Description:BACKGROUND TECHNICAL FIELD [0001] Embodiments of the subject matter disclosed herein relate to a system and method for using a combination of ocean bottom node data and streamer data for imagining the subsurface of a body of water, and more specifically, to combining sparse ocean bottom nodes and short streamers to reduce acquisition time and cost associated with a seismic survey. DISCUSSION OF THE BACKGROUND [0002] Probing underground formations in search of hydrocarbon resources is an ongoing process driven by continually increasing worldwide demand. Seismic surveys are used for exploration, hydrocarbon reservoir field development, and production monitoring (time lapse). The probed underground formations are made of volumes of rocks with different attributes (permeability, shear and compressional wave velocities, porosity, etc.). The oil and gas is found in pores and fractures ranging from microscopic fissures to kilometer-wide networks creating complex paths for fluid movement. The acquired seismic data is thus processed to generate images of geophysical structures and extract seismic attributes under the ground or the seafloor, i.e., the subsurface, to identify the oil and gas reservoirs. [0003] Seismic surveys are performed on land and in marine environments. Figure 1 illustrates equipment used during a marine seismic survey. A vessel 110 tows plural detectors or receivers (also called “seismic sensors”) 112, which are disposed along a flexible cable 114 (typically several kilometers long). Those skilled in the art use the term “streamer” (labeled 116) for the cable and its corresponding detectors. A vessel usually tows plural streamers at predetermined crossline intervals (crossline being a direction perpendicular to the towing direction), with the streamers forming a spread in the horizontal (XY) plane. A typical streamer is longer than 4,000 m. Streamer 116 is towed at a substantially constant depth z1 relative to the water surface 118. However, streamers may be towed at a slant (i.e., to form a constant angle) with respect to the water surface, or may have a curved profile as described, for example, in U.S. Patent No. 8,593,904, the entire content of which is incorporated herein by reference. Each streamer is normally equipped with compasses, acoustic pingers, steering devices (known as “birds”) and depth sensors that give continuous location information and control over heading, position and depth. [0004] Vessel 110 (or another vessel) may also tow a seismic source 120 configured to generate acoustic waves 122a. Note that, in this document, the terms “acoustic” and “seismic” are interchangeably used to indicate the same type of mechanical energy propagation (i.e., waves). Acoustic waves 122a propagate downward and penetrate the seafloor 124. For simplicity, Figure 1 shows only two paths 122a corresponding to source-emitted acoustic waves. When encountering a layer interface 126 (different impedance in different layers), the acoustic waves are at least partially reflected. The reflection at reflector R is characterized by an incidence/reflection acute angle formed by the incoming or reflected wave and a vertical direction, and an azimuth angle ω (not shown since Figure 1 is a vertical view and ω is in a horizontal plane) between the reflected wave’s projection in the horizontal plane and a reference direction (e.g., x-North). [0005] The reflected acoustic waves 122b and 122c propagate upward. The reflected acoustic wave 122b is received by one of detectors 112, while the reflected wave 122c passes by the detectors and is reflected back at the water surface 118 (the interface between the water and air serving as a quasi-perfect reflector to mirror acoustic waves). Wave 122d, which is wave 122c’s reflection due to the water surface, travels downward and is then also detected. The detectors record amplitude versus time series, known as traces, which are processed to generate a reflectivity image of the underground structure 124 and, in particular, the location of reflectors 126. The traces are recorded as seismic data. [0006] Unlike the marine seismic acquisition system in Figure 1 in which the detectors are moving while housed inside towed streamers, a water-bottom or a land seismic acquisition system as shown in Figure 2 has detectors, known as ocean bottom nodes (OBN) 200 placed over the water-bottom surface 218. One or more sources 220 are towed by a vessel 210 above the OBN 200 and generate sound waves 222, similar to the waves 122A in Figure 1. These waves also propagate into the subsurface 226 and get reflected at various interfaces or reflectors R, and the reflected waves are recorded by the OBN 200. In these different data acquisition geometries, the detectors similarly record traces, and the reflections are characterized by incidence and azimuth angles. [0007] The principle of the acquisition of the seismic data (with streamers or OBN) is to sample the targeted area by traversing programmed adjacent and parallel sail lines 228 over the targeted area as discussed above with regard to Figures 1 and 2. To obtain reliable and good quality seismic images of the surveyed subsurface, the seismic data needs to be acquired continuously over the area. The quality of the distribution of the sources 120/220 