BR102022009544A2 - OCEAN BOTTOM SCATTERED NODES AND SEISMOGRAPHIC MINICABE ACQUISITION SYSTEM TO INCREASE SUBSURFACE IMAGE - Google Patents

Abstract

The present invention relates to a system of correlated sparse nodes and seismographic minicables (300) for collecting seismic data that includes several nodes (330) distributed on the ocean floor, and the propagation of seismographic minicables (320) that includes several seismographic minicables (322). The multiple nodes (330) and seismographic minicable propagation (320) are configured to simultaneously collect seismic data from the surveyed subsurface, and wherein a length of the seismographic minicables (322) is equal to or less than three times a distance in line between adjacent nodes of different nodes.

Description

OCEAN BOTTOM SCATTERED NODES AND SEISMOGRAPHIC MINICABE ACQUISITION SYSTEM TO INCREASE SUBSURFACE IMAGE Background Field of Technique

[001] Embodiments of the subject described in this document relate to a system and method for using a combination of ocean floor node data and seismographic cable data to image the subsurface of a body of water, and more specifically, to combine sparse ocean floor nodes and short seismograph cables to reduce the acquisition time and cost associated with a seismic survey.

Background Discussion

[002] The probing of underground formations in search of hydrocarbon resources is an ongoing process driven by the continuous increase in world demand. Seismic surveys are used for exploration, development of hydrocarbon reservoir fields and monitoring of production (elapsed time). The underground formations probed are made up of volumes of rocks with different attributes (permeability, shear and compression wave velocities, porosity, etc.). Oil and gas are found in pores and fractures that range from microscopic fissures to networks kilometers wide, creating complex pathways for fluid movement. The acquired seismic data are thus processed to generate images of geophysical structures and extract seismic attributes under the ground or the seabed, that is, the subsoil, to identify oil and gas reservoirs.

[003] Seismic surveys are carried out in land and sea environments. Figure 1 illustrates equipment used during marine seismic surveys. A vessel 110 tows a number of detectors or receivers (also called "seismic sensors") 112, which are arranged along a flexible cable 114 (typically several kilometers in length). Those skilled in the art use the term "seismographic cable" (labeled 116) for the cable and its corresponding detectors. A vessel typically tows multiple seismograph cables at predetermined cross-line intervals (the cross-line is a direction perpendicular to the towing direction), with the seismograph cables forming a spread in the horizontal (XY) plane. A typical seismograph cable is over 4,000 m. The seismograph cable 116 is towed at a substantially constant depth z1 with respect to the surface of the water 118. However, the seismograph cables may be towed at an incline (i.e., to form a constant angle) with respect to the surface of the water, or they may be towed having a curved profile as described, for example, in U.S. Patent No. 8,593,904, the entire contents of which are incorporated herein by reference. Each seismograph cable is typically equipped with compasses, acoustic indicators, heading devices (known as "birds") and depth sensors that provide continuous location information and control over heading, position and depth.

[004] Vessel 110 (or other 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 used interchangeably to indicate the same type of mechanical energy propagation (ie waves). The acoustic waves 122a propagate downwards and penetrate the seafloor 124. For simplicity, Figure 1 shows only two paths 122a corresponding to the acoustic waves emitted by the source. When encountering a layer 126 interface (different impedance in different layers), the acoustic waves are at least partially reflected. Reflection at reflector R is characterized by an acute angle of incidence/reflection formed by the incident or reflected wave and a vertical direction, and an azimuth angle ω (not shown, as Figure 1 is a vertical view and ω is in a plane). horizontal) between the projection of the reflected wave on the horizontal plane and a reference direction (e.g. x-North).

[005] The reflected acoustic waves 122b and 122c propagate upwards. The reflected acoustic wave 122b is received by one of the detectors 112, while the reflected wave 122c passes through the detectors and is reflected back from the surface of the water 118 (the interface between the water and the air serving as an almost perfect reflector for mirroring the waves acoustic). Wave 122d, which is the reflection of wave 122c due to the surface of the water, travels downwards and is also detected. The detectors record amplitude versus time series, known as traces, which are processed to generate an image of the reflectivity of the underground structure 124 and, in particular, the location of reflectors 126. The traces are recorded as seismic data.

[006] Unlike the marine seismic acquisition system in Figure 1 in which the detectors are moving while housed inside towed seismographic cables, a land or water bottom seismic acquisition system as shown in Figure 2 has detectors, known as ocean floor nodes (OBN) 200 placed on the water floor surface 218. One or more sources 220 are towed by a vessel 210 above the OBN 200 and generate sound waves 222, similar to waves 122A in Figure 1. These waves also propagate to the subsurface 226 and are reflected in various interfaces or reflectors R, and the reflected waves are registered by the OBN 200. In these different data acquisition geometries, the detectors register traces in a similar way, and the reflections are characterized by angles of incidence and azimuth.

