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    • 专利摘要:
    A method of identifying at least one fluid migration feature comprises receiving seismic data and processing the seismic data to identify the at least one fluid migration feature, wherein the seismic data comprises speed or velocity data and/or seismic amplitude data.
    公开号:DK201570358A1
    申请号:DK201570358
    申请日:2015-06-10
    公开日:2015-07-13
    发明作者:Anette Uldall；Katrine Juul Andresen
    申请人:Mærsk Olie Og Gas As；
    IPC主号:
    专利说明:

    Seismic Data Processing Method and apparatus
    Field
    The present invention relates to a method and apparatus: for processing seismic data, for instance for processing seismic velocity data. The method: and apparatus: may be far obtaining information concerning geological structures:, for example vertical anomalies, that may; represent a fluid migration: route.
    Background
    It is very well known to use a wide range of different measurement and data processing techniques to Obtain information concerning geological formations that may contain oil, gas or other hydrocarbons.
    Hydrocarbon-rich deposits are often present in relatively complex geolog leal formations, and the likelihood of whether hydrocarbons are present or absent in a particular location can depend on whether and; how the hydrocarbon deposits have migrated over time and/or in dependence on geological events.
    Summary in a first aspect of the Ihvehtlon there is provided a .method of identifying, for example determining the presence of, at least one geological feature, comprising receiving seismic data and processing the seismic data to ideniffy the at least one geological feature, wherein the seismic data comprises speed or velocity data and/or amplitude data and/or volume data.
    The at least one geological feature may comprise a fluid migration feature, for example a fluid migration route. A fluid migration feature may comprise a feature along which fluid may migrate, or along which fluid has or may have previously migrated.
    The fluid may comprise a hydrocarbon fluid;, for example oil or gas.
    The at least one geological feature may comprise at least one anomaly, for example at least one substantially vertical anomaly. Any suitable criteria may be: used to determine whether an anomaly, for example a speed, velocity or amplitude anomaly, is to be considered as a substantially vertical anomaly. For examples in some cases an anomaly may be determined to fc# a substantially vertical anomaly if its; angle of inclination to the vertical (for example, a mean or median, angle of inclination) is within a threshold angle Of inclination, for example Within 45" of the vertical, optionally within 30® of the vertical, optionally within 10" of the vertical, further optionally within 5" of the yertieai. The threshold angle of inclination can in some oases be selected in dependence on a characteristic or characteristics of the speed. Velocity and/pr amplitude data and/or in dependence on a characteristic of the geology represented by the data- The threshold angle of inclination can be predetermined and/or selected by a user. In some cases, the selected angle of inclination (and/or other threshold properties to determine whether a substantially vertical anomaly or other anomaly is present) may be varied, for example within: upper and Sower bound, until a: desired number, for example a predetermined target number, of substantially vertical anomalies is identified. Those identified substantially vertical anomalies can than be used to select features or sub-regions for further study or exploration.
    The method may comprise mapping the at least One anomaly according to at: least one of vortical extent, average velocity, one or more natural effects, Initiation: level,, termination level, or relation to at least one other;geological feature:
    The atteast on© anomaly or other geological feature may comprise, or be associated with, at least on© of a fracture, fault, depression, incision, karst feature, cap, channel, sinkhole, or reef feature.
    The method may comprise determining at least one of a termination level or an initiation level of the anomaly from the velocity data and/or amplitude data, for example a velocity volume and/or amplitude volume obtained from the seismic data.
    The at feast one anomaly may be characterised by lower amplitudes and/or acoustically distorted intervals of the seismic data.
    The processing of fee seismic data may comprise processing the seismic data to identify at least one anomaly in the seismic data, for example at least one yertieai anomaly. The processing of fee seismic data may comprise processing the data to identify at least one speed or velocity anomaly, and/or at least one amplitude anomaly, A speed or velocity anomaly may comprise a region for which valuers) of the speed of velocity data are different to the valuers) that may be expected. A speed or velocity anomaly may comprise s region for which yaiue(s) of speed or velocity data are different to values of speed or velocity obtained for other regions at substantially the; same vortical or horizontal position and/or obtained fcr other regions having similar'..geological properties and/or før other regions in the same interval and/or in comparison to average speed or velocity values., in some cases a speed or velocity or amplitude anomaly may be identified as being a region providing substantially lower {pr higher} speed or velocity or amplitude than adjacent regions tor corresponding positions in the same siratMm or strata; and/or for corresponding vertical positions, Corresponding positions may for eyampie be positions at the same depth beneath the surface, and/or positions having the same displacement ina direction perpendicular to the plane of the stratum (which may or may not be aligned parallel to the surface} and/or positions having the substantially the same vertical position in any chosen seismic reference frame. A vertical velocity anomaly may comprise a region that produces anomalous speed or velocity data and that extends for a significant distance in a substantially vertical direction.
    The presence of a speed or velocity anomaly may for example be determined in dependence on whether tbe difference In the speed- or velocity vsloefs} is greater than a threshold value, and/or whether the value of speed or velocity is less than (or greater than) a further threshold value. Any other suitable method may foe used for determining whether Speed or velocity vaiues(s). or other vaiue/s}, for example amplitude values, are anomalous. For example,, a thresholding to determine whether speed, velocity and/or amplitude values are anomalous may comprise determining whether the speed, velocity and/or amplitude values for a particular region are; different by a greater than a threshold amount from surrounding or adjaeoht regiohS:, for example regions at the same vertical andfer horizontal position and regions in the same strata. The threshold amount may, for example comprise an absolute amount or a percentage of proportion, ter example in some cases a difference of at least 80%, optionally at least 50%, optionally;: at least 20%, optionally by any other suitable value optionally selected id dependence on characteristics of the particular seismic data and/or geology represented by the seismic data under consideration. The threshold may be predetermined and/or selected by a user, In some cases;, the selected threshold values for speed, velocity and/or amplitude (and/or other threshold properties to determine whether a substantially vertical anomaly or other anomaly Is present) may be varied:, for example within upper and lower bounds, until a desired number, for example a predetermined target number, of anomalies is identified. Those identified substantially vertical anomalies can then be used to select features or sub-regions for further study or exploration,
    The speed or velocity data may, for example, comprise interval velocity data.
