evolution of the South China Sea. The Chaoshan Depression is a Mesozoic and Cenozoic superimposed depression in the northern South China Sea (Figure 1), characterized by polyphase basin formation and structural transformation. It developed thick marine Mesozoic strata and has strong potential for exploration activity [2,3,4]; however, oil and gas have not yet been discovered in this region through drilling. The physical properties of the South China Sea’s Mesozoic reservoir are complex and the predrilling predictions do not match the results of LF35-1-1 [5,6,7,8,9]. In recent years, extensive investigations and studies have been conducted in this area, and a lot of trapped structures rich in organic matter have been discovered [10,11,12,13]. To ensure further successful exploration, the effective identification and prediction of favorable exploration areas and petroleum reservoirs is key.

Micro-leakage in oil and gas reservoirs are a common natural phenomenon and form geochemical anomalies on the land surface or the seafloor. Geochemical anomalies in seafloor samples can be used to quickly delineate favorable exploration zones in underexplored basins.

Surface geochemistry (SG) is a rapid method for predicting favorable zones of exploration activity and the types of petroleum reservoirs. Driven by the pressure of oil and gas, petroleum migrates upward along complex micro-fractures, fault planes, and other migration channels in the form of micro-bubbles or continuous gas phases. These hydrocarbons are adsorbed by clay minerals and encapsulated by secondary carbonates. As a result, the adsorbed hydrocarbon anomalies corresponding to the underlying reservoir accumulate in the seafloor sediments above the reservoirs. By detecting such anomalies, potential reservoirs can be predicted. Based on the direct correlation between latent petroleum reservoirs and the hydrocarbon concentrations of the gas adsorbed in sea bed sediments, the hydrocarbons’ internal composition can be used to reliably forecast the properties of the migrated hydrocarbons and forecast the development characteristics of the underlying petroleum reservoir and distinguish its overall properties [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28].

Marine SG mainly employs the analysis of gaseous alkanes (C₁–C₅) present in seabed sediments to predict the characteristics of the underlying petroleum reservoir [29]. These bound gases are believed to be attached to organic and/or mineral surfaces, which are entrapped in water structures or authigenic carbonate inclusions. Horvitz (1981, 1985) pioneered the concept of bound sediment gas analysis with his method of acid-extraction adsorbed gas analysis [30,31]. Migrated thermogenic hydrocarbon gases readily bind to near-surface fine-grained sediments (e.g., clays) due to the highly adsorptive nature of these sediments towards hydrocarbons. He also believed there was a preferential adsorption of the migrating thermogenic hydrocarbons relative to the in situ-derived microbial gases. Whiticar (2002) describes how structured water creates a relatively impermeable membrane of organized water molecules that entrap the migrated thermogenic gases, and the in situ-generated interstitial microbial gases will have little or no exchange with the entrapped/sorbed phase [32]. He describes a contiguous coating or network of structured water whereby thermogenic hydrocarbons will migrate vertically within the sedimentary column in a contiguous structured water network, a process known as “handshake migration” [29].

However, gaseous alkanes can also be affected by factors such as disturbances to seabed microorganisms and the interference of biogenic methane, which increases the difficulty of predicting the location of underlying petroleum reservoirs and exploration risks. Therefore, analyzing and identifying whether hydrocarbon anomalies in seafloor sediments originate from the hydrocarbons of the underlying petroleum reservoir is an important factor in predicting the success or failure of oil and gas traps, keeping in mind that the near-surface petroleum seepage signature can be generated from microbial as well as thermogenic sources. This study qualitatively and quantitatively analyzes the acid-extracted hydrocarbon anomalies in the Chaoshan Depression in the northeast of the South China Sea. Using anomalies in the abundance, structure, and distribution characteristics of light and heavy hydrocarbons, this study predicts the attributes of the Mesozoic Petroleum system. The findings delineate the northeastern and southwestern parts of the Chaoshan Depression as comprehensive anomalous zones for oil and gas exploration, and these are also the most favorable prospective oil and gas areas. The DS-A structure is determined as being a predominantly gas-bearing reservoir.

