SYSTEM AND METHOD FOR DETERMINING A SET OF FIRST BREAKS OF A SEISMIC DATASET

Abstract

A system and method for determining a set of first breaks of a seismic dataset are disclosed, the method including obtaining the seismic dataset composed of a plurality of seismic traces and a provisional first break for each seismic trace. The method further includes selecting a plurality of proximal picks for each seismic trace, determining a near-offset pick for each seismic trace starting with shortest offset and sequentially selecting traces in order of increasing offset, and determining a far-offset pick for each seismic trace starting with the farthest offset and sequentially selecting traces in order of decreasing offset. The method further includes determining a set of coincident picks based on the near-offset and the far-offset picks for each seismic trace, fitting a curve to the set of coincident picks, and determining the set of first breaks of the seismic dataset from the curve.

Claims

1. A method of determining a set of first breaks of a seismic dataset generated by a seismic source, comprising: obtaining the seismic dataset, wherein the seismic dataset comprises a plurality of seismic traces and a provisional first break for each of the plurality of seismic traces; selecting, using a computer processor, a plurality of proximal picks for each seismic trace, wherein each proximal pick lies within a time window enclosing the provisional first break; determining, using the computer processor, a near-offset pick fora seismic trace with a shortest offset and sequentially selecting, in order of increasing offset, a selected trace and determining the near-offset pick for the selected trace based on proximal picks of the selected trace and the near-offset pick for at least one seismic trace with a shorter offset than the selected trace; determining, using the computer processor, a far-offset pick for a seismic trace with a farthest offset and sequentially selecting, in order of decreasing offset, a selected trace and determining a far-offset pick for the selected trace based on the proximal picks of the selected trace and the far-offset pick for at least one seismic trace with a farther offset than the selected trace; determining, using the computer processor, a set of coincident picks based on the near-offset pick and the far-offset pick for each seismic trace; fitting, using the computer processor, a first break curve to the set of coincident picks; and determining, using the computer processor, the set of first breaks of the seismic dataset based, at least in part, on the first break curve.

2. The method of claim 1, wherein selecting a plurality of proximal picks for each seismic trace comprises: forming, using a computer processor, a positive trace from each of the plurality of seismic traces; determining, using the computer processor, a centroid time for each of a plurality of lobes of each positive trace; and selecting, using the computer processor, for each positive trace, the plurality of proximal picks, wherein each proximal pick comprises one centroid time lying within the time window enclosing the provisional first break.

3. The method of claim 1, wherein the set of first breaks of the seismic dataset comprises a first break for each seismic trace having a coincident near-offset pick and far-offset pick.

4. The method of claim 1, wherein the set of coincident picks comprises a coincident pick for each seismic trace for which the far-offset pick and the near-offset pick are identical.

5. The method of claim 1, wherein the plurality of proximal picks for each seismic trace comprises at least one proximal pick with a time less than a time of an initial first break for that seismic trace and at least one proximal pick with a time greater than the time of the provisional first break for that seismic trace.

6. The method of claim 1, further comprising: determining, using the computer processor, a seismic velocity model based, at least in part, on the set of first breaks of the seismic dataset; and determining, using the computer processor, a seismic image of a subsurface region of interest based, at least in part, on the seismic velocity model.

7. The method of claim 6, further comprising: planning a wellbore trajectory based, at least in part, on the seismic image; and drilling the wellbore trajectory.

8. A non-transitory computer readable medium storing instructions executable by a computer processor, with instructions comprising functionality for: receiving a seismic dataset generated by a seismic source, wherein the seismic dataset comprises a plurality of seismic traces and an initial first break for each of the plurality of seismic traces; selecting a plurality of proximal picks for each seismic trace, wherein each proximal pick lies within a time window enclosing the initial first break; determining a near-offset pick for a seismic trace with a shortest offset and sequentially selecting, in order of increasing offset, a selected trace and determining the near offset-pick for the selected trace based on proximal picks of the selected trace and the near-offset pick for at least one seismic trace with a shorter offset than the selected trace; determining, a far-offset pick for a seismic trace with a farthest offset and sequentially selecting, in order of decreasing offset, a selected trace and determining a far-offset pick for the selected trace based on the proximal picks of the selected trace and the far-offset pick for at least one seismic trace with a farther offset than the selected trace; determining a set of coincident picks based on the near-offset pick and the far offset pick for each seismic trace; fitting a first break curve to the set of coincident picks; and determining a set of first breaks of the seismic dataset based, at least in part, on the first break curve.