    The method may comprise determining whether an.identified speed or velocity anomaly, or other anomaly, matches a predetermined pattern or possesses predetermined properties. The predetermined pattern or predetermined properties may represent a variation of velocity or speed with position, for Instance lateral position. For example a pattern may be representative of higher velocity or speed at the centre of the velocity anomaly region and lower velocity or speed at at least poe edge of the velooity anomaly region, or vide versa. The velocity anomaly may comprise a composite velocity anomaly.
    The method may -further comprise selecting a region for further exploration or analysis in dependence on whether an anomaly is identified. The region may be selected in dependence on whether at least one anomaly Is associated with said region, for example is proximate to, Seeds to or from said region, terminates or initiates at said region, or extends wholly or partly within said region. The region may be selected In dependence in on the number, concentration or size of anomalies associated with said region, for example the number, concentration or size of Identified .anomali es proximate to, leading to or from said region, terminating or initiating at said region, or s&id -regiom
    The method may comprise making a prediction as to whether said selected regions contain hydrocarbons, for example oil or gas.
    The further exploration or analysis may comprise, for example further processing of seismic or other data, performance of further seismic or other measurements, or performance of a physical intervention, for instance an exploratory drilling operation.
    The method may comprise mapping where fluids, for example, hydrocarbon Hulds, may have moved in dependence on the presence, position, size, concentration or other property of the Identified at least one geological feature, for example the at least one anomaly.
    In another aspect of the invention, which may foe provided independently, there is provided a method of processing volume and/or speed/veiocity to interpret fluid migration in seismic migrations.
    In another aspect of tins invention, which may be provided independently, there is provided a method of applying seismic velocities to interpret fluid migration from seismic sections and seismic velocities. Thus, it may be possible to map where fluids have moved. The fluids may com prise hydrocarbons.
    The method may comprise performing seismic predictions (with the velocities) of mature source rocke.
    In another aspect af the invention, which may be provided independently, there id provided an apparatus for identifying at least one geological feature, the apparatus comprising a processing resource configured to receive seismic data and to process: the :Sei«mic data, to identify at least one geological feature, wherein the seismic data comprises speed or velocity data and/or amplitude data and/or volume data, The at least one geological feature may Comprise at least one fluid migration feature,
    In another aspect of thp invention, which may he provided independently, there is provided a computer program product comprising computer readable instructions that are executable to perform a method of identifying at least one geological feature, comprising reselving seismic data and processing the seismic data to identify the at least one geological feature, wherein the seismic data '.comprises speed or velocity data and/or amplitude data and/or volume data.
    The apparatus and/or the computer program product may he configured to perform any method described herein, or any aspect or feature of such a method.
    Features erf one aspe# of the invention may be applied to any other aspe# of the invention in any appropriate combination,
    Detailed description
    Embodiments of the Invention are now described, by way of non-limiting example with reference to the accompanying drawings, in which:
    Figure 1 is an illustration of a processing system according to an embodiment:
    Figure 2 is a schematic diagram showing stratigraphy and other eiements in an area that is tiro subject of a study described herein;
    Figure 3a Is a map view presenting variance time slice data at 1080 ms TWT, showing two fauit trends as linear eiements of lower coherency;
    Figure 3b shows a proposed strain ellipsoid for the fault system of the study area:
    Figure 3c shows a reservoir scafe faurf polygon used in the study:
    Figure 4 is a how chart iiiustrating a method used by the computing apparatus erf Figure 1 to process seismic speed/Velccity data and/or seismic amplitude data;
    Figure 5: is an illustration of flow for a computation of interval velocities, with tee original: stack shown ©n tee upper left plot* a derived skeleton or the upper right plot, raw Interval: velocities with no smoothing shown on the lower left plot, and a final, loaded interval velocity volume shown on the lower right plot;
    Figure 6 provides: amplitude volume and variance plots for: various identified vertical anomalies;
    Figure 7A Is a plot of RMS velocity in the interval 350-1750 ms TWT;
    Figures B to 7E are vertical cross section plots, each showing one or more vertical velocity anomalies;:
    Figure 8 is a map view, showing the location Of velocity anomalies as the features and Indicating the distribution of the Velocity anomalies with respect to average velocity;
    Figures 9a to 9d are map views, representing initiation levels (Figures 9a and 9b) and termination levels (Figures 9c and Sd) of mapped vertical anomalies;
    Figure IQ is a map view showing a distribution of velocity anomalies in relation to other shaiiow and/ot seafloor anomalies and reservoir scale faults;
    Figure 11 is a simplified diagram shewing API variations of fluids in the study area; and Figure 12 is a diagram (not to scale) illustrating possible relations between fluid migration and faults, surface karst, sinkholes, and gas chimneys.
    Methods according to described embodiments can be performed by a suitable processing device or system, for example a system comprising a suitably programmed processor and associated memory. Methods in some embodiments are performed using a suitably programmed d esktop com poter or portable computer.
    In one embodiment, Illustrated in Figure 1, the processing system comprises a computing apparatus 4, in this case a personal computer (PC) or workstation^ which is connected te a data store 6, a display screen 8 and an input device or devices, such as a computer keyboard 11 end mouse. In the embodiment of Figure 1, the computing apparatus 4 includes an anomaly identification module 12 and a seismic data processing module 14 configured to process seismic data to Identify anomalies, for example vertical anomalies, in seismic speed/veioc-ty anchor seismic amplitude data. Any suitable speed/velooity and seismic amplitude data can be used. In the study described:below in relation to the embodiment of Figure 1, interval veiocities derived from RfvIS velocities are used, in this case, the interval velocities were derived tom the RMS velocities using: the Dix method, but any: suitable method of deriving the interval veiocities can be used.