[007] The principle of seismic data acquisition (with seismographic or OBN cables) is to obtain a sample of the target area by crossing the programmed adjacent and parallel navigation lines 228 over the target area as discussed above in relation to Figures 1 and 2 To obtain good quality and reliable seismic images of the surveyed subsurface, seismic data needs to be acquired continuously over the area. The quality of the distribution of 120/220 sources and receiver positions during acquisition are monitored by analyzing the seismic coverage derived from the surface in the imaginary compartment grid. The recorded seismic wave field is subsequently processed in several steps (pre-processing, velocity model building and imaging) to create a subsurface image.

[008] Ocean floor datasets (hereinafter referred to as "node datasets") acquired as illustrated in Figure 2 or using other methodologies (knot on a rope, remotely operated vehicle (ROV) based systems, drop knot , cable systems, permanent monitoring, etc.) are well known for creating significant improvements in subsurface imaging, when processed and photographed properly, due to full azimuth illumination, zero offsets, long offsets, better signal-to-noise ratio (especially for low frequencies) and the multicomponent nature of the acquired data. These datasets are highly desirable due to the superior subsurface definition that cannot be achieved even using multi-azimuth or wide-azimuth towed seismographic cable datasets, especially in complex geological settings.

[009] However, the acquisition of high-density ocean floor seismic data has remained a niche, restricted to small isolated areas, due to the exponential costs associated with the node density required to adequately sample the subsurface for optimal imaging. In this regard, note that a traditional node dataset is acquired with a line distance ID between nodes of about 100 m and a cross-line distance CD between nodes not greater than 400 m, as illustrated in Figure 2 The X and Y axes in Figure 2 indicate the in-line and cross-line directions, respectively. The line direction is considered the direction parallel to the navigation line 228, that is, the direction followed by the vessel 222 towing the sources 220, while the cross line direction is considered perpendicular to the line direction, in a plane substantially parallel to the water surface.

[010] In recent years, the acquisition of more sparse ocean floor seismic (OBS) data (ie with a cross-line distance between nodes greater than 400 m) has gained significant momentum. However, the primary purpose of these sparse OBS surveys is limited to better definition of the subsurface velocity field, which leads to a potentially improved towed seismographic cable image. Acquisition sparseness limits the potential of OBS data to create a high-resolution standalone subsurface image due to sampling requirements for optimal imaging. Recent efforts are directed towards the simultaneous acquisition of long displacement seismograph cable datasets and OBN data for further seismic surveys.

[011] However, the inventors noted that the underlying principles of seismic acquisition have not changed significantly and this can be equated to a separate seismograph cable and a sparse node survey with zero time lag in between. There are improvements in font utilization (eg wide trailer, multiple fonts) sharing them across searches. For example, US Patent Publication Applications 2019/0064380A1, US 2020/0393591A1 and WO 2020/197403A1 have a common theme of sharing the seismic source of a typical offshore long distance seismic acquisition vessel, while a distribution of nodes is present on the ocean floor, to simultaneously acquire the marine seismographic cable and OBN datasets.

[012] The inventors noted the following limitations associated with these approaches. Acquiring OBN data is inherently uneconomical due to the need to place the stationary node on the seafloor and then retrieve it at intervals to retrieve the data. Both steps are very slow compared to seismograph cable surveys which are typically 4-8 times faster to cover the same unit area. To improve cost efficiency, OBN surveys typically densely sample source effort, as it is relatively cost-effective to do. The combination used for a specific search is decided after a comprehensive modeling approach. Even with this approach, receiver spacing in a node survey, especially orthogonal to the source firing direction (cross-line), is typically 3-9 times sparser than the equivalent seismographic cable survey. This greater crossline separation leads to a crossline offset increment 3-9 times greater than the narrow azimuth seismograph cable offset increment, depending on the number of sources. Given the fact that the nodes are on the seafloor, for OBN data both the primary energy (upward energy) and the first-order multiple of the receiver side (downward energy) can be used for imaging purposes. Comparing the upward energy from the OBN and data from the seismograph cable, for the same surface displacement, the upward energy from the OBN will have a greater angle of reflection than the data from the seismographic cable, with actual reflection points closer to the receivers, asymptote to the midpoint for very deep reflectors. Downward energy from the OBN will have a smaller reflection angle than the primary data from the upstream seismograph cable, with reflection points closer to the shots, asymptote to the midpoint for very deep reflectors.

[013] More sparse node surveys, typically acquired with cross-line receiver line spacing of 600-1200 m, create significant challenges for it to be used as a stand-alone subsurface imaging option, especially in resolving details at overhead shallow, which can significantly affect overall image quality. The main challenges are seen 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 choices, and finally imaging challenges related to sampling space. Spatial aliasing impact imaging of steeply dipped structures (eg salt bodies) is another challenge. These issues also create significant challenges in extracting attributes from seismic data (AVO inversion, coherence, dip and spectral decomposition, etc.).