and the receivers’ positions during the acquisition is monitored by the analysis of the surface‐derived seismic coverage on the bin grid. The recorded seismic wavefield is subsequently processed in multiple steps (pre-processing, velocity model building and imaging) to create an image of the subsurface. [0008] Ocean bottom datasets (called herein “node datasets”) acquired as illustrated in Figure 2 or using other methodologies, (node on a rope, remote operated vehicle (ROV) based systems, drop-node, cable systems, permanent monitoring, etc.) are well known to create significant improvements in subsurface imaging, when appropriately processed and imaged, due to full azimuth illumination, zero offsets, long offsets, better signal to noise ratio (especially for low frequencies), and the multicomponent nature of the data acquired. These data sets are highly desired due to the superior definition of the subsurface that cannot be achieved even with the use of multi azimuth or wide azimuth towed streamer datasets, especially in complex geological settings. [0009] However, high-density ocean bottom seismic data acquisition has remained a niche, restricted to small isolated areas, due to the exponential costs associated with node density required to adequately sample the subsurface for optimal imaging. In this regard, note that a traditional node dataset is acquired with an inline distance ID between the nodes of about 100 m, and a cross-line distance CD between the nodes not larger than 400 m, as illustrated in Figure 2. The axes X and Y in Figure 2 indicate the inline and the crossline directions, respectively. The inline direction is considered to be the direction parallel to the sail line 228, i.e., the direction followed by the vessel 222 that tows the sources 220, while the cross-line direction is considered to be perpendicular to the inline direction, in a plane substantially parallel to the water surface. [0010] In recent years, sparser Ocean Bottom Seismic (OBS) data (i.e., having a cross-line distance between nodes larger than 400 m) acquisition have gained significant momentum. However, the main goal of these sparse OBS surveys is limited to a better definition of the subsurface velocity field, which leads to a potentially improved towed streamer image. The sparsity of the acquisition limits the potential of the OBS data to create a standalone high-resolution subsurface image due to sampling requirements for optimal imaging. Recent efforts are directed to simultaneously acquiring long offset streamer dataset and OBN data for new seismic surveys. [0011] However, the inventors have observed that the underlying principles of seismic acquisition have not changed significantly, and this can be equated to a separate streamer and a sparse node survey with a zero time lag between both. There are improvements to source utilization (e.g., wide tow, multiple sources) by sharing them between the surveys. For example, US patent publication applications 2019/0064380A1, US2020/0393591A1 and WO2020/197403A1 have a common theme of sharing the seismic source from a typical long offset marine streamer seismic acquisition vessel, while a distribution of nodes is present on the ocean floor, to simultaneously acquire the marine streamer and OBN datasets. [0012] The inventors have noted the following limitations associated with these approaches. The OBN data acquisition is inherently expensive due to the need to place the node stationarily on the sea floor and then recover them, at intervals, to retrieve the data. Both these steps are very slow compared to streamer surveys, which are normally 4-8 times faster to cover the same unit area. To improve cost efficiency, OBN surveys typically densely sample on the source effort as it is relatively inexpensive to do so. The combination used for a particular survey is decided after a comprehensive modelling approach. Even with this approach, receiver spacing in a node survey, especially orthogonal to the source shooting direction (crossline) is typically 3-9 times sparser than the equivalent streamer survey. This bigger crossline separation leads to a crossline offset increment 3-9 times larger than narrow azimuth streamer’s offset increment, depending on the number of sources. Given the fact that nodes are on seafloor, for OBN data both primary energy (up-going energy) and receiver side first order multiple (down-going energy) can be used for imaging purpose. Comparing OBN upgoing energy and streamer data, for the same surface offset, OBN upgoing energy will have bigger reflection angle than streamer data, with actual reflection points closer to receivers, asymptote to mid-point for very deep reflectors. The OBN down-going energy will have smaller reflection angle than upgoing streamer primary data, with reflection points closer to shots, asymptote to mid-point for very deep reflectors. [0013] Sparser node surveys, typically acquired with 600-1200 m crossline receiver line spacing, create significant challenges for it to be used as a standalone sub-surface imaging option, especially in resolving details in the shallow overburden, which can significantly impact overall imaging quality. Main challenges are observed in Common Offset Vector (COV) domain processing related to sampling and signal to noise