    In alternative embodiments, the display screen: is a touch screen, which also acts as an Input device, in further embodiments* the computing apparatus is a mobile device* for example a tablet; computer. Seismic data may be stored locally in the data store, or may be accessed frerna remote source by the computing apparatus, for example over a network:. The seismic data are obtained using: any suitable: known seism id measurement technigue. in the embodiment of Figure 1 the computing apparatus: 4 can be: connected to a seismic measurement system 10 used; to obtain seismic data via seismic measurements performed at a series of locations. Any suitable seismic measurement system may be used· in the case of the study described below relating to the region of Figure: 2, the computing apparatus 4 obtains previously logged seismic data, comprising 0-4 second TVVT 3D seismic reflection amplitude data, from a remote data store rather than from the seismic measu rément system directly.
    As will be discussed:: In more detail below, the competing apparatus: 4 Is configured to process seismic speed/velocity data and/or seismic amplitude data to determine the presence of one or more geological features each comprising at least one fluid migration feature,
    The operation of the computing apparatus 4 to process speed/velocity data and seismic amplitude data to identify fluid migration features is described In relation to a study concerning an oil/gas field, Oil production from the field that Is the subject of this study relies on horizontal driing and careful stimulation of the very thin end iow-permeable Cretaceous carbonate reservoirs. Although the field has been in production some uncertainties remain, particularly concerning fluid migration routes and charging of the field. As discussed further below. It has been found that the field appears to be effected by vertical anomalies which have the potential to act as vertical migration paths for fluid migration possibly impacting Huid distribution and characteristics at present day reservoir levels.
    Stratigraphy and main elements in the study area are shown schematically in Figure 2, and main fault trends In the study area are shown in Figures 3a to 3c. Figure 3a is a map view representing a variance time slice at 1080 ms TWT dearly showing the two fault trends as linear elements of lower coherency. The circular iow coherency areas correspond to the vertical anomalies. Figure 3b shows the proposed strain ellipsoid for the fault system and Figure 3c is the reservoir scale fault polygon used in this study.
    This study uses 3D seismic data: combined with a calculated interval velocity volume to analyse the vertical anomalies in more detail. The anomalies are vertically extensive and typically characterized by lower velocities- than the surrounding strata. They have been mapped according te teeir vertical extent, average velocity, any associated lateral effects, initiation and termination levels; and their relation to other features in the area.
    The respits of fee mapping suggest that fee majority of fee velocity anomalies are related to fluid migration wife gas causing the anomalous low velocities. The present day gas cap may have formed due to vertical migration of gas along fee velocity anomalies, which in the area of the gas cap are associated wife very low velocities and ail terminate at fee level of the reservoir, in fee areas north of the gas cap, the velocity anomalies generally terminate shallower suggesfingdhat fluid venting probably continued: to the seafloor thereby preventing gas accumulation in the reservoirs.
    As Is discussed in more detail below,, the study successfully Implements velocity date in the analysis of fluid migration routes and supplements the current understanding of some of the uncertainties. The results represent new inputs to the characterisation of fluid migration within the reservoirs and the existing production and may furthermore provide now input in the assessment of the future development of fee field.
    The method used by the computing apparatus 4 to process seismic speed/velooity data and/or seismic amplitude data is shown in overview in the flow chart of figure 4
    At the first stage 42 of the method., the seismic data; processing module 14 of the computing apparatus 4 receives and processes seismic velocity and amplitude data from the seismic measuremehf apparatus: or,; in feis case, tom a data store.
    The seismic data sn this case is a full 0-4 sec TWT 30 seismic reflection amplitude volume, interval velocities were calculated from the pre-stack seismic data as input to the velocity volume analysed in the study. A skeleton was used in order to ensure better geological constraints on. the interval velocities and strong smoothing (11x11 traces) were applied to fee final volume, Figure 5 Is an illustration of fee flow for the computation of interval velocities, with fee original stack shown on fee upper left plot, the derived skeleton on fee upper right plot raw Interval velocities wife no smoothing shown on the tower left plot and fee final loaded interval velocity volume shown on the lower right plot, where 11x11 smoothing has been applied.
    The processing of the seismic data at stage 42 comprised screening velocity and amplitude cross-sectlpris to Identify the presence of possible anomalies, in particular yertical anomalies in cross-sections of the seismic velocity and amplitude data. Two examples 44, 46 of possible vertical anomalies in RMS velocity data for one cross-section of the study are indicated in the velocity plot to the lette box 42 in Figure·4, Qorr&sponding possible vertical anomalies 4B, 50: in amplitude:data are shown in the amplitude plot'to the left of box 42 in Figure 4, Velocity anomaly 44 occurs! at substantially the; same position as amplitude anomaly 48, and velocity anomaly 46 occurs at substantially the same position as amplitude anomaly §0, in the present case the vertical anomalies are identified as being regions in the velocity {or amplitude) cress-sections for which the values of velocity (pr amplitude) are significantly different, either lower or hlghep than other values of velocity (or amplitude) at substantially the same vertical position. The possible verticai anomalies can be: identified by a user for example from inspection of map views and/or cross-section: velocity (or ampiltude) plots, in the case of such manual sdeniiitcation by a usee the use of automatically calculated RMS ampiitode/veiocsfy maps can help to identify areas In which to look for or validate the anomalies. Alternatively, the possible anomalies can be identified automatically by the ianomaiy identification module :12 of the:computing apparatus 4,
    For example, according to one automatic mode of operation the anomaly identification module 12 determines whether each velocity data point in the cross-section may belong to a possible vPdical anomaly in dependence on whether the value of the velocity ai that data point differs: from the average velocity value for data: points at tie same verticai position, or corresponding: position in the samp: stratum pf strata by greater than a threshold: amount. The anomaly identification module repeats the process for each: data point In the velocity (or amplitude) cross-section to identify those data points (which may be referred to as anomalous data points): that seem to represent velocity (or amplitude) anomalies.
