Abstract:
A method of determining the quality of seismic data comprises the steps of defining a predetermined threshold (step  12 ) from a characteristic of a first set of seismic data and translating the difference between the predetermined threshold and the corresponding characteristic of a second set of seismic data into a measure of quality of the second set of seismic data (step S 16 ).

Description:
BACKGROUND OF THE INVENTION 
     The present invention relates to a method of and an apparatus for determining the quality of seismic data during or after a seismic survey. 
     At present, the quality of a seismic survey is generally determined by use of instruments or engineering specifications located above a survey site, for example a fixed μbar limit for ambient noise or a prescribed gun drop-out limit. In some cases, failure to meet these criteria can lead to a survey being halted unnecessarily, resulting in increased cost through loss of production. 
     SUMMARY OF THE INVENTION 
     According to the present invention, there is provided a method of determining the quality of seismic data, comprising the steps of defining a predetermined threshold from a characteristic of a first set of seismic data and translating the difference between the predetermined threshold and the corresponding characteristic of a second set of seismic data into a measure of quality of the second set of seismic data. 
     Preferably, the first set of seismic data comprises a model used to define the predetermined threshold. 
     Preferably, the predetermined threshold is defined using existing seismic data. 
     Preferably, the first set of seismic data comprises a plurality of seismic traces and the predetermined threshold is modified on the basis of a succeeding set of seismic traces. 
     The characteristic may be the resolving power, the resolving factor, the signal-to-noise ratio, the effective bandwidth, the detectability, the upper frequency range, or the lower frequency range of the seismic data. 
     According to a second aspect of the present invention, there is provided an apparatus for determining the quality of seismic data, comprising a means for defining a predetermined threshold from a characteristic of a first set of seismic data, and a means for translating the difference between the predetermined threshold and the corresponding characteristic of a second set of seismic data into a measure of quality of the second set of seismic data. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The invention will now be described in greater detail, by way of example, with reference to the accompanying drawings, in which: 
     FIG. 1 is a schematic diagram of a survey site; 
     FIG. 2 is a flow diagram showing method steps for surveying the survey site of FIG. 1 according to an embodiment of the present invention; 
     FIG. 3 is a schematic diagram of a step of FIG. 2 in greater detail; 
     FIG. 4 is a schematic diagram of an old and predicted attribute in accordance with the embodiment of FIG. 2; 
     FIG. 5 is a schematic diagram of an old, predicted and actual attribute in accordance with the embodiment of FIG. 2; and 
     FIGS. 6 and 7 are a real plots of the survey site of FIG.  1 . 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT 
     Referring to FIG. 1, a marine survey site  2  comprises a region of low loss and a region of high loss beneath the surface of the survey site  2 . The region of high loss, in this example, is due to a ridge. A set of well bore data, for example, bore logs and VSP data from a well  4  and a set of surface seismic data taken along lines  1 ,  2  and  3  from previous seismic surveys of the survey site  2  are available (not shown). The term “a set of seismic data” includes one or more seismic traces. 
     The known well bore data and surface seismic data are retrieved (step S 2 , FIG. 2) and used to evaluate and design a new seismic survey (step S 4 ). 
     Referring to FIG. 3, objectives of the new seismic survey, for example formation depth, structural setting and lithological description of a prospect model, are defined (step SED 1 ) and a set of “required” geophysical parameters are defined (step SED 2 ), for example, target resolution parameters, such as interval velocities, resolution requirements and source energy. 
     The known well bore and surface seismic data are analysed (step SED 3 ) in conjunction with other available data, such as tidal information and weather reports, in order to define a set of corresponding achievable geophysical parameters (step SED 4 ). For example, VSP data is used as a measure for determining signal bandwidth. Other parameters include temporal resolution, migration aperture, signal to noise ratio, spatial resolution, offset distribution and azimuth distribution. 
     The required and achievable geophysical parameters are compared (step SED 5 ) in order to determine if the above objectives can be met and a set of preferred acquisition and geophysical parameters are defined (step SED 6 ), provided that the required geophysical parameters are within the scope of the achievable geophysical parameters. However, if the required geophysical parameters are not achievable, the above objectives are modified until the required geophysical parameters fall within the achievable geophysical parameters (step SED 7 ). Examples of the preferred acquisition and processing parameters include source and streamer depths, group and shotpoint intervals, in-line and cross-line CMP spacing, record length, migration aperture, receiver offset range, shooting direction, maximum feather, amplitude v. offset (AVO), dip moveout (DMO), demultiple, noise suppression, imaging and sampling interval. 
     The operational costs and constraints are then examined (step SED 8 ) in order to ascertain whether the preferred acquisition and processing parameters are feasible on the basis of the costs and equipment constraints. For example, resolution has a direct effect on the costs of line spacing. If necessary, the objectives are redefined in order to take account of the above constraints in order to provide the final “optimum” acquisition and processing parameters. 
     Once a final set of optimum acquisition and processing parameters are defined (step S 6 , FIG.  2 /step SED 6 , FIG.  3 ), a set of Quantitative Quality Assurance (QQA) parameters are measured (step S 8 ) for the known data. On the basis of the final parameters (which may differ, for example, in acquisition parameters from the known data), the QQA values are modified (step S 10 ) by modelling the expected changes due to the preferred parameters. The modified values are then used to define the minimum acceptable threshold above which the attribute of the newly acquired seismic data must remain in order to be of an acceptable quality to attain the objectives defined. Such a situation can arise when, for example, the known seismic data is acquired using deep streamer cable and the evaluation and design of the new seismic survey indicates that the optimum acquisition parameters should include shallow streamer cable. Other parameters include: source depth, source volume, trace interval and fold. Table 1 below shows old and new values of acquisition parameters and the effect of changes therein on newly acquired seismic data. 
     