9. The non-transitory computer readable medium of claim 8, wherein selecting a plurality of proximal picks for each seismic trace comprises: forming a positive trace from each of the plurality of seismic traces; determining a centroid time for each of a plurality of lobes of each positive trace; and selecting, for each positive trace, the plurality of proximal picks, wherein each proximal pick comprises one centroid time lying within the time window enclosing a provisional first break.

10. The non-transitory computer readable medium of claim 8, wherein the set of first breaks of the seismic dataset comprises a first break for each seismic trace having a coincident near-offset pick and far-offset pick.

11. The non-transitory computer readable medium of claim 8, wherein the set of coincident picks comprises a coincident pick for each seismic trace for which the far-offset pick and the near-offset pick are identical.

12. The non-transitory computer readable medium of claim 8, wherein the plurality of proximal picks for each seismic trace comprises at least one proximal pick with a time less than a time of an initial first break for that seismic trace and at least one proximal pick with a time greater than the time of a provisional first break for that seismic trace.

13. The non-transitory computer readable medium of claim 8, wherein instructions further comprise functionality for: determining a seismic velocity model based, at least in part, on the set of first breaks of the seismic dataset; and determining a seismic image of a subsurface region of interest based, at least in part, on the seismic velocity model.

14. The non-transitory computer readable medium of claim 8, wherein instructions further comprise functionality for planning a wellbore trajectory based, at least in part, on the seismic image.

15. A system comprising: a seismic acquisition system; and a seismic processor configured to: receive a seismic dataset generated by a seismic source, wherein the seismic dataset comprises a plurality of seismic traces from the seismic acquisition system; determine an initial first break for each of the plurality of seismic traces; select a plurality of proximal picks for each seismic trace, wherein each proximal pick lies within a time window enclosing the initial first break; determine a near-offset pick for a seismic trace with a shortest offset and sequentially selecting, in order of increasing offset, a selected trace and determining the near offset-pick for the selected trace based on proximal picks of the selected trace and the near-offset pick for at least one seismic trace with a shorter offset than the selected trace; determine, a far-offset pick for a seismic trace with a farthest offset and sequentially selecting, in order of decreasing offset, a selected trace and determining a far-offset pick for the selected trace based on the proximal picks of the selected trace and the far-offset pick for at least one seismic trace with a farther offset than the selected trace; determine a set of coincident picks based on the near-offset pick and the far offset pick for each seismic trace; fit a first break curve to the set of coincident picks; and determine the set of first breaks of the seismic dataset based, at least in part, on the first break curve.

16. The system of claim 15, wherein selecting a plurality of proximal picks for each seismic trace comprises: forming a positive trace from each of the plurality of seismic traces; determining a centroid time for each of a plurality of lobes of each positive trace; and selecting for each positive trace, the plurality of proximal picks, wherein each proximal pick comprises one centroid time lying within the time window enclosing a provisional first break.

17. The system of claim 15, wherein the set of first breaks of the seismic dataset comprises a first break for each seismic trace having a coincident near-offset pick and far-offset pick.

18. The system of claim 15, wherein the set of coincident picks comprises a coincident pick for each seismic trace for which the far-offset pick and the near-offset pick are identical.

19. The system of claim 15, wherein the seismic processor is further configured to: determine a seismic velocity model based, at least in part, on the set of first breaks of the seismic dataset; and determine a seismic image of a subsurface region of interest based, at least in part, on the seismic velocity model.

20. The system of claim 15, wherein the seismic processor is further configured to plan a wellbore trajectory based, at least in part, on the seismic image.

