Hydrocarbon Trap Classification Based on Associated Gas Chimneys

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1 Chapter 14 Hydrocarbon Trap Classification Based on Associated Gas Chimneys Roar Heggland 1 Abstract Oil seeps, shallow gas, and surface features such as seabed pockmarks and mud volcanoes are historically believed to be signs of deeper hydrocarbon accumulations. In the search for connections between shallow features and deeper hydrocarbon accumulations, gas chimneys and faults have been studied as possible routes for vertical migration of gas and fluids from source rocks and hydrocarbon-charged traps. Understanding these fluid migration pathways can help evaluate whether a trap is charged or has leaked. A method based on seismic attributes and use of neural networks has been developed to detect and display gas chimneys. This method makes it possible to detect and map gas chimneys in a consistent manner and to see the position of chimneys relative to faults and traps. The detection of gas chimneys in seismic data has therefore been used as a tool in an effort to distinguish between hydrocarboncharged traps and dry traps with associated chimneys. Based on such case studies, a model of trap classification has been proposed and tested on more than 100 drilled traps in the Norwegian North Sea with good results. Introduction To identify connections between the seabed or shallow hydrocarbon indicators and oil and gas reservoirs or source rocks, seismic data have been used to infer migration pathways (Heggland, 1997, 1998). Seabed features such as pockmarks and carbonate formations (Hovland and Judd, 1989; Roberts and Aharon, 1994; Hovland et al., 010) are fluid escape features that may indicate deeper hydrocarbon accumulations. Buried features may evidence once-active hydrocarbon seepage. However, seabed and shallow features do not show the vertical fluid migration pathways that connect to a leaking trap or source. Gas chimneys and faults may provide connections to traps that can contain hydrocarbons as well as connections to hydrocarbon sources. Method Gas chimneys are visible on seismic data as vertically oriented zones of low reflectivity and distorted reflector continuity. Gas chimneys are not clearly visible on time slices from D volumes nor on attribute maps. Therefore, a method was proposed to better detect chimneys by combining seismic attributes in a manner that could distinguish gas chimneys from their surroundings (Heggland et al., 1999; Meldahl et al., 1999). Because of the difference in the seismic character inside and outside of a chimney, attributes such as amplitude, energy, trace correlations, and time-dip variance are well suited as input for chimney detection. A neural network (Steegs, 1997) was applied to the input seismic attributes and was trained on chimney and nonchimney locations. Based on this training, the network can make a classification of other samples in a seismic volume into chimney or nonchimney class by assigning a high probability to chimney samples and a low probability to nonchimney samples. Because noise and other features in the seismic data show a seismic character similar to a gas chimney (i.e., similar 1 Statoil ASA, Stavanger, Norway. rohe@statoil.com. 1

2 Hydrocarbon Seepage: From Source to Surface attribute values), the vertical extent of chimneys is extracted in order to discriminate between gas chimneys and features that have little vertical extent. This extraction is addressed by using multiple detection windows along the time axis. Still, features such as faults, channel edges, diapirs, and gas associated with mud-volcano feeders will be detected because their seismic character is similar to chimneys and because they have large vertical extents. However, most of these features can be distinguished from chimneys by using other criteria, such as shape and appearance at different stratigraphic levels. A chimney can, for example, be present below a mud volcano as a result of gas invading the surrounding formation during eruption. Some mud volcanoes exhibit mud flows at different stratigraphic levels, which makes them easier to identify and hence distinguish the associated chimney from chimneys not associated with mud volcanoes. The final neural network output, called a chimney cube, can be regarded as a chimney probability volume. Applications of the chimney-detection method have led to regional mapping of gas chimneys (Heggland et al., 000; Meldahl et al., 001), allowing comparisons of chimneys and chimney distributions from different areas. The first chimney cube was created in 1998 (see Figure 1). Since then, chimney detection has been used to infer remigration routes from traps useful information in predicting hydrocarbon-charged traps and dry traps. Model Some gas chimneys coincide with faults as well as with fluid escape features, shallow gas accumulations, hydrocarbon-charged reservoirs, and source rocks. The presence of Chimney Standard D Cube Seismic Attributes Neural network Classification Chimney Cube Figure 1. A D seismic volume (top) before and (bottom) after detecting gas chimneys. chimneys along a fault is interpreted to indicate that the fault is, or has been, open for vertical fluid migration. Chimneys associated with faults have been referred to as type 1 chimneys (Heggland, 005). Laterally extensive gas chimneys that are not associated with faults are observed above hydrocarbon-charged structures as well as over deep parts of basins where source rocks are known to be present; such chimneys are referred to as type chimneys. Based on comparisons between dry and charged traps, a simple model classifies traps using associated chimneys (Heggland, 005). The model, based on case studies from the Norwegian shelf, the Nigerian continental slope, the Gulf of Mexico, and the Caspian Sea, is comprised of three scenarios: class A, class B, and class C traps (Figure ). A class A trap has a leaking fault at the crest of the trap, indicated by one or more type 1 chimneys present at the fault, implying a risk that the trap has leaked and contains Class A Type 1 chimney Leaked trap Class B Type 1 chimneys Leakage from trap (left) or Charging of trap (right) Class C Type chimney Hydrocarbons in trap and seal Figure. Trap classification model based on associated gas chimneys for classes A, B, and C.