2. Geological Setting

The Dongsha Sea is an area in the northeast of the South China Sea comprising of thick Mesozoic strata, and the Chaoshan Depression is the largest residual depression in the area (Figure 1). The depression has undergone six stages of tectonic evolution in the Mesozoic and Cenozoic eras: (1) In the late Triassic rifting period, semi enclosed bay began to develop in the Mesozoic basin in the northeast of South China Sea; (2) During the Jurassic depression period, the largest scale transgression occurred, and the basin expanded to its maximum extent; (3) In the Late Jurassic tectonic uplift period, compaction fold and structural unconformity occurred under compression; (4) In the Early Cretaceous re-subsidence period, volcanic debris, lava flows, and continental margin debris began to rapidly fill and deposit in the basin; (5) In the Late Cretaceous tectonic inversion period, under the influence of four episodes of the Yanshan movement, the Chaoshan Depression was uplifted and denuded again, forming the second regional unconformity; and (6) In the Neogene regional thermal subsidence period, the central basin of the South China Sea reached its peak of expansion during the Miocene, and the Cenozoic basins in the northern continental margin of the South China Sea successively entered a stage of post-rift depression evolution; large-scale transgression also occurred, mainly accepting coastal and shallow marine deposits [33,34,35,36,37,38]. The DS-A structure is located in the M-low bulge and is a fault anticline structure (Figure 1), controlled by NE-, NNE-, and NW-trending faults.

The 1005–1369 m interval of LF35-1-1 is a Cretaceous sandstone mudstone interval and the 1369–1698 m interval contains Cretaceous tuff. The 1698–2412 m interval is Jurassic sandstone and mudstone, in which the 1698–1940 m interval is grayish-black laminated mudstone and argillaceous siltstone mixed with siliceous rock, containing a small amount of micrite limestone and pyroclastic materials. The 1940–2412 m interval is grayish-black laminated mudstone and argillaceous siltstone mixed with sandstone and limestone. The mudstone is rich in organic debris. Radiolarian fossils were found in the 1716 m to 1839 m interval, indicating a deep-water environment, dating back to the late Jurassic. Fossils of benthic foraminifera were found in the 2049–2112 m interval, indicating a shallow tropical marine environment. Spore and pollen fossils can be found in the 2187 m to 2268 m interval, mainly consisting of a combination of Carassous pollen and Alsophila spinulosa spores. This set of spore and pollen fossils appeared in the Middle and Upper Jurassic period of southern China, indicating a coastal swamp environment [1]. A granite granodiorite intrusion with a small amount of diorite appears in the well interval below 2412 m, and its invasion period is mainly in the Late Cretaceous.

Well LF35-1-1 reveals two source rock strata in the 1940–2022 m interval and the 2100–2412 m interval, wherein the 1940–2022 m rock is poor-to-medium source, and the 2100–2400 m rock is medium-to-good source. The organic matter of these two source rocks is mainly of type III and a small amount of type II2, which are stable in a considerable range. The minimum thickness of a single layer of source rock is 6 m, the maximum thickness is >40 m, and the average thickness is about 20 m. The average thickness of the single layer of the lower source rock is greater than the upper layer. The results of well seismic tracking and further research and comparisons of regional geology show that there are two sets of source rock developed in the Chaoshan Depression, including the upper Triassic–lower Jurassic shallow sea bathyal mudstone and lower Jurassic shallow sea shelf facies mudstone. According to the drilling strata of well LF35-1-1 and seismic data, there are two sets of reservoirs developed in the DS-A structure in the Upper and Middle Jurassic series, respectively. Among them, the top of the Middle Jurassic series is a set of stable shallow sea shelf facies reef limestone with thickness, while the Upper Jurassic is a set of basin floor fan sandstones (Figure 2).

3. Sampling and Methods

The samples used are sourced from the petroleum surveys of 200 stations collected by the Guangzhou Marine Geological Survey in the Dongsha Sea Area in recent years (Figure 1). Sampling grid points with a size of 8 km × 16 km are mainly distributed in the Chaoshan Depression. Samples at some grid points could not be collected due to the presence of submarine cables. Moreover, due to the large number of submarine optical cables in this area, sampling is limited by cable protection requirements, making it impossible to conduct encrypted investigations and detailed target investigations. The samples were collected using an open barrel gravity corer, with a length of 1.3 m. Sediment samples were taken at a depth of 85 cm–100 cm from the top of the columnar sample, acid extraction was performed on the hydrocarbon content, and δ13C (‰) testing and analysis was performed as well.

Acid-extraction hydrocarbon testing was performed as follows: under vacuum conditions and constant temperature, the hydrocarbons (mainly adsorbed hydrocarbons) present in the carbonate mineral lattice and its cement in the sample were separated by means of pressure reduction, heating, and chemical treatment (acid addition). The content of acid-extracted hydrocarbons was detected using a gas chromatography instrument.