Description

BRIEF DESCRIPTION OF DRAWINGS

[0008] Specific embodiments of the disclosed technology will now be described in detail with reference to the accompanying figures. Like elements in the various figures are denoted by like reference numerals for consistency.

[0009] FIG. 1 depicts elements of a seismic survey in accordance with one or more embodiments.

[0010] FIG. 2 shows a seismic dataset and initial first breaks in accordance with one or more embodiments.

[0011] FIG. 3 depicts a seismic trace and a positive trace determined from the seismic trace, in accordance with one or more embodiments.

[0012] FIG. 4A shows a centroid time dataset determined from the seismic dataset, in accordance with one or more embodiments.

[0013] FIG. 4B shows a subset of the positive centroid dataset in accordance with one or more embodiments.

[0014] FIG. 5 shows proximal times, near-offset picks, far-offset picks, and coincident picks, in accordance with one or more embodiments.

[0015] FIG. 6 shows a flowchart of the first break modification in accordance with one or more embodiments.

[0016] FIG. 7 shows a flowchart in accordance with one or more embodiments.

[0017] FIG. 8 shows a seismic dataset and the modified first breaks in accordance with one or more embodiments.

[0018] FIG. 9 shows a drilling system in accordance with one or more embodiments.

[0019] FIG. 10 depicts a system in accordance with one or more embodiments.

DETAILED DESCRIPTION

[0020] In the following detailed description of embodiments of the disclosure, numerous specific details are set forth in order to provide a more thorough understanding of the disclosure. However, it will be apparent to one of ordinary skill in the art that the disclosure may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description.

[0021] Throughout the application, ordinal numbers (e.g., first, second, third, etc.) may be used as an adjective for an element (i.e., any noun in the application). The use of ordinal numbers is not to imply or create any particular ordering of the elements nor to limit any element to being only a single element unless expressly disclosed, such as using the terms “before”, “after”, “single”, and other such terminology. Rather, the use of ordinal numbers is to distinguish between the elements. By way of an example, a first element is distinct from a second element, and the first element may encompass more than one element and succeed (or precede) the second element in an ordering of elements.

[0022] FIG. 1 depicts elements of a seismic survey in accordance with one or more embodiments. In a seismic survey, energy in the form of seismic waves is generated by the seismic source (106) which may be partially reflected (114) when encountering a surface across which an impedance contrast exists, and may be subsequently detected by a seismic receiver (116). Reflected seismic waves are useful for mapping and evaluating subterranean regions of interest (102), including geological discontinuities (112) and possible hydrocarbon accumulations. The energy contained in seismic waves may also be refracted (110), or “bent,” when passing through a subsurface boundary. Seismic waves may also be radiated (108) into subsurface layers.

[0023] FIG. 2 shows a seismic dataset (200) in accordance with one or more embodiments. A seismic dataset (200) is produced by the seismic survey (100). The seismic dataset includes a plurality of seismic traces, each recorded by a single seismic receiver (116). The seismic receivers (116) are located at a range of distances (“offsets”) from the seismic source (106). The range of distances extends from a minimum offset (206) to a maximum offset (208). FIG. 2 displays each seismic trace vertically with recording time increasing along a time axis (202) from a minimum recording time (204) to a maximum recording time (205). The seismic traces are ordered by monotonically increasing offset from the minimum offset at the left of FIG. 2 to the maximum offset at the right of FIG. 2.

[0024] FIG. 2 further shows the set of initial first breaks (202), depicted by a white line, in accordance with one or more embodiments. Each initial first break, t.sub.f, (202) approximates the time at which the seismic wave is first detected by the corresponding seismic receiver (116). However, a person of ordinary skill in the art will readily appreciate that the set of initial first break (202) may contain a plurality of noisy or erroneous values.

[0025] FIG. 3 depicts a seismic trace (300) and a positive trace (306) determined from the seismic trace, in accordance with one or more embodiments. The seismic trace (300) includes a series of samples at various recording times. The recording times are typically sampled at regular time intervals. Each sample of the seismic trace (300) records the amplitude of the vibration caused by seismic waves at the location of the seismic receiver (116) at the time the sample is taken. The amplitudes may have positive values (302) or negative values (304) at different times along the seismic trace (300), shown as positive or negative deviations from zero along the seismic trace (300).