       
         
               
             
               
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 Effects of changes in acquisition parameter values. 
               
             
          
           
               
                 Parameter 
                 Old value 
                 New value 
                 Effect on new data 
               
               
                   
               
               
                 Source vol. 
                 6400 cu in 
                 3397 cu in 
                 Higher ambient 
               
               
                   
                   
                   
                 noise 
               
               
                 Source depth 
                    4 m 
                   5 m 
                 Slightly lower 
               
               
                   
                   
                   
                 frequency 
               
               
                 Cable depth 
                    7 m 
                   7 m 
                 None 
               
               
                 Group interval 
                 16.667 m 
                 12.5 m 
                 Shots have less 
               
               
                   
                   
                   
                 random noise 
               
               
                 CMP interval 
                  8.33 m 
                 12.5 m 
                 Stack has more 
               
               
                   
                   
                   
                 random noise 
               
               
                 Fold 
                 60 
                 40 
                 Stack has more 
               
               
                   
                   
                   
                 random noise 
               
               
                   
               
             
          
         
       
     
     In order to define the thresholds, sample wavelets are taken from the known surface seismic data. The surface seismic data can be surface seismic data which has been calibrated against borehole derived wavelets (where available) at intersection points between the surface seismic data and the borehole location or theoretically calculated wavelets using a given geological model. Various attributes or characteristics of the wavelets, for example, the High Frequency Effective Bandwidth (HFEB), are determined and a corresponding set of predicted attributes are derived (FIG.  4 ). The thresholds of the attributes are then set (step S 12 ). 
     Table 2 shows an example of attributes and their threshold values. 
     