    The anomaly: identification module 12 then determines whether the identified anomalous velocity for amplitude) data points form a region that may represent a vertical anomaly. For example, in one mode of operation the anomaly identification: module 12 determines whether there are connected anomalous data points forming a region of sufficient length and/or width or volume to be identified as a potential: verticai anomaly. For instance the anomaly identification module 12 may compare the vertical extent of a candidate anomaly formed from connected anomalous data: points to a length threshold to determine whether the candidate anomaly should be: considered to represent a vertical or other anomaly in the velocity (or amplitude data). Alternativelygr·additionally the.,anomaly identification module 12 can compare tie width and/or volume and/or area and/pr other size parameter of each candidate anomaly te width and/or volume and/or area and/or other size threshold(s) to make the determination, in some cases, the size threshold can effectively be set in the creation of the velocity volume by applying a lateral fitter based on reflectors in die seismic data. The decision as to whether to disregard a region as a potential vertical anomaly may depend on how weMefined tee region is and the context In which It was observed, as well as on the size of the region.
    Any: other suitebie automatic method or paftialiy-automatic method may be used by the anomaly Identification mode 12 to identify vertical or other anomalies in tee speed/veteoSy of ampiitude data, inciuding any suitable thresholding, edge detection, clustering or pattern matching methods.
    At the end of stage42, vertical anomalies in the velocity and/or amplitude data have been identified. At the next stage 52, the computing apparatus 4 maps the vertical anomalies in tee velocity and/or amplitude data and compares the vertical anomalies in a map view with other map view expressions. Usually various anomalies: :may be seen in the: seismic amplitude data,: but only some: of those are associated with a velocity anomaly, In tee present study, tee most significant vertical anomalies in the geology were mapped by implementing varying surface attributes, time slices of variance, correlation , ampiitude and exact values for mapped horizons. The main criterion for mapping a vertical anomaly in the geological structure in the present study was however the association With a significant velocity anomaly in order to discriminate between anomalies that may be conduits for hydrocarbon flow and those that mightcemehted or otherwise blocked.
    In some cases at stage 52, vertical anomalies present in one or more of RMS velocity and amplitude, time slices of variance, amplitude and velocity, and exact values for mapped horizons' are refected as not representing possible vertical geological features of relevance if no Corresponding significant vertical anomaly in the velocity date Is identified.
    At the next stage 54, each of the remaining candidate regions representing vertical anomalies are mapped and polygons are generated to represent the shape of the vertical anomalies in the horizontal plane, in some cases a full 30 representation of each anomaly, for example a 30 representation of the boundary of each anomaly can be generated using any suitable method of mapping 3D shapes.
    Upon mapping the vertical anomalies, their relations to overlying and underlying features may be tested at stage 56 in order to distinguish true vertical anomalies from varying imaging artifacts. This Included relation to faults, gas caps and incisions at reservoir levels* shallower karst features and channels, seabed reefe and data related artifacts. Well-data concerning fractures, faults and actual depressions can also be used wherever an anomaly is Intersected by a horizontal well with available data.
    At the ne^ stage 58t termination and initiation levels of each vertical anomaly are observed manually in the velocity and amplitude volumes. The termination level for a vertical anomaly may be considered to be the highest point of the vertical anomaly* and the initiation level for a vertical anomaly may be considered to be the deepest point of the vertical anomaly. In alternative modes of operation, the .termination and initiation leveis of each vertical anomaly may be determined automatically by the computing apparatus 4 rather than by manual inspection of the velocity and amplitudevolumes by a user.
    Since, in the present study date* the velocity volume only had a time range of 2 sec TWT the deeper initiation leveis were observed from the amplitude volume as the deepest level of acoustic disturbance and deformation. The average velocity within the vertical anomalies was noted, preferably at reservoir level. To accommodate manual errors*, the velocity readings were subdivided info bow (2000-3000 m/s), Medium (3001-350(5 mte| and High (3501 -5500 m/s) velocity grou ps.
    At the next stage 60. an interpretation:ef the cause of the vertical anomalies was generated for the present: study* and a model for the field was generated at stage 82, A total of 84 vertical anomalies were mapped In the data of the present study of Figures 2 and Figures 3a to 3c, The vertical anomalies are represented in the seismic amplitude and variance velurne data, and in the seismic interval velocity volume.
    Considering the seismic amplitude and variance volume data; first, in the present study the vertical anomalies typically occur as circular low coherency features in map view sections slich as those shown in Figure 6, which show®: characteristics of the verticai anomalies observed: in the amplitude· volume. On seismic cross-sections the anomalies have varying expressions, but the majority are characterized by lower amplitudes and acoustically distorted intervals* often comprising deformed reflections typically forming significant depressions. The depressions can be large: structures up to a few km in diameter and 50 ms TWT in depth with visible Internal ootapping reflections, or small narrow structures up to 500 m in diameter and 10 msTWT in depth. Furthermore, the degree of continuity through the depressions varies In addition to how well the depressions: are defined. The density of depressions in the amplitude volume varies with higher density at the top of the Jurassic period formation indicated In Figure 2 (c. 850 ms TWT) and in the interval above the reservoirs: |e. 300-600: ms TWTJ. . Considering Figure 6 in mom detail, amplitude volume plots for various ones of the anomalies are show in plots 76,7¾ 74,76,78, 80, 82. The anomaly of plot 70 provides a large, broad depression, continuous rejections, oniag infill, significant effect on undedying succession. The anomaly of plot 72 Is characterised by a fault-related poorly defined depression, significant deformation, and intense acoustic distortion below. The anomalies of plots 74 and 7f are two examples of narrow well-defined shallow depresslohScW^ acoustic distortions below. The anomaly of plot. 78 represents a typical depression for this study, with well-defined significance deformation, collapse of'ovedying: strata, and Imprint on underlying succession. The anomalies of plots 80 and 82 are anomalies with upward deformed reflections.
    Turning to the appearance of the vertical anomalies of the study in seisniie interval velocity volume data, the vertical anomalies are characterized in the velocity volume by vertically extensive areas of significantly lower velocities than the surrounding strata, as shown in Figures 71 to 7E, which shews characteristics of the vertioai anomalies in the velocity volume.
    Figure 7A is a plot of RMS velocity in the interval 360-1750 ms 1WT highlighting the main vertical anomalies in that interval as circular to semi-circular low velocity areas 84a, 840, 84c. 84d 84e, The labels A, B, C, F in Figure 7A represent the location of piatform areas, as also shown in Figure 8. The shown coiour/shading legend on the left hand side of Figure 7A, which indicates r.m.s, velocity value in metres/second, also applies to the vertical cross-sections shown in Figures 7B to 7E, each of which is a vertical cross section showing one or more vertical anomalies.