[0026] In accordance with one or more embodiments, the positive trace (306) includes only those portions of the seismic trace (300) with amplitudes greater than zero. Each continuous segment (“lobe”) of the positive trace (306) is shown as a black shaded lobe (308a-308q) on the positive trace (306). From each lobe (308a-308q), a centroid time, t.sub.c, may be computed, as:

[00001]$\begin{array}{cc}{t}_c=t_s+\frac{{\int }_{t_s}^{t_e}\left(t-t_s\right)w\left(t\right)u\left(t\right)\mathrm{dt}}{{\int }_{t_s}^{t_e}w\left(t\right)u\left(t\right)\mathrm{dt}}& \mathrm{Equation}\left(1\right)\end{array}$

where t.sub.s is the start time of the lobe, t.sub.e, is the end time of the lobe, u(t) is the amplitude of the positive trace, and w(t) is a weighting function.

[0027] In accordance with other embodiments, a centroid mask trace, C(t.sub.c.sup.i), may be calculated as:

[00002]$\begin{array}{cc}C\left(t_c^i\right)=\{\begin{array}{cc}1& \mathrm{when}{l}^i\ge l^{\mathrm{avg}}\\ 0& \mathrm{else}\end{array}& \mathrm{Equation}\left(2\right)\end{array}$

where l.sup.i is the length of the i.sup.th lobe, and l.sup.avg is the average length of lobe in the positive trace. The center of each lobe, t.sub.c.sup.i, may be determined as:

t.sub.c.sup.i=t.sub.s.sup.i+(t.sub.e.sup.i−t.sub.s.sup.i)/2  Equation (3)

where t.sub.s.sup.i is the start time of the i.sup.th lobe and t.sub.e.sup.i is the end time of the i.sup.th lobe. The length of the i-th lobe, l.sup.i, may be determined as:

l.sup.i=t.sub.e.sup.i−t.sub.s.sup.i,  Equation (4)

and the average length, l.sup.avg, of all the lobes in a trace as:

l.sup.avg=(Σ.sub.it.sub.e.sup.i−t.sub.s.sup.i)/i.  Equation (5)

[0028] FIG. 3 shows a first break (312) and a plurality of centroid times (316a-1, 314a-f) for the positive trace (306). A subset of the plurality of centroid times may be designated proximal picks (314a-f) and. Each proximal pick, p.sub.2, (314a-f) may lie within a time window (310) that encloses the first break (312). The time window (310) may be disposed symmetrically around the first break (312).

[0029] In accordance with one or more embodiments, The proximal picks, (314a-f) may include a proximal pick, t.sub.1, (314c) that is the centroid time closest to the first break (312) in time that may be computed as:

t.sub.1=argmin(√{square root over ((t.sub.f−C(t).Math.t).sup.2)}), 0≤t≤t.sub.length  Equation (6)

where c is the centroid time, t is time, and t.sub.length is the duration of the trace. Further, the proximal picks (314a-f) may include a proximal pick (314b) that is the centroid time closest in time, but earlier than, t.sub.1. This proximal pick time may be denoted t.sub.2 and may be computed as:

t.sub.2=argmin(√{square root over ((t.sub.1−C(t).Math.t).sup.2)}), 0≤t≤t.sub.1  Equation (7)

Further still, the proximal picks (314a-f) may include a proximal pick (314d) that is the centroid time closest in time, but later than, t.sub.1. This proximal pick time may be denoted t.sub.3 and may be computed as:

t.sub.3=argmin(√{square root over ((t.sub.1−C(t).Math.t).sup.2)}), t.sub.1≤t≤t.sub.length  Equation (8)

Thus, a proximal pick array, denoted p.sub.2, may be computed as:

[00003]$\begin{array}{cc}{p}_2\left(t,x\right)=\{\begin{array}{cc}1& \mathrm{when}t\in \left\{t_1\left(x\right),t_2\left(x\right),t_3\left(x\right)\right\}\\ 0& \mathrm{else}\end{array}& \mathrm{Equation}\left(9\right)\end{array}$

[0030] In accordance worth one or more embodiments the entries in the proximal pick array may be extended to include other centroid times (314a, b and 314e, f) that lie within the time window (310). A local extension algorithm may be used to extend the set of proximal picks. For example, if the value obtained from calculating proximal picks (314a-f) is non-zero, no additional proximal picks are added. However, if the value obtained from calculating proximal picks (314a-f) is zero but a continuous centroid time exists the continuous extension time may be chosen.