       
         
               
             
               
               
               
               
             
               
               
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 Attribute thresholds 
               
             
          
           
               
                   
                 Attribute 
                 Shots 
                 Stacks 
               
               
                   
                   
               
             
          
           
               
                   
                 Resolving Power 
                 10 
                 20 
               
               
                   
                 Resolving Factor 
                 30 
                 40 
               
               
                   
                 Signal to Noise 
                 30 
                 80 
               
               
                   
                 Detectability 
                 100 
                 1000 
               
               
                   
                 High Frequency (Hz) 
                 20 
                 30 
               
               
                   
                 Low Frequency (Hz) 
                 20 
                 20 
               
               
                   
                   
               
             
          
         
       
     
     Referring back to FIG. 4, curve A shows the high frequency effective bandwidth of the known seismic data and curve B shows the predicted high frequency bandwidth for the new seismic data to be acquired. On the basis of curves A and B, a threshold value of 30 Hz is set as the minimum value of the predicted HFEB (shown as broken line C) within a margin of error. 
     The new seismic data is then acquired (step S 14 ) and one or more of the above mentioned attributes of the newly acquired data is compared with the corresponding thresholds (step S 16 ). If the seismic data is of sufficiently good quality (within specification), the or each attribute is equal to or greater than the corresponding threshold and the acquisition continues. 
     If the quality of the data is unacceptable (below specification), the cause of the poor seismic data quality is investigated (step S 18 ). If the cause is found to be of a geological nature, for example a ridge, all effected attribute thresholds are modified or the acquisition redefined (step S 20 ), for example, by adjusting the depth of the streamers. If it is found that the cause is acquisition related, for example poor weather or equipment failure, a decision is made as to whether to reacquire the effected seismic data, or whether to simply correct it (step S 22 ), for example, by correcting a technical failure, such as air pressure or gun synchronisation. If a decision is made to reacquire the seismic data, the seismic data which is below specification is reacquired (step S 24 ) and step S 16  is repeated (and steps S 18  to S 28 —depending on whether or not the reacquired seismic data is within specification). If a decision is made not to reacquire the seismic data, the seismic data can either be corrected (step S 26 ) or if, deemed appropriate, the correction step is omitted (see broken line—step S 28 ) and acquisition of the new seismic data is continued. 
     When the seismic survey of the survey site  2  has been completed or during acquisition of the new seismic data, the actual high frequency bandwidth or other attributes of the acquired seismic data can be calculated and plotted. Curve D in FIG. 5 represents the high frequency bandwidth of the newly acquired seismic data and is above the 30 Hz threshold previously set. This indicates that this attribute of the newly acquired seismic data is within specification and so of an acceptable quality. 
     An a real plot of the high frequency bandwidth or other attributes of the newly acquired seismic data can be generated (FIG.  6 ). The darker regions of the plot represent areas of the survey site  2  where the high frequency bandwidth attribute of the new seismic data is within specification. The lighter regions of the plot represents areas where the high frequency bandwidth attribute has fallen below an acceptable quality threshold and so is below specification. 
     By comparing the a real plot of FIG. 6 with the survey site  2  of FIG. 1, it can be seen that there is a correspondence between the areas of high loss of the survey site  2  and the lightly shaded areas, especially the upper right hand quadrant of the a real plot. As described above, the cause of such results has to be investigated to determine whether the result is due to the geology of the survey site  2  or acquisition problems. 
     As another example, an a real plot of the resolving factor of the newly acquired seismic data can be generated (FIG.  7 ). 
     It is also possible to generate a final a real plot consolidating previous individual plots relating to individual attributes. 
     The a real plots can be generated in colour in accordance with a “traffic light” scheme. Areas where an attribute is clearly within specification can be plotted in green, areas where the attribute is marginally in or below specification can be plotted in amber, and areas where the attribute is clearly below specification can be plotted in red. 
     Although the above embodiment describes a ‘real time’ seismic survey where the quality of seismic data is evaluated as it is acquired, it is conceivable to evaluate the quality of the seismic data in accordance with the invention once the entire survey site  2  has been surveyed. However, the reacquisition of seismic data over areas having acquisition related problems is no longer possible. 
     The above embodiment has been described in the context of a marine seismic survey. However, it should be noted that the above invention can be equally applied to land seismic surveys.