EXPLORATION Offshore 3D seismic, geochemical data integration, Main Pass project, Gulf Of Mexico

John Q. Belt Jr., Gary K. Rice
GeoFrontiers Corp.
Dallas

A bottom cable, 3D seismic, and shallow piston-core geochemical survey was conducted in summer 1992 on Main Pass Blocks 41 and 58 in the Gulf of Mexico (Fig. 1[38253 bytes]). The 15.5 sq mile study area is in 11-24 m (36-79 ft) of water.

Two hundred seventy-six shallow, 2 m piston-core sediment samples were collected using a uniform grid pattern on 400 m (1,320 ft) spaced intervals. Retrieved sediment samples were immediately sealed in metal 1 pt cans containing biocide solution.

The purpose of the 3D seismic survey and geochemical offshore data integration project was three-fold:

• Determine if near-shore, low-cost shallow piston-core sediment samples would be affected by fluvial contamination.

• Evaluate the efficiency of a shallow-core, dense-grid sample design program in detecting thermogenic hy- drocarbons at depth.

• Evaluate the benefits of integrating offshore, shallow sediment geochemistry with 3D seismic data in developing a petroleum geological model.¹

All 3D seismic survey data and block boundaries, as described in the following illustrations and figures, are only generally located within the Main Pass Area.

3D seismic data

The bottom cable, 3D seismic survey included Main Pass Blocks 41 and 58. The project was located in the St. Bernard delta complex.

High sedimentation rates resulted in differential loading and compaction of the underlying sediments in the subsiding depocenter.2 Vertical profile lines showed structural traps to be growth faults and rollover anticlines in the 0 to 2,000 msec seismic time interval. This interval contains typical Miocene and Pliocene shallow marine deltaic complexes sourced from the north and northwest.

Numerous horizontal time slices and vertical profile lines were created from the seismic survey data and integrated with the geochemical data. Fig. 2 [37188 bytes] shows a horizontal time slice at 500 msec covering Blocks 41 and 58. Three different vertical profile lines are shown progressing from south to north dissecting the horizontal time slice. Numerous faults are visible in the horizontal time slice and vertical profile lines, most of which trend northeast to southwest and dip southeast.

Figs. 3 [63284 bytes] and 4 [53046 bytes] display the horizontal time slices at 500 msec and 1,500 msec. The 500 msec horizontal time slice, in Fig. 3 [63284 bytes], shows the area's fault trends. Since this time slice was closest to the surface, it was selected for comparing seismic fault trends to fluorescence (aromatic) data anomalies. The 1,500 msec horizontal time slice, in Fig. 4 [53046 bytes], was selected based on fluorescence fingerprinting that matched the sediment core samples to production at this depth. The 1,500 msec horizon was integrated with acid extraction analysis to investigate similarities between defined seismic traps and ethane data anomalies.

Careful evaluation of the geophysical data provided information on visible, petroleum migration pathways, and the location of hydrocarbon traps with known production. This information was integrated with geochemical data from the shallow piston-core sediment samples.

Geochemical data

Three types of geochemical analyses were conducted on the shallow sediment samples: acid extraction, fluorescence, and C₁₅₊ capillary gas chromatography (GC). However, prior to converting raw geochemical data into usable information, statistical quality control (SQC) assessments were conducted.

Quality control

The data passed a six phase SQC assessment before being considered reliable. The phases were process capability, data reproducibility, sample variability. reagent blanks, correlation coefficients, and hydrocarbon cross plots.

• Process capability monitored the variability or capability of the analytical equipment (e.g., gas chromatographic, fluorometer, etc.) and techniques used in quantitating the hydrocarbon data. Certified standards were analyzed and plotted on statistical quality control charts (X-bar and R) to ensure specifications were within statistical control limits.^3-4

• Data reproducibility measured the ability of the extraction process (acid and solvent extractions) to provide reproducible data. Random samples were selected, then extracted and analyzed in duplicate to determine data variability.

• Sample variability determined the difference in concentration data between two or more samples collected at the same location. Each sample was extracted and analyzed independently. The hydrocarbon data were compared for variability.^3-4

• Reagent blanks were analyzed on a daily basis. The same extraction equipment, reagents, and analytical methods were used. Only the sediment sample was omitted from the procedure. This quality control measure checked for entrained hydrocarbons in the various reagents, materials, and equipment that would have biased the data.

• Pearson Product-Mo- ment Correlation Coefficients measured how close the relationship between two variables (e.g. propane versus ethane) approached a linear relationship.5 If the two variables were directly correlated, the correlation value would be 1. Light hydrocarbon data from a single source, free of contamination should have a propane to ethane correlation coefficient greater than 0.9.

• Hydrocarbon cross plots graphically illustrated the correlation between two variables (e.g. propane versus ethane). Cross plots were equally important because a single, extremely non-correlated variable pair would have resulted in low Pearson Product-Moment Correlation Coefficient values. Cross plots would reveal this problem associated with non-correlation.

Acid extraction data

Subsamples from each sediment core were analyzed for low-molecular-weight hydrocarbons (methane through n-pentane) and reported in parts per billion by dry weight of sample. Data statistical analysis, in Table 1[19644 bytes], shows Pearson Product-Moment Correlation Coefficients are 0.9881, or higher, for normal alkanes. The propane versus ethane correlation coefficient is 0.9987. This very high correlation indicates the samples are compositionally similar and free of contamination. The extremely low correlation between the alkanes and olefins (ethylene and propylene) is indicative of olefinic compounds not being directly associated with a thermogenic source.