ratios, challenges in velocity model building due to inadequate sampling for RMO picks and finally imaging challenges related to spatial sampling. Spatial aliasing impacting imaging of steeply dipping structures (e.g., salt bodies) is another challenge. These issues also create significant challenges in extracting attributes from the seismic data (AVO inversion, coherence, dip and spectral decomposition etc.). [0014] Some examples will be used to help illustrate the two challenges from sparse node survey. The 1st challenge: large minimum offset linked to increased crossline receiver line spacing leads to inferior near angle coverage. The 2nd challenge: the offset increment determined by node spacing leads to too sparse reflection angle sampling especially for shallow reflectors and/or steep dips. [0015] Looking at the 1st challenge, the shot lines near the centre of two adjacent node lines will have large minimum offset around half of node line spacing. In case of 900m node receiver line spacing, the minimum offset (measured in XY plane) for those shot lines at the centre of two node receiver lines is ~450m. Even assuming a flat geology and constant velocity, with water bottom (WB) at depth 300m and a shallow reflector at 600m, for up-going energy, the expected reflection angle is ~26o for reflector at 600m; for down-going energy, reflection angle ~26o at WB, and reflection angle ~16o for reflector at 600m. As the minimum offset is determined by the distance between shot and receiver in the XY plane, this problem cannot be mitigated by shot density or OBN inline density. The limited reflection angle range due to receiver spacing puts limits on imaging the overburden complexities and in case of shallow targets, creates critical limitations on the ability of data being used for imaging. This can be routinely noticed in existing sparse node surveys where the sparse OBN data is used to feed the velocity model and does not directly contribute towards imaging the subsurface, especially for shallow targets. [0016] In general, for an OBN survey, node spacing is bigger than shot spacing, and the offset increment in both inline and crossline directions is determined by wave field sampling by the node spacing. Let’s look at the 2nd challenge, to study the reflection angle sampling linked to node spacing. Assuming the node inline spacing is 300m and crossline spacing 900m, this leads to OBN dataset inline offset (offset x) increment 600m and crossline offset (offset y) increment 1800m. For this challenge, a 300m WB depth is considered, and a shallow flat reflector at 600m, with constant velocity. With 600m offset x increment, for up-going energy, the first offset x class (value 0m to 600m) will cover reflection angle 0o to 33o for reflector at 600m if offset y is 0m (shot line right above node line); for down-going energy, the first inline offset class will cover reflection angle 0o to 22o for reflector at 600m if offset y is 0m. Since offset y increment is larger, the reflection angle sampling will be even sparser along crossline direction. It is clear the reflection angle increment for shallow geologies is too big between neighbouring offset classes for curvature picking or seismic attributes extraction. [0017] Under the same flat geology and constant velocity assumption, 300m water depth, node inline spacing 300m, offset y=0, traces with offset x (0m, 600m, 1200m, 1800m), for reflector at 600m, up-going wave reflection angles are (0o, 34o, 53o, 63 o), down-going wave reflection angles are (0o, 22o, 39o, 50o); for reflector at 1200m, up-going wave reflection angles are (0o, 16o, 30o, 41o), down-going wave reflection angles are (0o, 13o, 24o, 34o). It is possible to verify that for the given reflector as offset value increases, the same offset increment will map to smaller reflection angle increment for both up- and down-going waves, and as reflector depth gets larger, the same offset will map to smaller reflection angle as well. In real data, more factors will affect the mapping between surface offset and reflection angle, but the overall trend from above simple example is valid. It is possible for given acquisition geometry to get smaller minimum near angle and denser angle sampling by utilizing surface multiples for both streamer and OBS datasets, but the cross-talk between different order of multiples and ability to produce gathers for AVO/AVA are very complex challenges to handle with the current technologies. [0018] The previously mentioned references require a typical long offset marine seismic streamer vessel together with the node placement on the ocean floor for data acquisition. The subsurface sampling is very dependent on the width and number of sources used, source tow width, streamer spacing, inline streamer receiver spacing, cable length, additional long offset acquired for the nodes (if any), and the sail line spacing between adjacent lines. This would also mean that the resulting dataset is likely to be heavily blended as simultaneous source acquisition would be required for overall cost efficiency, streamer subsurface sampling and minimum streamer vessel speeds to ensure stable tow depth coupled with equipment, material and personnel safety. In any case, the methodology will result in a new towed streamer dataset which