Before formally measuring the test material, the standard gas was measured 3–5 times. Only when the relative error of the standard gas measurement was ≤3% could the test material be measured. During the measurement process, it was necessary to regularly check the controlled status of the instrument with standard gas.

The procedure for GC testing is as follows: First, 500 μL ± 0.5 μL of gas was accurately extracted using a 1 mL syringe. The gas was quickly injected into the gas chromatograph. The measuring instrument was then started, chromatograph charts were drawn, and the data were collected. After the chromatographic peak was reached and the recombination components were “driven” at high temperature according to the set temperature program, qualitative and quantitative analysis was conducted.

Result Calculation: Response factor calculation: ${{\displaystyle \mathrm{F}}}_{\mathrm{i}}={{\displaystyle \mathrm{C}}}_{\mathrm{si}}·{{\displaystyle V}}_s/{{\displaystyle A}}_{si}$

Fi—Response factor of component i, μL/(mV•s);

Csi—concentration of standard gas component i, φ (i)/10⁻²;

Vs—Standard gas injection volume, μL;

Asi—Peak area of component i in standard gas, mV•s.

Calculation of component content in the sample: ${{\displaystyle X}}_{\mathrm{i}}=\frac{{{\displaystyle F}}_{\mathrm{i}}·{{\displaystyle \mathrm{V}}}_{\mathrm{t}}{{\displaystyle ·A}}_{\mathrm{i}}}{\mathrm{m}·{{\displaystyle V}}_{\mathrm{j}}}$

Xi—The content of acid-hydrolyzed hydrocarbon component i in the sample (if the integer number is less than 3, retain 1 decimal place; if the integer number is ≥3, do not retain decimals), μL/kg;

Vt—degassing volume, mL;

Ai—peak area of acid-hydrolyzed hydrocarbon component i in the test sample, mV•s;

Vj—Injection volume of test sample, mL; and

M—Weighing mass of the sample, kg.

The analysis and data-processing methods include probability distribution statistics, data structure analysis (where the mean represents the average level of the data, the standard deviation represents the size of data dispersion, and the coefficient of variation represents the size of data relative fluctuations), and background value and anomaly determination (via the mean method and Kriging method). The results of comprehensive analysis of the acid-extracted hydrocarbon and methane carbon isotope test data are then used to determine the underlying oil and gas attributes [39,40,41,42,43].

4. Results

4.1. Acid-Extracted Hydrocarbon Composition

Acid-extracted C₁–C₅ hydrocarbons were detected in the samples, with methane (CH₄), ethane (C₂H₆), and propane (C₃H₈) being the main components. The content of butane- and pentane-series hydrocarbons was extremely low, especially for pentane, with only a few samples being detected. The acid-extracted hydrocarbon index of the samples at each station had the characteristic of CH₄ > C₂H₆ > C₃H₈. The variation in methane content in the acid-extracted hydrocarbons ranged from 13.34~1799.31 μL/kg, with an average value of 138.25 μL/kg and a median value of 94.01 μL/kg. The variation in ethane content in the acid-extracted hydrocarbons ranged from 0.66~195.26 μL/kg, with an average value of 21.61 μL/kg and a median value of 9.54 μL/kg, which was significantly lower than the content of methane. The variation in propane content in the acid-extracted hydrocarbons ranged from 0.26~80.60 μL/kg, with an average value of 8.17 μL/kg and a median value of 3.57 μL/kg. Detailed data are presented in

Table 1. The abundance anomaly of acid-extracted hydrocarbons.

	Minimum (μL/kg)	Maximum (μL/kg)	Median (μL/kg)	Mean (μL/kg)	SD	CV	K
SC1	13.34	1799.31	94.01	138.25	163.23	1.18	1.47
SC2	0.66	195.26	9.54	21.61	29.99	1.39	2.27
SC3	0.26	80.64	3.57	8.17	11.79	1.44	2.29
SiC4	0.10	67.37	2.14	5.97	9.61	1.61	2.80
SnC4	0.06	32.53	1.25	2.89	4.37	1.51	2.32
SiC5	0.02	87.15	2.47	7.38	12.29	1.66	2.99
SnC5	0.01	9.74	0.22	0.53	0.99	1.87	2.47
SC2g	1.23	465.18	19.74	46.56	68.47	1.47	2.36

.