[0031] FIG. 4A shows a centroid time dataset (400) determined from the seismic dataset (200), in accordance with one or more embodiments. The centroid times are computed by determining a positive trace for each seismic trace and determining a centroid time for each lobe of the positive trace. The vertical axis (402) of the positive centroid dataset (400) indicates recording time increasing from a minimum recording time (404) to a maximum recording time (406). The horizontal axis (408) indicates the offset of the positive traces, monotonically increasing from the minimum offset to the left to the maximum offset to the right. Each dot in the positive centroid dataset (400) represent one centroid time. FIG. 4A further shows a subset (410) of the positive centroid dataset (400) that is further displayed in FIG. 4B.

[0032] FIG. 4B shows a subset (410) of the positive centroid dataset (400) in accordance with one or more embodiments. FIG. 4B shows centroid times (412) indicated by dark gray dots, and proximal times (414) indicated by light gray dots. Most proximal times (414) are located in a portion (416) running from earlier times at shorter offsets to longer times at farther offsets. However, some proximal times (414) lie outside the portion (416). The outlier proximal times may be determined by outlier values of the initial first breaks (202).

[0033] FIG. 5 shows proximal times (414), near-offset picks (502), far-offset picks (504), and coincident picks (506) in accordance with one or more embodiments. Near-offset picks (502) are determined from proximal times (414) beginning with the proximal times (414) with the shortest offsets and progressing to the longest offsets by iteratively selecting from proximal picks (414) in order of monotonically increasing offset. Far-offset picks (504) are determined from proximal times (414) beginning with the proximal times (414) with the longest offsets and progressing to the shortest offset by iteratively selecting from proximal picks (414) in order of monotonically decreasing offsets.

[0034] The near-offset picks (502) and far-offset picks (504) are each determined such that the picks vary smoothly from one trace to the next. A near-offset may be determined from the proximal picks of a trace based, at least in part, on the value of near-offset picks (502) already determined for adjacent traces. For example, near-offset picks (502) and far-offset picks (504) may be determined based on the following algorithm:

TABLE-US-00001 Input:p(x, t) = 1 for sample with t = a proximal pick time; otherwise zero dt = time sampling rate of seismic data off(x) = offset information Output: l(x) = near-offset pick for each trace  1: x.sub.0 ← the spatial index of starting point  2: t.sub.0 ← the time index of starting point  3: n ← the number of traces  4: nt ← the number of time samplings  5: for x = 0 to x = n do  6:  for t = 0 to t= nt do  7:   if p(x, t) ≠ 0 then  8:    for l = 0 to l = 20 do  9:     v.sub.0 = off(x.sub.0)/(t.sub.0 .Math. dt) 10:     v = off(x)/(t .Math. dt) 11:     b.sub.x = |off(x) − off(x.sub.0)|/|(v + v.sub.0)/3. | 12:     b.sub.t = dt 13:     dist(l, t) = [{(x − l) − x.sub.0} .Math. b.sub.x].sup.2 + [{(t − t.sub.0)} .Math. b.sub.t].sup.2 14:    end for 15:   end if 16:  end for 17:  (l′ ,t′ ) = arg min dist(l, t) 18:  x.sub.0 ← x − l′ 19:  t.sub.0 ← t′ 20:  l(x) ← t.sub.0 21:  end for
Near-offset picks (502) may be determined iteratively from the nearest-offset trace to the far-offset trace. Far-offset picks (504) may be determined iteratively from the farthest-offset trace to the near-offset trace. It will be readily apparent to a person of ordinary skill in the art how to modify the above algorithm to determine far-offset picks (504) rather than near-offset picks (502).