    Figure 7B shows two well defined vertioai anomalies with medium velocity, different termination levels, and pronounced lateral effects. Arrows 90, 92 point along the length of the two vertical anomalies of Figure 7S. The oval 91 shown In Figure 7B is included to indicate the presence of low velocities spreading laterally from the vertical anomaly indicated fey arrow 90, and is an example of different geological behaviour around a vertical anomaly, In this case pronounced lateral effects. The oval 93 shown in Figure 78 is included to indicate the presence of a high velocity anomaly above the velocity anomaly indicated by arrow 92.
    Figure 7C shows; two 'high velocity anomalies with significant lateral effects at their top. Arrows 94, 96 point along, the length of the two vertical anomalfes of Figure 7B: The oval 96 shown in Figure IG Is,: included to Indicate the presence of· the sfgjnffidadtiatbfa|:: d^!^ associated with the high velocity anomalies, not hydrocartaon-mlated In this case.
    Figure 7P shows two very well defined low Velocity anomalies with termination at the Eocene age level Indicated in Figure 2, where apparent lateral effects can be observed, Arrows 88, 100 point along the length of tl^:.'tw0'Vef8c9|'an<^!ld§ of Figure 7D.
    Figure 7E shows three shallow and poorly defined velocity anomalies, Arrows 102,104,106 point along the length of the three vortical anomalies of Figure 7E.
    Figure 8 is a map view, showing the location of the velocity anomalies as file features outlined In green, red and yellow. The distribution of the velocity anomalies with respect to average velocity is indicated by the different colours, with high average velocity features indicated in red, medium average velocity features indicated In yellow, and low average velocity features indioated in green, Superposed as curved black lines is the outline øf the Inferred: gas cap within the reservoir. The boundary of the study area is indicated by the polygon 110, Some seismic: data is obtained for areas outside the study area, as can be seen from the presence in the figure of a yeio„ ty anomaly outside the boundary of the Study area. The location of platform areas are inaicatoc by the black dels labelled A, 8. C, D, E, F, G, H and i in Figure 8.
    The majority of the mapped velocity anomalies are obvious from the mapped data: but subtler features have also been; mapped, Generally,, the vertical anomalies are characterized by Tow velocities but a few pronounced anomalies with higher velocities also occur (see for example Figures 7G and 8), Composite velocity anomalies with, for instance,: high velocities in the centre and low velocities at the edges have been observed. The areal distribution of the anomalies with respect to average velocity generally show low to medium velocity anomalies in foe southern and central parts where an inferred gas cap occur in the reservoir succession, and high velocity anomalies in the northern part of the study area (Figure 8). Lateral effects such as anomalous low or high velocity layers at the top of an anomaly or high velocities extending from the edges of an anomaly are freguentiy observed (see for example Figures 7BS C and 70).,
    The main criterion for mapping a vertical anomaly in this study was, as mentioned, the association with a significant velpcify' enorrøjy,. observed in the amplitude volume with no significant velocity anomalies have not been mapped in Figures 7 or 8, Some vertical anomalies are only recognised in the veiodty volume and have no expression in the amplitude volume. However, the major end larger anomalies of the study typically have a distinct signature in doth the amplitude and: the velocity volumes.
    Figures 9e to id are map views, showing initiation levels (FiguresdSadand 9fe) and fermihatiioh levels (Figures 9c and 9d) of the mapped vertical anomalies. Beth overall (Figures 9a and 9c) and detailed (Figures 9b and 9d): levels are shown. Deep initiation, as indicated in FigureoSa.. is generally' below level 9 (corresponding to the top of the Jurassic age formation In Figure 2). of the stratigraphic levels listed in Table 2 below, whilst shallow initiatioh is above level 9. The detailed initiation levels indicated in Figure ©b are subdivided into 8 levels, whilst the detailed termination levels indicated In Figum id are specified to 12 levels.
    Superposed in Figures 9a to 9d as curved black lines is the outline of the inferred gas cap within the reservoir. The boundary of the study area is indicated by the polygon 119. The location of platform areas are Indicated % the black dots labelled A, B, Q, D, E. F, G, H and I in Figures 9a to 9d. Termination levels at stratigraphic levels 1 to 12 of Table 2 are indicated In Figure 9d. in the ease of the study of Bgures2:and 3a to 3c, there seems to be no overall pattern in the areal distribution of the initiation levels, with deep and shallow initiation levels occurring throughout tine study area, as Indicated in Figures 9a and b. However, as shown In Table t there is a small majority of snpmaiies initiating tom the deeper leyelsat 1299-1609: TWT (ms) and 1690-1900 TWT f ms) (66 %). This may indicate that the majority of the anomaltes have a deeper origin which could be related tp: the thermogenic gas system i.e. formed duringeecenctary gas migration tom the reservoir,
    Table 1: Distribution of approximate Initiation ievets for the vertical anomalies. Compare with Fig, 8b.
    Table 2 provided below gives: a stratigraphic distribution of termination levels for seme of the Vertical anomalies, and: can be cprnparedi wlfl'5 Figure 9c!, Table :2 highlights the observed detailed termshatipn levete, with 3 % of the anomalies Mririin&tirig above the reservoir succession, 39 % terminating within the reservoir succession and 24 % terminating at levels below the reservoir succession. The anomalies terminatlhQ above the reservoirsi tend to occur In the central and northern part of the study area« while there is a predominance of anomalies with termination af reservoir tevel in the southern part of the study area (Figures 9c and Sd).
    74% of the mapped vertical anomalies of the study occur at fault planes Interpreted at reservoir-level, while 26% appear to have no association with faults, as indicated in Figure 10, which is a map view showing the distribution of the velocity anomaiies (in blue) in relation to the reservoir scale faults (in yellow}. Of the feulbrelated anomalies 63% occur at the primary fault trend (47% of all anomalies), 26% occur at the intersection between the two fault trends (19% of all anomalies}, and only 11% occur at the secondary fault trend (8% of ail anomalies). This relationship suggests that the primary fault trend (WNW-ESE) has been øf major Importance in the generation and distribution of the vertical anomalies mapped in the present: study.