Low-molecular-weight hydrocarbon cross plots also showed excellent data quality and a single source. For example, the propane versus ethane cross plot in Fig. 5 [39904 bytes] reveals a single linear relationship interpreted as a single composition. The linear trend indicates the samples are contamination free and represent a single thermogenic source at depth.

Fig. 6 [34593 bytes] is an Ethane Composition Index (ECI) histogram. Hydrocarbon ratios are good indicators of multiple thermogenic sources. An ECI value was determined by ratioing the ethane concentration to petroleum n-alkane sums. Fig. 6 [34593 bytes] shows a single population and near normal distribution indicating a single composition.

Fig. 7 [32575 bytes] is an ethane concentration ordered plot. Ethane concentrations are sorted in ascending order and graphed. A well defined, increase in slope at 300 ppb/wt indicates approximately 25% of the samples are significant.

Fluorescence data

Piston-core subsamples were dual-solvent extracted and analyzed by fluorometry. The solvent extract was excited by ultraviolet light at 265 nm and fluorescence emission intensities measured at 320 nm and 365 nm. The corresponding two-ring and three-ring aromatic hydrocarbons were reported in parts per billion by weight equivalents of naphthalene (two-ring) and phenanthrene (three-ring).

Chevron USA Production Co., New Orleans, supplied 12 crude oil samples from Main Pass Block 41 field production. These samples were analyzed by fluorometry. Based on their three-ring versus two-ring ratios, the 12 crude oil samples were divided into three groups: shallow, mid-depth, and deep.

Fig. 8 [54927 bytes] illustrates fluorescence fingerprinting of a representative sediment sample to the three oil groups. The sediment sample is an excellent match to mid-depth oil. The similar steep, tailing slope of the sediment sample compared to mid-depth oil indicates little degradation and a continuous source supplied to the shallow sediments.

Fig. 9 [56812 bytes] is an aromatic cross plot of the three-ring versus two-ring aromatic hydrocarbon concentrations. The three oil groups are compared to the sediment samples. The cross plot shows:

• The three-ring versus two-ring aromatic concentrations of the sediment samples are very similar to mid-depth oil.

• The linear trend indicates the sediment core samples have a single, common source at depth.

• The linear trend also suggests the fluorescence data are free of contamination. This confirms the high values of the Pearson Product-Moment Correlation Coefficients (Table 1[19644]) and linear trend in the propane versus ethane cross plot (Fig. 5 [39904 bytes]).

Fig. 10 [29752 bytes] is a three-ring aromatic concentration ordered plot. The three-ring aromatic equivalents are sorted in ascending order and graphed. A sharp change in slope at 1,800 ppb/wt was interpreted as increased aromatic concentrations associated with liquid petroleum seepage along faults into near-surface sediments. To illustrate these sharp concentration gradients associated with liquid petroleum seepage, a 3D fluorescence surface model was plotted (Fig. 11 [35267 bytes]). This model was used to determine near-surface fault locations and trends.

C₁₅₊ capillary GC data

Selected samples high in aromatic concentrations were solvent extracted for 24 hr using a reflux extraction apparatus. Solvent extract was concentrated and analyzed for high-molecular-weight hydrocarbons (C₁₅₊).

The selected sediment samples showed a high concentration of high-molecular-weight hydrocarbons in the C₁₅ to C₂₅ range. A significant concentration of hydrocarbons in the C₁₅ to C₂₀ range suggests the migration of thermogenic hydrocarbons from depth. Hydrocarbons in this molecular weight range do not generally survive fluvial transport.⁶

Fig. 12 [41497 bytes] shows the C₁₅₊ capillary gas chromatographic scans for a selected sediment sample and mid-depth oil (diluted). The distribution of C₁₅₊ hydrocarbons in the mid-depth oil are similar to those in the extracted sediment sample.

Data integration

Prior to integrating geochemical data with the 3D seismic survey data, a "stand-alone" geochemical model was developed using the acid extraction and fluorescence data. Basic principles of mass transport for low-molecular-weight hydrocarbons (e.g. ethane) and high-molecular-weight hydrocarbons (e.g. aromatic) were used to evaluate migration pathways from reservoir depth into near-surface sediments.^{7 8 9} These principles are:

• First, aromatic compounds and C₁₅₊ alkanes are associated with liquid petroleum seepage. The transfer of liquid petroleum at depth into near-surface sediments requires larger conduits (e.g. macro-fractures). Therefore, aromatic data reflect liquid petroleum seepage along faults. Elevated aromatic concentrations represent approximate fault trace locations in the near-surface sediments.

• Second, the presence of low-molecular-weight hydrocarbons (e.g. ethane) in near-surface sediments is due to fractionation in the small, upper portion of a petroleum reservoir. These fractionated light gases will attempt to migrate near-vertical through a fracture network (micro-fractures and larger) into near-surface sediments. These data represent the approximate location of various subsurface hydrocarbon traps.^{8 9}

The geochemical model, in Fig. 13 [125,338 bytes], was developed using the above criteria to assess and evaluate the hydrocarbon data. The model illustrates two basic conclusions:

1. The anomalous aromatic (fluorescence) data suggest the near-surface location of a fault network trending northeast to southwest and east to west. Also, fluorescence fingerprinting and C₁₅₊ capillary gas chromatography analysis match the sediment core samples to the mid-depth oil producing horizon.

2. The anomalous light gas data (e.g. ethane) are located between most of the aromatic trends, especially in the south. Light gas data suggest the presence of petroleum reservoirs at depth located between faults.

Next: 3D seismic survey and geochemical data integration.

The Authors