3 Chapter 14: Hydrocarbon Trap Classification Based on Associated Gas Chimneys only minor volumes of hydrocarbons. A small column can only be maintained by charge from a deeper source; if this is the case, hydrocarbons will continue to escape the structure (i.e., remigration). A class B trap leaks hydrocarbons vertically through a fault at the flank of the trap. Chimneys indicate leakage from the trap through the fault, but leaving a larger hydrocarbon column than in the class A case. Faults may act as trap leakage or charge routes and show associated chimneys above or below class B traps, respectively. The latter case indicates fluid migration between a source rock and a reservoir (i.e., migration). A class C trap has hydrocarbons in the trap as well as in the seal. In this class, a type gas chimney is located within the map outline of the trap and extends from the top of the trap into the overburden. It can be widespread, covering part of or the whole surface of the trap. This kind of chimney is not associated with faulting of the cap rock. Similar models are presented in Connolly et al. (see Chapter 7, this volume). Criteria for chimney recognition Noise in seismic data can be created by features in the overburden and can be misinterpreted as gas chimneys. Similarly, gas chimneys can be misinterpreted as noise created by shallower features. Some examples follow. Shallow high-amplitude anomalies Shallow high-amplitude anomalies or features exhibiting complex reflection patterns can create distortions below them that look like gas chimneys. In many cases, high-amplitude anomalies that are interpreted, or confirmed by drilling, as shallow gas accumulations are present above gas chimneys. These may have been charged through vertical migration pathways, as indicated by the gas chimneys. Chimney detection creates an output in accordance with what the neural network has been trained to recognize. In the example in Figure a, the neural network is trained to detect features interpreted to be gas chimneys. The vertical noise on the right side of Figure a seems to be caused by the shallow high-amplitude anomalies and has not been selected for training the neural network for chimney detection. As a result, the detection has picked up the interpreted chimney and not the noise below the shallow high-amplitude anomalies, as seen in Figure b. Sand injections Over large areas in the North Sea, V-shaped high-amplitude anomalies, interpreted as sand injections (Cartwright et al., 007), are present. Below these anomalies are commonly zones of vertically extended noise that resemble gas chimneys (Figure 4). In Figure 5, these V-shaped highamplitude anomalies are highlighted in red. The underlying noise has been detected as gas chimneys, highlighted in yellow. At the base, a time slice from a trace correlation volume is in blue and black to show how deeper faults at the Jurassic level compare with the locations of the V-shaped high-amplitude anomalies and the possible gas chimneys. As can be seen in Figure 5, the amplitude anomalies (red) and the underlying noise (yellow) do not fully overlap. This comparison indicates that the vertical noise is not a) Amplitude anomalies b) Noise 1 Gas chimney Gas chimney BCU BCU km km Figure. (a) Seismic section showing a gas chimney versus noise created by shallow amplitude anomalies. (b) A result of chimney detection.

4 4 Hydrocarbon Seepage: From Source to Surface created by the V-shaped high-amplitude anomalies but likely represents gas chimneys. Both the anomalies and the gas chimneys are located above faults. The noise, or the gas chimneys, can be associated with the deeper faults, so they are interpreted to indicate continued vertical fluid migration pathways. The faults have also probably influenced the injections of sand into shallower levels because they too are located almost directly above the faults. The injected sands probably contain gas because they exhibit high amplitudes and are located above the gas chimneys. 0 Pockmarks and associated chimneys Gas chimneys are sometimes observed to be present below seabed pockmarks (e.g., Heggland, 1998). In an example from offshore Nigeria (Figure 6), a cluster of pockmarks can be seen on a seabed azimuth map derived from a D seismic volume. Vertically extended distortions are present below the pockmarks in the D volume (Figure 7), and the deep parts of the distortions are suspected to be artifacts. To find out, angle stacks with increasing offset between the seismic source and the receiver are displayed to identify any changes in appearance with offset. Sand injections 1 Chimneys km Figure 4. Seismic section showing amplitude anomalies interpreted as sand injections. Noise below the anomalies is interpreted to be gas chimneys, based on the display in Figure 5. Figure 6. Seabed azimuth map derived from D seismic data, Nigerian continental slope, showing the presence of pockmarks. Pockmarks Figure 5. A trace correlation time slice at 44 ms TWT (blue) is used to display faults at the Jurassic level. Amplitude anomalies interpreted as sand injections are displayed in red. Noise below the anomalies is detected as gas chimneys, displayed in yellow. The red and yellow spots do not fully overlap, so the noise is interpreted as gas chimneys. Seismic distortions Figure 7. Seismic section showing columnar distortions below pockmarks.