4.2. Acid-Extracted Hydrocarbon Distribution

The high values of methane in the acid-extracted hydrocarbons are mainly distributed in the northern part of the study area; other high values are distributed in the central–southern part of the study area. The high values of heavy hydrocarbons in the acid-extracted hydrocarbons are also mainly distributed in the northern part of the study area, and secondary high values are mainly distributed in the central–southern part of the study area. The anomalies in the acid-extracted methane and heavy hydrocarbons have high positive correlation (Figure 3 and Figure 4).

4.3. δ ¹³C (‰) of Acid-Extracted Hydrocarbon Methane

The variation in δ¹³C (‰) content in the acid-extracted hydrocarbons ranged from −34‰~−48‰, with a maximum value of −34.45‰, a minimum value of −47.11‰, a median value of −37.5‰, and a standard deviation of 2.48. The distribution is characterized by a high north–south distribution and low middle distribution (Figure 5).

5. Discussion

5.1. Variations in Acid-Extracted Hydrocarbon Abundance

From the perspective of data statistics, the mean reflects the average level of the data, the standard deviation (SD) reflects the size of the data dispersion, and the coefficient of variation (CV) reflects the size of the relative fluctuations in the data. From a geological perspective, the coefficient of variation and intensity (K) reflects the impact of later geological processes. The coefficient of variation is calculated as the standard deviation/mean and the intensity coefficient as the mean/median. The coefficients of variation of the indicators of geochemical exploration in the Chaoshan Depression are all greater than 1, and the intensity factors of later superimposed actions are all greater than 2, indicating that the geochemical exploration indicators in the region are greatly affected by later geological processes. More details are presented in Table 1.

The acid-extracted hydrocarbons of the Chaoshan Depression belong to the medium-abundance geochemical background and are characterized by heterogeneous fields and homogeneous fields [44,45]. Altered carbonates belong to a medium abundance geochemical background and possess homogeneous field characteristics. The interference of seabed microbial disturbances and biogenic methane on indicators of oil and gas geochemical exploration is relatively small [45], and all geochemical exploration indicators are affected by later oil and gas interactions.

5.2. Acid-Extracted Hydrocarbon Structural Indicators

Under normal circumstances, the sample data of a single parent obey a normal distribution; however, when multiple parent characteristics are present, the data structure characteristics, for the most part, do not obey a normal distribution. The ideal separation mode between the background and an anomaly is shown in Figure 6a, which features a trailing phenomenon.

Figure 6b–f show the results of the iteration analysis of the main indicators of oil and gas geochemical exploration in the Dongsha area. The iteration results of each indicator have similar non-normal distribution characteristics, and all indicators have tailing phenomenon or multiple parent backgrounds, suggesting the effect of late superposition. Moreover, the intensity factors of the later superimposed actions are all greater than 1, indicating that all the indicators are affected by the geological factors of the later stage (oil–gas, sediment sources, environment, etc.).

5.3. The Fabric Characteristics of Hydrocarbons

The composition of adsorbed gas near the surface has a favorable tracing effect for distinguishing oil and gas properties and indicating the presence of gas reservoirs. The ratio of gas components in the hydrocarbons, such as C₁/∑C, C₁/C₂, C₃/C₁, reflect this differentiation effect. The range of variation in the composition and characteristics of the hydrocarbon series indicators in the sediments above petroleum reservoirs are shown in

Table 2. The range of gas composition changes in the overlying sediments of petroleum reservoirs.

Type	Ratio of Hydrocarbon
	C1/∑C × 100	C1/C2	(C3/C1) × 1000
Oil	75~50	10~4	60~500
Gas	>75	>10	<60

.

The C1/∑C × 100 ratio ranges from 51.55 to 97.06, with an average of 78.43; C₁/C₂ ranges from 2.66 to 52.71, with a mean of 10.58; and (C₃/C₁) × 1000 ranges from 5.65 to 163.88, with an average of 55.36. Based on the characteristics of the hydrocarbon ratio, the petroleum reservoirs in the Chaoshan Depression are determined to be mainly composed of gas (Figure 7, Figure 8 and Figure 9).