is not desirable in most cases, especially in mature basins where large volumes of towed streamer seismic data already exist. The length and width of the towed streamer spread can limit the acquired coverage, especially around existing infrastructure, e.g., oil and gas platforms. The number of towed active sources on a single vessel is inversely proportional to the available source volume per active source and this can further limit the inline sampling with the same source, due to air flow limitations to the source, leading to potentially sub-optimal illumination and subsurface sampling for seismic imaging. The coupling of the streamer and OBN sampling can limit the potential for a variable geometry for the nodes in different areas within the survey area. Sampling variability is a commercially advantageous solution to cater to varying complexity within the total survey area. Typical sail line spacing, that defines native streamer source sampling, is half of the receiver spread width. This is inversely proportional to the source width and number of sources. [0019] Thus, there is a need for a new system and method that is capable of optimizing the subsurface sampling using OBN and streamers by acquiring distinctive and complimentary datasets, which may further be enriched by existing seismic data, previously collected, using towed streamers or OBNs. BRIEF SUMMARY OF THE INVENTION [0020] According to an embodiment, there is a correlated sparse nodes and mini-streamers system for collecting seismic data, and the system includes plural nodes (330) distributed on the ocean bottom, and a mini-streamer spread (320) that includes plural mini-streamers. The plural nodes and the mini-streamer spread are configured to simultaneously collect seismic data from a surveyed subsurface. A length of the mini-streamers is selected to be equal to or less than three times an inline distance between adjacent nodes of the plural nodes. [0021] According to another embodiment, there is a correlated sparse nodes and mini-streamers system for collecting seismic data, and the system includes plural nodes distributed on the ocean bottom, a mini-streamer spread that includes plural mini-streamers, plural sources configured to generate sound waves, and a vessel configured to simultaneously tow the plural sources and the mini-streamer spread above the plural nodes. A length of the mini-streamers is selected to be equal to or less than three times an inline distance between adjacent nodes of the plural nodes. [0022] According to yet another embodiment, there is a method for processing seismic data acquired over a body of water, and the method includes receiving sparse node seismic data acquired with plural seismic nodes distributed over the ocean floor; receiving mini-streamer spread data acquired with plural mini-streamers towed with a vessel above the plural seismic nodes; combining the sparse node seismic data and the mini-streamer spread data; and processing the combined sparse node seismic data and mini-streamer spread data to generate an image of the subsurface. A length of the plural mini-streamers is equal to or less than three times an inline distance between adjacent nodes of the plural nodes. BRIEF DESCRIPTION OF THE DRAWINGS [0023] For a more complete understanding of the present invention, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which: [0024] Figure 1 is a schematic illustration of a seismic data acquisition system that uses streamers; [0025] Figure 2 is a schematic illustration of a seismic data acquisition system that uses ocean bottom nodes; [0026] Figure 3 illustrates a correlated sparse nodes and mini-streamers system for collecting hybrid seismic data; [0027] Figure 4 illustrates a seismic dataset acquired with ocean bottom nodes distributed with a traditional density; [0028] Figure 5 illustrates a seismic dataset acquired with traditional long streamers; [0029] Figure 6 illustrates a seismic dataset acquired with the correlated sparse nodes and mini-streamers system; [0030] Figure 7 illustrates the configuration of the traditional ocean bottom nodes; [0031] Figure 8 illustrates the common medium point position for waves recorded by the mini-streamers and the nodes; [0032] Figure 9 illustrates how the mini-streamers complement the seismic data acquired by an ocean bottom node system for a given reflector; and [0033] Figure 10 is a diagram of various steps for processing the acquired seismic data for generating an image of the surveyed subsurface. DETAILED DESCRIPTION OF THE INVENTION [0034] The following description of the embodiments refers to the accompanying drawings. The same reference numbers in different drawings identify the same or similar elements. The following detailed description does not limit the invention. Instead, the scope of the invention is defined by the appended claims. For simplicity, the following embodiments are discussed with regard to a marine seismic system that survey a subsurface for oil and gas resources. However, the embodiments discussed herein are equally applicable to any subsurface resource, for example, geothermal or hydrothermal exploration and exploitation, carbon capture and storage, ore detection, etc. [0035] Reference throughout the specification to “one embodiment” or “an embodiment” means