5 Chapter 14: Hydrocarbon Trap Classification Based on Associated Gas Chimneys 5 The result is shown in Figure 8. The deepest parts of the distortions look cone shaped; these features widen with offset, indicating they are artifacts. In addition, the reflection sequences on the inner side of the cone-shaped distortions on the far offsets are preserved; they correlate with the reflection sequences on the outside and away from the cone shapes. The faults in the deep part of the seismic section, however, stay fixed in their respective positions throughout all offsets, whereas some of the deepest distortions move across faults when the offset increases. These comparisons suggest that only the upper part (e.g., 500 ms or less below seabed) of the distortions below the pockmarks can be a) b) c) interpreted to be gas chimneys, creating artifacts farther down in the seismic section, which can be identified using angle stacks. In Løseth et al. (011), these features are described as 1000-m-long blowout pipes. Based on the angle stacks, it seems that these features are less than half that length (i.e., down to only s two-way time [TWT] in Figure 8). This difference is significant because they are then not connected to the interpreted deep marine reservoir sands (at ~ s TWT) described by Løseth et al. (011). Mud volcanoes Vertically extended chimneys can also be seen on seismic sections below mud volcanoes. These chimneys may be detected in chimney cubes and are believed to be related to gas emitted during eruptions, in which case some of the gas invades the surrounding formation and is captured within the shales. This process can explain why the gas is visible on the seismic data as a chimney. Figures 9 11 show a mud volcano on the Nigerian continental slope (Heggland et al., 1996; Heggland and Nygaard, 1998). Figure 9 illustrates a seismic section from D seismic data. A mud volcano and a wide zone of disturbance can be seen below the mud volcano. This disturbance may result from acoustic masking caused by the high amplitudes at the mud volcano; alternatively, it may be due to the presence of gas in the underlying sediments. In Figure 10, the mud volcano and two generations of mud flows are made visible by an average absolute amplitude display, created by using a time interval parallel to and positioned below the seabed reflector. The time window used starts below the (black) seabed reflector and is large enough to capture the two mud-flow d) Mud volcano Mud flow Mud flow 1 1 Figure 8. Angle stacks of the section in Figure 7, showing that the distortions widen with increasing offsets and that the reflection sequences within the distorted zones are preserved in the far offset stacks, correlating with the reflection sequences outside the distorted zones. Angle stacks are for (a) 16, (b) 14 8, (c) 6 40, and (d) 8 5. Figure 9. Seismic section across a mud volcano at the Nigerian continental slope. Two generations of mud flows are visible as two reflectors terminating down the slope below the seabed reflector.

6 6 Hydrocarbon Seepage: From Source to Surface reflectors seen in Figure 9. Figure 11 shows a side-scan sonar image of the same mud volcano. Two mud-expulsion centers are clearly visible, indicating the mud feeders have a much smaller radius than their respective mud volcano and the seismic distortion below it. Seabed gravity cores taken at this mud volcano showed high content of oil and gas (Graue, 000). Mud volcanoes can bring large amounts of gas and sometimes oil to the surface during eruption, and they are known to seal themselves after eruption. Mud volcanoes are present in many areas where oil and gas discoveries have been made, e.g., in the south Caspian Sea (e.g., Azeri, Chirag, Guneshli, and Shah Deniz oil and gas fields) and offshore Nigeria. An oil discovery was made close to the mud volcano shown in Figure 10. In Figures 1 and 1, other mud volcanoes offshore Nigeria are indicated by arrows. These are located at the flank of a gas-filled trap (green structural closure in Figure 1). Gas chimneys Leaked trap Gas below mud volvanoes Seismic section Mud flow 1 Mud flow Figure 10. Average absolute amplitude in a time interval parallel to and positioned just below the seabed reflector, where high amplitudes are imaging the mud volcano in Figure 9 and its two mud flows. Figure 1. A D visualization of a top reservoir horizon and detected gas chimneys (yellow) on the Nigerian continental slope. Pockmarks Mud volcanoes Seabed Leaking fault Mud expulsion features Sample locations Leaked trap Gas chimneys 500 m Figure 11. Side-scan sonar image of the mud volcano in Figures 9 and 10. Two mud expulsion features can be seen. Gravity-core sample locations are noted. Figure 1. A D visualization of a top reservoir horizon and detected chimneys (yellow) on the Nigerian continental slope. A seabed azimuth map is displayed above, showing faults, mud volcanoes, and pockmarks.