5.4. Differentiation Characteristics of Hydrocarbon

Due to the differences in the chemical and physical properties of oil and natural gas, the differentiation of hydrocarbons occurs during the micro-leakage of gas into seafloor sediments, changing the proportion and dynamic balance of the original hydrocarbons and forming significant differences between oil, gas, and non-oil-and-gas zones in seafloor sediments. As shown in the differentiation diagram of heavy and light hydrocarbons (Figure 10), 198 sites out of 200 have C₂ + C₅/C₁ ratios greater than 5%, thus belonging to wet gas.

The C₁–C₄ ratio represents the content of methane to butane (nC₄ + iC₄) in the acid-extracted hydrocarbons adsorbed from the underlying oil- and gas-bearing structures that leak into the seafloor sediments. The C₁/(C₂ + C₃) ratio represents the degree of evolution (or maturity) of the hydrocarbon-generating organic matter. As the maturity increases, this value increases exponentially, indicating a gradual transition from source rock to crude oil, to condensate oil and gas, and to dry gas in the underlying strata. The C₂/(C₃ + C₄) ratio reflects the interrelationships between heavy components in the acid-extracted light hydrocarbons, and to some extent, it can also reflect the degree of evolution of the hydrocarbon-generating parent materials. The ratio of C₁/(C₂ + C₃) to C₂/(C₃ + C₄) can be used to identify the types of oil and gas reservoir from which of the acid-extracted adsorbed hydrocarbons originate.

5.5. Carbon Isotope of Methane (δ¹³C) Features

The stable carbon isotope of methane in the acid-extracted hydrocarbons is an important indicator for distinguishing oil and gas properties. The average δ¹³C value of biogenic gas is less than −54‰, the average δ¹³C value of oil field gas ranges from −54‰ to −40‰, and the average δ¹³C value of mature gas or coal-type gas is greater than −40‰ (Figure 11) [32]. The stable carbon isotope values of acid-extracted hydrocarbon methane in the Chaoshan Depression range from −34‰ to −48‰, with a maximum value of −34.45‰, a minimum value of −47.11‰, a median value of −37.50‰, and a standard deviation of 2.48. Its oil and gas characteristics are of an organic origin and are in the over-mature stage (Figure 11).

The planar anomalies of carbon isotopes in methane are high in the south and the north of the region, and low in the middle area (Figure 12).

5.6. Evaluation of Favorable Oil and Gas Areas

Through acid-extracted hydrocarbons anomaly analysis of the composition, abundance, structure, planar distribution, and planar distribution of methane stable isotope values of acid-extracted hydrocarbons in the Chaoshan Depression, it is believed that anomalous zones are distributed in the central and southwestern parts of the depression. After normalizing the oil and gas exploration indicators, the moving average method and Kriging method were used to delineate the northeast (I) and southwest (II) parts of the Chaoshan Depression as the most favorable prospective oil and gas areas (Figure 12).

From the seismic profile crossing the northern abnormal area, it can be observed that the methane present in the acid-extracted hydrocarbons is abnormally developed in the seafloor sediments above the reservoir. However, this anomaly gradually decreases as it approaches the edge of the reservoir, tending towards the background value. There is a favorable correspondence between the oil reservoir and the anomaly (Figure 13), and the micro-leakage of oil and gas from the underlying reservoir has been determined as the main reason for the formation of these geochemical anomalies. The formation mechanism of geochemical anomalies in the Chaoshan Depression is as follows: gas from the underlying reservoir is driven upwards by pressure and leaks into the seabed through fault planes and micro-fractures. The underlying petroleum reservoir is controlled by the source, the micro-fractures control the permeability, and the surface sediments adsorb and trap the leaked hydrocarbons, forming a “lower generation, upper accumulation and micro fractures leaking “model. This model would benefit from understanding the mechanism of hydrate accumulation in the Dongsha area also.

6. Conclusions

• The oil and gas reservoir in the Chaoshan Depression is mainly composed of condensate gas (oil). The reservoir is of an organic thermal origin. The source rock is dominated by marine sedimentation, with highly mature organic matter.
• The favorable oil and gas prospects in the Chaoshan Depression are divided into two regions, respectively favorable zone I and favorable zone II, mainly located at the intersection of the central low bulge, the western depression, and the western slope of the depression; the DS-A structure indicates an oil and gas reservoir dominated by gas.
• The “lower generation, upper accumulation and micro fractures leaking” model is the mechanism explaining the formation of oil and gas anomalies in the Chaoshan Depression, in which hydrocarbons are controlled by the underlying petroleum reservoir, leak through micro-fractures, and adsorb on the seabed’s surface.