    Severn! géologieai phenomena can give rise to vertically extensive seismic anomalies with a circular to serni-eifpuiar map view expression, such as stacked paieo-peckmarks (Andresen 5 Hunse:7fBulls-eye: pockmarks and polygonal faulting in the tower Congo Basin: relative timing and implications for fluid: expulsion during shallow burialo Marine Geology 27¾ 111-127,), surface karst sinkholes; and dissolution collapse (s.g. Hardage et at, 1988, “3-D seismic evidence'of the effects: of carbonate karst collapse on owriyihg classic stratigraphy and reservoir ppmpartmeniaiization’ Geophysics, 61, 1036-1360; McDonnell et at, “Quantifying the origin and geometry of circular sag structures in northern Fort Worth Basin, Texas: Paleocave collapse,: puli-apart fault systems,, or hydrothermal alteration ” AAFG .Bulletin 91 (9),: 1295-1318;;: Stewart, “Seismic Interpretation of circular geological features”, Petroleum Geoscience IS* 273-285, 1999), fault related tectonic sags and other fault anomalies, salt displrs and salt dissolution (e,g. Stewart, "Seismic interpretation of circular geological features", Petroleum Geoscience 5* 273-285,1999), gas chimneys (Loseth et a!,, 2000, “Hydrocarbon leakage Interpreted on seismic data·’, Marine and Petroleum Geology 26,1304-1319), fluid expulsion pipes (e,g. Berndt, “Focused fluid flow in passive continental margins*, Philosophical Transactions, Senes A, Mathematical, Physical and Engineering Sciences 363, 2855--2871, 2005; Moss & Dartwright, "The spatial and temporal distribution of pipe formation, offshore Namibia^ Marine and Petroleum Geology 27,1215-1234,2010), mud volcano systems (Stewart & Davies, “Structure and emplacement of mud volcano systems In the South Caspian Basin”, Amæoan Association of Petroleum Geoioglsts BulieMn 90, 771 -786, 2006) ånd other vertically focused fluid migration features (Cartwright et ai., "’Seal bypass systems”; American Association øf Petroleum Geologists Bulletin 91, 1141-1166,26077
    The carbonate environment of this study makes karst-related features such as surface karst, sinkholes and dissoiytion cofiapse depressions very likely candidates for the origin of the vertical anomalies, Addiifonaity, since the study area Is heavily faulted and many of the anomalies are fault-related, tectonic sags are likely to account for several of the anomalies. There also appear to be some candidates for true gas chimneys among the vertical a nomaifes (Table 3),
    The fluid migration system in the study area includes several potentially migrating fluids such as thermogenic Oil, thermogenic gas, biogenic gas (shallow gas), ground water and hot formation water, as can be seen from Figure 11. Figure 11 is a simpiified diagram showing potential fluids- in the study area. Red arrows indicate gas migration and green arrows indicate oil migration. Figure: 11 is not to scale, and timing is hot included.
    Several approaches have been used In connection with present study in order to assess whether the: vertical: anomalies may be associated with fluid migration. These include observations of acoustic disturbance, continuity, coherency, reflection strength and reflection configuration within the anomalies and: the velocity signature. In this connection low velocity anomalies may foe related to the presence of gas In the: sediment and: high velocity anomalies may reflect cemented conduits also forming during fluid migration, Lateral effects associated id the velocity anomalies are potentially a positive indicator of fluid migration revealing secondary alterations of the near-by sediments resulting from upward fluid migration Within the vertical conduit.
    Figure 12 is a diagram (not ίο scale) illustrating the possible relations Between fluid migration (red arrows) and faults, surface karst, sinkholes, and gas chimneys. Based op the analysis of the present study it is concluded that the majority of the mapped vertical anomalies are related to fluid flow. Fluid migration is thought to be involved in the formation of the vertical anomalies in three ways, as indicated schematically in Figure 12 and as discussed below:- 1) Fluid migration along fault zones.
    Fault zones acting as weakness zones and competent fluid migration routes. Due to the high density of faults in the study area, this is proposed as the main mode for vertical fluid migration. 2) Fluid migration in relation to sinkholes and shallow karst features
    Karst processes could be facilitated and/or enhanced by focused fluid migration. Alternatively; sinkholes and surface karst could represent already established weakness zones and hence preferred fluid migration routes. 3} Gas chimneys,
    Verilcaiiy-focused fluid migration along conventional acoustically distorted gas chimneys with a deep initiation. The ascending fluids within the gas chimneys may cause upward deformation of the strata and/or velocity puli-up.
    The three elements are oioseiy connected and typically more than one element may have worked in the generation of the discrete vertical anomalies. For instance, sinkholes and surface karst typically occur above faults indicating that faults represent preferred fluid migration routes which facilitate and control the location of karst processes during sub-aerial exposure,
    Production data and gas samples from horizontal wells suggest the presence of a distinct gas cap within the reservoir. Observations which may help explain the present;day position of the gas cap are: 1} The gas cap area correlaies with vertices anomalies characterised by a. .low and medium velocities (see Figure 8}, b, medium to high API gravities. c. predominant termination ieveis (see Figure. 9d). d, predominant apparent deep initiations from the early classic and middleio late permian levels indicated in Figure 2 (1200 to 1600TWT (ms)) and deeper levels (see Figure 0b). 2) The gas cap area correlates with abundant depressions at the top sf the Jurassic age formation indicated in Figure 2, 3) The area to the north of the gas cap is associated with shallower termination levels predominantly at the top erf the stratigraphic level 2 indicated In Tabie 1 (in the Eocene age formation indicated in Figure 2) - see Figure $&
    These observations suggest that the gas cap could be associated with vertical gas migration from a;:ddépørsugcto^toh/(stratigrdphic level 3 of Table 1) into the reservoir succession. The areal extent of the gas cap appears to be strongly related to the north-south variation: in termination levels. To the north the majority of the vertical anomalies continue above the reservoirs to the top of the stratigraphic level 2 formation indicated in Table 1 (Eocene), thereby bypassing the deeper reservoirs and apparently preventing gas cap formation. However shallower reservoirs have gas in northernmost part, which may be associated with lateral migration of gas. To the south the vertical anomalies terminate within the reservoir succession and: possibly facilitate the formation of the gas cap.