7 Chapter 14: Hydrocarbon Trap Classification Based on Associated Gas Chimneys 7 Trap classification The following sections provide examples to illustrate the three classes of traps. Class A trap example Figure 1 is an example from the Nigerian continental slope. As noted along the left side of Figure 1, detected chimneys are located at a fault oriented along the ridge of a structure. The fault extends to the seabed and can be identified on the seabed azimuth map in Figure 1. A well drilled into this structure was dry, probably because hydrocarbons had leaked out through the fault. Many examples such as this one show chimneys located at faults at or close to the crest of traps that are dry or that may contain only small Flat spots Traps amounts of hydrocarbons. In some class A traps, a small column may be maintained by persistent charge. Figure 14 shows a case wherein a fault cuts through multiple stacked traps, causing partial leakage. A gas chimney indicates fluid migration through the fault from below the deepest trap to the uppermost trap. Small hydrocarbon columns may be present, as indicated by flat spots. Class B trap example Figures 15 and 16 show an example where subtle chimneys are located at the flank of a Late Jurassic trap, the blue line in the figure being the base Cretaceous horizon. In Figure 15a, the chimneys are located above faults present in the Late Jurassic at the flanks of the trap. Figure 15b shows the corresponding section with detected chimneys. In Figure 16, the base Cretaceous horizon shows the structural closure of the trap; detected chimneys are displayed in white. The appearance of chimneys located at faults at the flank of the trap makes it a class B trap, according to the model. A gas discovery was made at the location shown by the red line in Figure 16. Gas chimney Fault Class C trap example Figure 14. Seismic section showing stacked traps with flat spots. A fault is cutting through the middle of the traps. A chimney that can be associated with the fault is visible between the traps. In class C traps, a trap is partially or fully covered by a gas chimney and no faults are associated with the chimney. Figure 17 displays an example of a class C trap. In the seismic section (Figure 17a), a widely extended gas chimney can be seen above a trap in the Jurassic, indicated by a base Cretaceous horizon shown as a blue line. A flat spot may a) b) A B A B Chimneys Class B trap Chimneys BCU BCU 4 Faults km km Figure 15. A seismic section showing a class B trap in the upper Jurassic, North Sea, where (a) chimneys and faults are present at the flanks and where (b) chimneys are detected in the corresponding section.

8 8 Hydrocarbon Seepage: From Source to Surface indicate a fluid contact. In the D display (Figure 17b), the base Cretaceous horizon and detected chimneys (white) show that a large part of the trap is covered by the chimney. Figure 18 shows another class C trap example. Many known fields and discoveries in the North Sea are class C cases, e.g., Ekofisk, Valhall, and Tommeliten. Discovery well Results based on classification of drilled traps in the North Sea A test of the trap classification has recently been made for more than 100 previously drilled traps in a region of the northern North Sea (well data taken from the Norwegian Petroleum Directorate s Factpages). The actual number of discoveries in this region is high and represents 56% of all drilled traps regardless of chimney presence, bearing in mind that several well-known fields (Statfjord, Snorre, Visund, Gullfaks, Troll) are present here. The following results were obtained: A Seismic line B The success rate for drilled traps with no chimneys is 46%. The success rate for drilled traps with chimneys is 78%. If the trap classification had been used, some of the leaked traps, class A, could have been avoided, increasing the success rate to above 90%. All drilled traps with associated chimneys (including dry traps) also contained a reservoir. Figure 16. A D display of a base Cretaceous horizon, showing the structural closure of the class B trap in Figure 15, the location of a discovery well, and detected chimneys (white). The recommendation is hence first to drill prospects with associated chimneys and then to drill traps without chimneys. a) A B b) Chimney B A Seismic line Flat spot BCU 4 km Figure 17. (a) A seismic section showing a class C trap in the Late Jurassic, North Sea, where a chimney covers a large area above the trap. A flat spot indicates a fluid contact. (b) A D display of a base Cretaceous horizon and detected chimneys (white), showing that a large part of the trap indicated in the seismic section is covered by a chimney.