[0035] Coincident picks (506) may be determined from near-offset picks (502) and far-offset picks (504). Coincident picks (506) are determined to exist where near-offset picks (502) and far-offset picks (504) coincide in time and offset.

[0036] In accordance with one or more embodiments, FIG. 6 shows a flowchart of the first break modification (600). In Step 602, in accordance with one or more embodiments, a seismic dataset (200) is obtained. The seismic dataset (200) includes a plurality of seismic traces and an initial first break (202) for each trace.

[0037] In Step 604, in accordance with one or more embodiments, a positive trace for each of the plurality of seismic traces (300) is determined. In addition, a centroid time (314a-f, 316a-1) for each lobe (308a-q) of the positive trace (306) may be determined.

[0038] In accordance with one or more embodiments, in Step 606, a modified first break for each trace (300) beginning at a greatest active offset may be determined. Step 606 is described in greater detail below.

[0039] In Step 608, in accordance with one or more embodiments, the first of two stopping criteria may be evaluated. If the modified first breaks are all equal to the initial first breaks, then the flow may progress to Step 610. If the modified first breaks are not all equal to the initial first breaks, then the flow may progress to Step 614.

[0040] In Step 610, the second stopping criterion may be evaluated. If the shortest modified offset is the shortest offset (206) in the dataset (500), the workflow may terminate at Step 612. If the shortest modified offset is not the shortest offset (206) in the dataset (500), the workflow may progress to Step 618.

[0041] In Step 618, in accordance with one or more embodiments, a new greatest active offset equal to an offset between the smallest modified offset and the current greatest active offset is set, and each initial first break is set to be equal to each modified first break.

[0042] From Step 610, in accordance with one or more embodiments, if the shortest modified offset is not the minimum offset in the dataset, a new greatest active offset may be set. The new greatest active offset may be set equal to an offset intermediate between the shortest offset and the current greatest active offset. Further in Step 618, the initial first breaks may be updated to be equal to the modified first breaks and the workflow may proceed to Step 606.

[0043] If, in Step 608, the modified first breaks are not all equal to the initial first breaks, then the flow may progress to Step 614. If, in Step 614, all the modified first breaks are earlier than initial first breaks, the workflow may proceed to Step 614. However, if in Step 614, not all the modified first breaks are earlier than initial first breaks, the workflow may proceed to Step 616.

[0044] In Step 616, each initial first break may be set equal to the corresponding modified first break before the workflow proceeds to Step 606.

[0045] FIG. 7 shows a flowchart describing Step 606 of FIG. 6 in greater detail. In Step 702, in accordance with one or more embodiments, a plurality of proximal picks (314a-f) for each positive trace (402) may be selected. Each proximal pick may lie in a time window (310) disposed around the first break (312) for the positive trace (306).

[0046] In Step 704, near-offset picks (502) and far-offset picks (504) are determined, based, at least in part, on the plurality of proximal picks (314a-f) determined in Step 702. Near-offset picks (502) are selected in an iterative manner, beginning with the proximal picks for the positive trace (306) with the smallest offset, and proceeding by selecting near-offset picks for positive traces (306) with monotonically increasing offsets. In contrast, far-offset picks (504) are selected in an iterative manner, beginning with the proximal picks for the positive trace (306) with the largest offset, and proceeding by selecting far-offset picks for positive traces (306) with monotonically decreasing offsets. Each near-offset pick (502) is selected to minimize its separation in space and time from previously selected near-offset picks (502) in the iterative process. Each far-offset pick (504) is selected to minimize its separation in space and time from previously selected far-offset picks (504) in the iterative process.

[0047] In Step 706, in accordance with one or more embodiments, a set of coincident picks (506) are determined from the near-offset picks (502) and far-offset picks (504) is determined. Each coincident pick (506) is determined when the near-offset picks (502) and far-offset picks (504) coincide in time and offset.