that a particular feature, structure or characteristic described in connection with an embodiment is included in at least one embodiment of the subject matter disclosed. Thus, the appearance of the phrases “in one embodiment” or “in an embodiment” in various places throughout the specification is not necessarily referring to the same embodiment. Further, the particular features, structures or characteristics may be combined in any suitable manner in one or more embodiments. [0036] According to an embodiment, a novel seismic acquisition data methodology is employed for reducing the cost and time associated with OBN data while also improving the subsurface imaging by utilizing mini-streamers whose inline and crossline receivers’ separation are coordinated with those of the OBNs. In one application, the node dataset and the mini-streamer dataset are simultaneously acquired and used together with a traditional data set (OBN or streamer) for further improving the subsurface imagining. For example, a method for using the above datasets may include defining an optimal receiver and source grid to achieve adequate coverage criteria, utilization of mini-streamers (and/or Near Field Hydrophone (NFH)) towed by the source vessel to improve for near offset coverage, joint processing of the acquired node data, mini-streamer data, and existing towed streamer seismic data utilizing Earth reflectivity as a key criterion. For imaging, the joint pre-stack inversion either through Least Square Migration or full waveform inversion (FWI) imaging can enhance resolution, suppress migration artifacts, and balance subsurface illumination. [0037] According to an embodiment, the system and method that acquire and process the node and mini-streamer datasets take full advantage of (i) the prior knowledge of the subsurface from existing data, proprietary (if allowed) and public information within the geoscience community, (ii) the various source types, blended acquisition methodologies, source diversion and steering technologies available on marine seismic systems, (iii) the real time positioning of the seismic equipment, (iv) the recent improvements in node sensors and associated deployment techniques, and (v) the recent improvements in mini streamer technologies. [0038] The proposed method will bring several benefits to seismic exploration and asset development, especially near-field opportunities, by: (1) improving subsurface imaging and reducing geological and geophysical uncertainties due to better OBN FWI velocity and enhanced imaging from OBN and complementary datasets, (2) reducing environmental footprint by eliminating the need to have multiple surveys for optimal imaging, (3) reducing capital expenditure for exploration, and (4) minimizing acquisition time and associated health, safety and environment (HSE) exposure. [0039] The optimal sampling of the subsurface is needed to achieve a representative seismic image of the subsurface. Sampling required during the data acquisition is very much dependent on the subsurface complexity and hence widely varies. To obtain an optimal subsurface sampling, the main factors evaluated during a marine survey design phase are bin size, structural dips, lateral velocity contrasts, depth and resolution required for target, maximum offset, fold and aperture. These factors are impacting the novel system and method proposed herein, and thus, these factors are now briefly discussed. [0040] Initial maximum acceptable bin size can be estimated by calculating the maximum unaliased frequency required for given maximum dip of events in the subsurface. A bin is typically a given square or rectangular imaginary area on or under the ocean bottom having a size in the tens of meters. Considering diffractions in the datasets, a minimum dip of ~45° is considered for all cases. In general, the maximum bin size, X, can be defined as where V is the velocity of the propagating wave in a given layer, n is the number of cycles, f is the frequency of the recorded wave, and θ is the angular dip of the reflector. The above definitions are only fully applicable to a constant velocity layer. For a more complex overburden, sophisticated approaches involving FWI and migration of the forward modelled data will be required. Stacking within the bin can also attenuate the energy of an event that has a dip across a bin. [0041] The maximum offset for a seismic survey has a large impact on the overall survey cost irrespective of land/marine acquisition. The offset is considered to be the distance, between the source and the first receiver (or another receiver) on the streamer. Thus, the receivers on the streamer that are proximal to the vessel (and implicitly to the source) are considered to be near offsets and the receivers on the streamer that are distal to the vessel are considered to be the far offsets. The required maximum offset is arrived upon by estimating the deepest target depth R, interference with direct waves, normal moveout (NMO) stretch effects and critical offset required at target depth. The angle at which refraction occurs at an interface can be computed based on the velocity variation across the interface and incidence angle. From Snell’s law, , where V1 and V2 are the velocities of the wave above and below the interface, and V1