9 Chapter 14: Hydrocarbon Trap Classification Based on Associated Gas Chimneys 9 TWT s 1 Well Conclusions Chimney Figure 18. Seismic section showing a broad gas chimney above the Tommeliten Gamma discovery, a class C trap. Case studies show that it is possible to differentiate between hydrocarbon-charged traps and dry traps, based on the occurrences of associated gas chimneys (Heggland, 005). A trap classification model that illustrates these differences has been proposed to predict hydrocarbon charge. Gas chimneys are believed to indicate fluid migration pathways through faults, as for class A and class B traps. In some cases, chimneys may indicate sufficient seal capacity, as for class C traps. The trap classification, which is based on the presence of gas chimneys, has been tested using more than 100 previously drilled traps in a region of the North Sea, and it worked well. In general, traps with associated gas chimneys seem to have a higher chance of containing hydrocarbons except for class A cases, which indicates traps have leaked. This observation does not mean that traps without chimneys should be avoided; rather, traps with chimneys (classes B and C) are lower-risk traps that perhaps should be drilled first. Traps with associated gas chimneys also contained reservoirs, suggesting that chimney presence can be used as an indication of the presence of a reservoir. By using the trap classification model, the rate of discoveries can be increased. Acknowledgements Statoil ASA is acknowledged for giving permission to publish this material. Many thanks go to my Statoil colleagues Nicholas Ashton, Benjamin Clements, Hallstein Lie, and Philip W. Mullis for supporting this work and offering valuable comments. References Cartwright, J., M. Huuse, and A. Aplin, 007, Seal bypass systems: AAPG Bulletin, 91, Graue, K., 000, Mud volcanoes in deep water Nigeria: Marine and Petroleum Geology, 17, Heggland, R., 1997, Detection of gas migration from a deep source by the use of exploration D seismic data: Marine Geology, 17, Heggland, R., 1998, Gas seepage as an indicator of deeper prospective reservoirs: A study based on exploration D seismic data: Marine and Petroleum Geology, 15, no. 1, 1 9. Heggland, R., 005, Using gas chimneys in seal integrity analysis: A discussion based on case histories, in P. Boult and J. Kaldi, eds., Evaluating fault and cap rock seals: AAPG, Heggland, R., P. Meldahl, A. H. Bril, and P. de Groot, 1999, The chimney cube, an example of semi-automated detection of seismic objects by directive attributes and neural networks Part II: Interpretation: 69th Annual International Meeting, SEG, Expanded Abstracts, Heggland, R., P. Meldahl, P. de Groot, and F. Aminzadeh, 000, Chimney cube unravels subsurface: The American Oil & Gas Reporter: February, Heggland, R., and E. Nygaard, 1998, Shale intrusions and associated surface expressions Examples from Nigerian and Norwegian deepwater areas: Proceedings of the Offshore Technology Conference, 1, Heggland, R., E. Nygaard, and J. W. Gallagher, 1996, Techniques and experiences using exploration D seismic data to map drilling hazards: Proceedings of the Offshore Technology Conference, 1, Hovland, M., R. Heggland, M. H. de Vries, and T. I. Tjelta, 010, Unit-pockmarks and their potential significance for predicting fluid flow: Marine and Petroleum Geology, 7, Hovland, M., and A. G. Judd, 1989, Seabed pockmarks and seepages Impact on geology, biology and the marine environment: Graham and Trotman. Løseth, H., L. Wensaas, B. Arntsen, N. Hanken, C. Basire, and K. Graue, 011, 1000 m long gas blow-out pipes: Marine and Petroleum Geology, 8, Meldahl, P., R. Heggland, A. H. Bril, and P. de Groot, 1999, The chimney cube, an example of semi-automated detection of seismic objects by directive attributes and neural networks Part I: Methodology: 69th Annual International Meeting, SEG, Expanded Abstracts,

10 0 Hydrocarbon Seepage: From Source to Surface Meldahl, P., R. Heggland, A. H. Bril, and P. de Groot, 001, Identifying faults and gas chimneys using multi attributes and neural networks: The Leading Edge, 0, Roberts, H. H., and P. Aharon, 1994, Hydrocarbon-derived carbonate buildups of the northern Gulf of Mexico continental slope: A review of submersible investigations: Geo-Marine Letters, 14, no. -, Steegs, T. P. H., 1997, Local power spectra and seismic interpretation: Ph.D. dissertation, Delft University of Technology.

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