[0048] In Step 708, in accordance with one or more embodiments, a curve is fitted to the set of coincident picks (506). The fitting may be performed using a method that is robust to the presence of outliers in the fitted coincident picks (506). The fitting may be performed using a random sampling consensus (“RANSAC”) method. Further, in Step 708, modified first breaks may be determined from the fitted curves for the offset of each positive trace lying between the coincident pick for the smallest offset positive trace and the coincident pick for the largest offset positive trace.

[0049] FIG. 8 shows the seismic dataset (200) and the modified first breaks (802) in accordance with one or more embodiments. The modified first breaks (802) result from the application of the workflows depicted in FIG. 6 and in FIG. 7 to the seismic dataset (200) and the initial first breaks (202). It will be readily apparent to one of ordinary skill in the art, that the set of modified first breaks (802) contain much less noise and erroneous first breaks than the initial first breaks (202).

[0050] FIG. 9 shows a drilling system (900) in accordance with one or more embodiments. The drilling system (900) may include a derrick (902). In some embodiments, the derrick (902) may be located on the land surface (904). In other embodiments, the derrick may be located on a jack-up drill rig (not shown), or a floating drill rig (not shown), on a drill ship (not shown). A drill bit (906) suspended by a drill string (906) from the derrick (902) may drill a wellbore (910a, 910b) through the subsurface. In accordance with one or more embodiments, the wellbore may be vertical (910a), highly deviated or horizontal (910b). The wellbore (910a, 910b) may traverse a plurality of overburden layers (912) and one or more cap-rock layers (914). The wellbore (910a, 910b) may penetrate one or more hydrocarbon reservoirs (916). Furthermore, the wellbore path may be planned and drilled, based at least in part, on a targeted hydrocarbon reservoir based, at least in part, on the modified first breaks (802).

[0051] FIG. 10 shows a system in accordance with one or more embodiments. The system may further include a seismic recording facility (1024) for recording the seismic dataset (200) recorded by the seismic survey (100) and a seismic processor (1020) that may be located in the seismic recording facility (1024) or may be located at a location remote from the seismic survey (100) and connected to the seismic recording facility (1024) by a network (1030). The seismic processor (1002) may be a computer system configured to process a seismic dataset to determine a set of modified first breaks (802) of the seismic dataset (200).

[0052] FIG. 10 further depicts a block diagram of the computer system (1002) used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures as described in this disclosure, according to one or more embodiments. The illustrated computer (1002) is intended to encompass any computing device such as a server, desktop computer, laptop/notebook computer, wireless data port, smart phone, personal data assistant (PDA), tablet computing device, one or more processors within these devices, or any other suitable processing device, including both physical or virtual instances (or both) of the computing device. Additionally, the computer (1002) may include a computer that includes an input device, such as a keypad, keyboard, touch screen, or other device that can accept user information, and an output device that conveys information associated with the operation of the computer (1002), including digital data, visual, or audio information (or a combination of information), or a Graphical User Interface (GUI).

[0053] The computer (1002) can serve in a role as a client, network component, a server, a database or other persistency, or any other component (or a combination of roles) of a computer system for performing the subject matter described in the instant disclosure. The illustrated computer (1002) is communicably coupled with a network (1030). In some implementations, one or more components of the computer (1002) may be configured to operate within environments, including cloud-computing-based, local, global, or other environment (or a combination of environments).

[0054] At a high level, the computer (1002) is an electronic computing device operable to receive, transmit, process, store, or manage data and information associated with the described subject matter. According to some implementations, the computer (1002) may also include or be communicably coupled with an application server, e-mail server, web server, caching server, streaming data server, business intelligence (BI) server, or other server (or a combination of servers).

[0055] The computer (1002) can receive requests over network (1030) from a client application (for example, executing on another computer (1002) and responding to the received requests by processing the said requests in an appropriate software application. In addition, requests may also be sent to the computer (1002) from internal users (for example, from a command console or by other appropriate access method), external or third-parties, other automated applications, as well as any other appropriate entities, individuals, systems, or computers.