    The study discussed above in relation to Figures 2 to 12 presents a detailed analysis of abundant: vertical anomalies found in relation to an oil field under investigation. The analysis was carried out with two main objectives aiming to accomplish a better understanding of: a) the charging history of the field b) the migration routes into the field
    The results of the analysis provide insight relevant to both objectives and may contribute to the further development of the field. A mam element of the analysis was the successful implementation of an interval velocity volume In the seismic Interpretation, and 84 distinct vertical velocity anomalies were mapped. The velocity, anomalies are characterized by anomalous vertically extensive and typically lower interval velocities than the surrounding strata. Fluid migration is interpreted to have occurred along the majority of toe veiocity anomalies and they may thus be characterized as vertical fluid migration routes.
    The velocity anomalies have been subdivided into five primary: genetic origins including gas chimneys, surface karst* slnkhoies/coiiapse depressions*.. fault-related tectonic sags, and other fault-related anomalies. Fluid migration is Interpreted to occur along fault: planes* gas chimneys, and karst features and may also have facilitated dissolution of the carbonates in certain: areas. Major eontrpiiing factors for too formation and timing of the veiocity anomalies 'includes: faulting,. source rock maturation, pateotc^ograph^ (distribution of structural highs), and periods of sub-aerial exposure, Fanifing and source rock maturation are the primary controlling factors.
    The majority of the velocity anomalies of the present study v^ere generated 70-50 Ma. ago and ere .related to major faulting and gas expulsion fern the source rock. Oil charging of the Field occurred later· '{< 45 Ma) and re-iisc of the already established -fluid migration mutes prohahiy represented a critical element of the charging, A gas cap is present in the study area, The inferred area of the gas cap correlates with velocity anomalies that general iy are characterised by; a) medium to high Oil gravities within the reservoirs b) tow to medium velocities c) terminations at reservoir level d) apparent deep initiation levels
    These observations suggests that: the gas cap js related to gas and secondary vertical gas migration from the reservoirs, rather than being merely associated gas. in the northern part the velocity anomalies terminate af much shallower depths (at the top of stratigraphic level 2 of Table 2, Eocene) indieeting bypass of the reservoirs.
    As discussed above, 1 has been shown that for the present study the presence of fluid migration features can be determined from anomalies, in this case vertical anomalies, in seismic velocity data, in turn, the fluid migration features can be correlated with the presence and location of oil or gas deposits.
    As well as modelling the charging history or migration routes for existing known oil or gas deposits:, as is the base the for study described above, the embodiment of Figure 1 can also be used for predictive purposes, for example to predict the location of possible oii or gas deposits, and/or foSeieehr^iohS-forfUrther exploration or analysis,
    In one mode of operation, seismic speeri/veiocify data and/or amplitude data for a region is processed/by the processing system of Figure d to determine the presence of speed/velociiy ianomalles (oramplifudeanomaleslthat may be associated: with I did migration features and to select a region for further exploration or analysis based on the presence and location of such speed/veiocity anomalies (or amplitude anomalies). if fluid migration features are determined to be present, based on the presence of the speed/veloctty anomalies of suitable characteristics, then in some modes of operation a region is selected for further exploration or analysis if the vertical anomalies (and hence the fluid migration features) are proximate to, terminate at, lead to or from the region, as that suggests that fluid (e.g< oil or gas) may have migrated to that region.
    The selection of a region for further exploration or analysis may also be based on further seismic or other measurements, that support the conclusion that the speed/veiocity anomalies may be associated with fluid migration features* and will also usually be based on an assessment of the general geology of the region and its surroundings to determine whether It is likely that oil or gas may have migrated along the fluid migration features.
    The region may be selected in dependence on the number, concentration or size of anomalies associated with said region, for example the number, concentration or size of identified anomalies proximate to, terminating at, leading to or from said region, or extending wholly or partly within said region. For instance* a region may only be selected in some cases if the number, concentration or size of the anomalies suggest that a significant amount of oil or gas may have migrated to the region.
    The further exploration or analysis may involve further processing of seismic or other data, performance of further seismic or other measurements, or performance of a physical intervention, for instance an exploratory drilling operation, to determine the presence of oil or gas or to provide a more accurate assessment of whether oil or gas may be present in the region.
    In some embodiments, a mapping is performed by the processing system to determine where fluids, for example, hydrocarbon fluids, may have moved in dependence on the presence, position, size, concentration or other property of the identified at least one fluid migration feature. The selection of the region for further exploration or analysis may then he performed in dependence on the mapping. in some embodiments, a further or more detailed analysis is performed to determine whether anomalies in speed and/or velocity and/or amplitude data may represent significant potential fluid migration routes^ For example, such anomalies may be correlated with other seismic or other measurements, or it may be determined whether a property or properties of each anomaly match a predetermined pattern, for example whether a speed/veiocity or amplitude profile matches a predetermined pattern, in some cases, size (e.g, width, length, volume) thresholding may be applied to select the most significant anomalies.
    It has been found the detection of speed/veloeity and/or amplitude anomalies can provide a simple and effective way to determine the presence and location of possible fluid migration features. Knowledge of the presence and location of such possible fluid migration features can in turn be used t© predict ^lippatiph pf/pd^f#!© oil or gas deposits, dr at feast be used in selecting regions for exploration or further analysis or measurement.