[0056] Each of the components of the computer (1002) can communicate using a system bus (1003). In some implementations, any or all of the components of the computer (1002), both hardware or software (or a combination of hardware and software), may interface with each other or the interface (1004) (or a combination of both) over the system bus (1003) using an application programming interface (API) (1012) or a service layer (1013) (or a combination of the API (1012) and service layer (1013). The API (1012) may include specifications for routines, data structures, and object classes. The API (1012) may be either computer-language independent or dependent and refer to a complete interface, a single function, or even a set of APIs. The service layer (1013) provides software services to the computer (1002) or other components (whether or not illustrated) that are communicably coupled to the computer (1002). The functionality of the computer (1002) may be accessible for all service consumers using this service layer. Software services, such as those provided by the service layer (1013), provide reusable, defined business functionalities through a defined interface. For example, the interface may be software written in JAVA, C++, or other suitable language providing data in extensible markup language (XML) format or another suitable format. While illustrated as an integrated component of the computer (1002), alternative implementations may illustrate the API (1012) or the service layer (1013) as stand-alone components in relation to other components of the computer (1002) or other components (whether or not illustrated) that are communicably coupled to the computer (1002). Moreover, any or all parts of the API (1012) or the service layer (1013) may be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of this disclosure.

[0057] The computer (1002) includes an interface (1004). Although illustrated as a single interface (1004) in FIG. 10, two or more interfaces (1004) may be used according to particular needs, desires, or particular implementations of the computer (1002). The interface (1004) is used by the computer (1002) for communicating with other systems in a distributed environment that are connected to the network (1030). Generally, the interface (1004 includes logic encoded in software or hardware (or a combination of software and hardware) and operable to communicate with the network (1030). More specifically, the interface (1004) may include software supporting one or more communication protocols associated with communications such that the network (1030) or interface's hardware is operable to communicate physical signals within and outside of the illustrated computer (1002).

[0058] The computer (1002) includes at least one computer processor (1005). Although illustrated as a single computer processor (1005) in FIG. 10, two or more processors may be used according to particular needs, desires, or particular implementations of the computer (1002). Generally, the computer processor (1005) executes instructions and manipulates data to perform the operations of the computer (1002) and any algorithms, methods, functions, processes, flows, and procedures as described in the instant disclosure.

[0059] The computer (1002) also includes a memory (1006) that holds data for the computer (1002) or other components (or a combination of both) that can be connected to the network (1030). For example, memory (1006) can be a database storing data consistent with this disclosure. Although illustrated as a single memory (1006) in FIG. 10, two or more memories may be used according to particular needs, desires, or particular implementations of the computer (1002) and the described functionality. While memory (1006) is illustrated as an integral component of the computer (1002), in alternative implementations, memory (1006) can be external to the computer (1002).

[0060] The application (1007) is an algorithmic software engine providing functionality according to particular needs, desires, or particular implementations of the computer (1002), particularly with respect to functionality described in this disclosure. For example, application (1007) can serve as one or more components, modules, applications, etc. Further, although illustrated as a single application (1007), the application (1007) may be implemented as multiple applications (1007) on the computer (1002). In addition, although illustrated as integral to the computer (1002), in alternative implementations, the application (1007) can be external to the computer (1002).

[0061] There may be any number of computers (1002) associated with, or external to, a computer system containing computer (1002), wherein each computer (1002) communicates over network (1030). Further, the term “client,” “user,” and other appropriate terminology may be used interchangeably as appropriate without departing from the scope of this disclosure. Moreover, this disclosure contemplates that many users may use one computer (1002), or that one user may use multiple computers (1002).

[0062] Although only a few example embodiments have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the example embodiments without materially departing from this invention. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the following claims. In the claims, any means-plus-function clauses are intended to cover the structures described herein as performing the recited function(s) and equivalents of those structures. Similarly, any step-plus-function clauses in the claims are intended to cover the acts described here as performing the recited function(s) and equivalents of those acts. It is the express intention of the applicant not to invoke 35 U.S.C. § 112(f) for any limitations of any of the claims herein, except for those in which the claim expressly uses the words “means for” or “step for” together with an associated function.