    Embodiments, or features of such embodiments, can be implemented as a computer program product for use with a computer system* the computer program product being, for example, a series Of computer instructions stored on a tangible data recording medium, such as a diskette, CD-ROM, ROM, or fixed disk, or embodied in a computer data signal, the signal being transmitted over a tangible medium or a wireless medium, for example, microwave or infrared. The series of computer Instructions can constitute ail or part of the functionality described herein, and can also be stored in any memory device, volatile or nonvolatile, such as semiconductor, magnetic, optical or other memory device. it will also be well understood by persons of ordinary skill in the art that whilst embodiments implement certain functionality by means of software, that functionality could equally be implemented solely in hardware (for example by means of one or more ASICs (application specific integrated circuit}} or indeed by a mix of hardware end software. As such, tie scope of the present invention should not be interpreted as being limited only to being implemented in software. it will be understood that embodiments of the present invention are described purely by way of exarnpte, and modifications of detail can be made within the scope of the ; inventron. Each feature disclosed in the description, and (where appropriate:} the drawings may be provided independently or in any appropriate combination.
    权利要求:
    Claims (15)
    [1] 1, A method of identifying at least one fluid migration feature, comprising receiving seismic data and processing the seismic data to identify the at least one fluid migration feature, wherein the seismic data comprises speed or velocity data and/or seismic amplitude date.
    [2] 2, A method according to Cialm 1. wherein:- the identifying øf the at least one fluid migration feature comprises determining the presence of the at least one fluid migration feature; the at feast one fluid migration feature comprises at least one hydrocarbon fluid migration feature; the speed or velocity data and/or seismic amplitude data Is speed or velocity data; the processing of the seismic data comprises processing the seismic data to identify at least one .substantially vertical anomaly in the speed or velocity data; and the method further comprises:-· reiating the at least one substantially vertical anomaly In the speed or velocity data to at least one hydrocarbon fluid migration feature thereby to obtain said determining of the presence of the at;least one hydrocarbon fluid migration feature: and selecting a; region for further exploration or analysis in dependence on whether said substantially vertical anomaly In the speed or yefccity data is associated with said region,
    [3] 3, A method according to Claim 1 wherein the processing of the seismic date comprises: processing the/seismic data to identify at least one anomaly In the speed or velocity' data ppd/or the: amplitude data,
    [4] 4, A method according to Claim 3, comprising relating the at least one anomaly In the speed or velocity data and/or the amplitude date to the fluid migration feature,
    [5] 5, A method according to Claim 3 or 4, wherein the at least one anomaly comprises at least one substantially vertical anomaly.
    [6] 8. A method according to any of Claims 3 to 5, further composing determining whether the identified speed or veiocity anomaly, and/or tee identified amplitude anomaly matches a predetermined pattern or possesses at least one predetermined property: T, A method according to Claim 6: wherein the predetermined pattern or at: least one predetermined property represents a variation of velocity or speed with lateral position, or a variation of amplitude with latera! position, B, A method according to Claim 6 or t, wherein the pattern is representative of higher Velocity or speed at the centre of a velocity anomaly region and lower velocity or speed at least one edge of a velocity anomaly region, or vice versa.
    [7] 9, A method according to any of Claims 3 to 8. further comprising selecting in dependence on depth one of the speed/veipclty data and the amplitude data for use in identifying the at least one anomaly.
    [8] 10, A method according to any of Claims 3 to 9, wherein the identifying of at least one of the anomalies comprises identifying the anomaly using speed or velocity data for: depths less than a depth limit and identifying the anomaly using the amplitude data for depths: greater than the depth limit, 11, a method according to any preceding claim, wherein the fluid comprises comprise a hydrocarbon fluid, for example oil or gas,
    [9] 12, A method according to any preceding claim, wherein the at least one fluid migration toatore is asspoiated at least one of a fracture, fault, depression, incision, karst feature, cap, channel, sinkhole, or reef feature.
    [10] 13, A method according to any preceding claim, comprising determining at least one of a termination levei dr an initiation level of the anomaly from ahd/Pr ampiiigde data* for example a velocity volume and/or amplitude volume obtained from the seismic data.
    [11] 14, A method according to any preceding claim:,: further comprising selecting a region for further exploration of -analysis in dependence on -whether an anomaly is identified .
    [12] 15, A method according to Gialm 14, comprising selecting the region in dependence on whether at least one anomaly is associated with said region, for example is proximate te, terminates or initiates at said region, leads to or from said region, or extends wholly or partly within said region.
    [13] 18, A method according to Claim 14 or 15, comprising selecting the region in dependence in on the number, concentration or size of anomalies associated with said region, for example the number, concentration or size of identified anomalies proximate to, terminating at, initiating at, leading to or from said region, or extending wholly or partly within said region.
    [14] 17. A method according to any of Claims 14 to 16, wherein the method comprises making a prediction as to whether said selected region or regions contain hydrocarbons, for example oli or gas. 18. Å method according to any of Claims 14 to 17, wherein the further exploration or analysis comprises further processing of seismic or other data, performance of further seismic or other measurements, of pedermanee of a physical intervention, tor Instance an exploratory drilling operation.
    [15] 19. A method according to any preceding claim, comprising mapping where fluids, for example, hydrocarbon holds, may have moved in dependence on the presence, position, size, concentration or other property of the identified at least one fluid migration feature, 2D, An apparatus comprising a processing resource configured to receive seismic data and to process the seismic data to identify at least one fluid migration feature, wherein the seismic data comprises speed or velocity data and/or seismic amplitude data. 2:1. A computer program product comprising cømputeAreadahie instructions that are executable to perform a method according to any of Claims 1 to 19,
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    同族专利:
    公开号 | 公开日
    US20160245940A1|2016-08-25|
    GB201318069D0|2013-11-27|
    GB201400831D0|2014-03-05|
    US10302787B2|2019-05-28|
    EP3055714A1|2016-08-17|
    WO2015052334A1|2015-04-16|
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    法律状态:
    2019-05-06| PHB| Application deemed withdrawn due to non-payment or other reasons|Effective date: 20190419 |
    优先权:
    申请号 | 申请日 | 专利标题
    GB201318069A|GB201318069D0|2013-10-11|2013-10-11|Seismic data processing method and apparatus|
    GB201318069|2013-10-11|
    GB201400831|2014-01-17|
    GB201400831A|GB201400831D0|2013-10-11|2014-01-17|Seismic data processing method and apparatus|
    EP2014071811|2014-10-10|
    PCT/EP2014/071811|WO2015052334A1|2013-10-11|2014-10-10|Seismic data processing method and apparatus|
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