[014] Some examples will be used to help illustrate the two challenges of sparse node research. The 1st challenge: Large minimum displacement associated with increased line spacing of the cross line receiver leads to poor near angle coverage. The 2nd challenge: the offset increment determined by node spacing leads to very sparse reflection angle sampling, especially for shallow reflectors and/or steep dips.

[015] Looking at the 1st challenge, trigger lines near the center of two adjacent node lines will have a large minimum offset around half the node line spacing. In the case of 900 m node receiver line spacing, the minimum offset (measured in the XY plane) for these trigger lines at the center of two node receiver lines is ~450 m. Even assuming a flat geology and constant velocity, with a water bottom (WB) at 300 m depth and a shallow reflector at 600 m, for upward energy, the expected reflection angle is ~26o for a reflector at 600 m; for downward energy, reflection angle ~26o in WB and reflection angle ~16o for reflector at 600 m. Since the minimum displacement is determined by the distance between the shot and the receiver in the XY plane, this problem cannot be mitigated by the shot density or the OBN in-line density. The limited range of reflection angle due to receiver spacing limits imaging of overhead complexities and, in the case of shallow targets, creates critical limitations in the capacity of the data used for imaging. This can be routinely noticed in existing sparse node surveys where sparse OBN data is used to feed the velocity model and does not directly contribute to subsurface imaging, especially for shallow targets.

[016] In general, for an OBN survey, the node spacing is greater than the trigger spacing, and the offset increment in both the line and cross-line directions is determined by sampling the wave field by the node spacing . Let's see the 2nd challenge, studying the sampling of the angle of reflection linked to the spacing of the nodes. Assuming node line spacing is 300 m and line spacing 900 m, this leads to the OBN dataset line offset increment (x-offset) of 600 m and cross-line offset (y-offset) increment of 1800 m. For this challenge, a WB depth of 300 m is considered, and a shallow flat reflector at 600 m, with constant velocity. With displacement of 600 m x increment, for upward energy, the first class of displacement x (value 0 m at 600 m) will cover reflection angle 0o to 33o for reflector at 600 m if y displacement is 0 m (shooting line just above of the node line); for downward energy, first line displacement class will cover reflection angle from 0° to 22° for reflector at 600 m if y displacement is 0 m. As the y-offset increment is larger, the reflection angle sampling will be even more sparse along the cross-line direction. It is clear that the reflection angle increment for shallow geologies is very large between neighboring compensation classes for curvature extraction or seismic attribute extraction.

[017] Under the same plane geology and assumption of constant velocity, water depth 300 m, node line spacing 300 m, displacement y = 0, traces with displacement x (0 m, 600 m, 1200 m, 1800 m ); for reflector at 1200 m, the reflection angles of the rising wave are (0o , 16o , 30o , 41o ), the reflection angles of the descending wave are (0o , 13o , 24o , 34o ). It is possible to verify that for a given reflector as the displacement value increases, the same displacement increment will be mapped to a smaller reflection angle increment for rising and falling waves, and as the reflector depth is greater , the same offset will be mapped to smaller reflection angles as well. In real data, more factors will affect the mapping between surface displacement and reflection angle, but the general trend of the simple example above is valid. It is possible for a given acquisition geometry to obtain a smaller minimum near angle and denser angle sampling when using surface multiples not only for seismographic cable datasets, but also for OBS, but the crosstalk between different orders of multiples and the ability to produce clusters for AVO/AVA are challenges too complex to deal with today's technologies.

[018] The aforementioned references call for a typical long displacement marine seismographic cable vessel, along with the placement of the node on the ocean floor for data acquisition. Subsurface sampling is very dependent on the width and number of sources used, source trailer width, seismograph cable spacing, in-line seismograph cable receiver spacing, cable length, additional long offset purchased for nodes (if any) ) and navigation line spacing between adjacent lines. It would also mean that the resulting dataset would likely be heavily mixed, as simultaneous acquisition of sources would be required for overall cost efficiency, seismograph cable subsurface sampling, and the minimum seismographic cable vessel speeds to ensure stable tow depth along with equipment, materials and personnel safety. Anyway, the methodology will result in a new set of towed seismographic cable data which is not desirable in most cases, especially in mature basins where large volumes of towed seismographic cable data already exist. The length and width of the towed seismograph cable span can limit the coverage gained, especially around existing infrastructure, eg oil and gas platforms. The number of active sources towed on a single vessel is inversely proportional to the available source volume per active source and this can further limit in-line sampling with the same source due to airflow limitations to the source, leading to a potentially suboptimal lighting and subsurface sampling for seismic imaging. Coupling seismographic cable and OBN sampling can limit the potential for variable geometry for nodes in different areas within the survey area. Sampling variability is a commercially advantageous solution to address varying complexity within the total survey area. The typical navigation line spacing, which defines the source sampling of the native seismographic cable, is half the propagation width of the receiver. This is inversely proportional to the font width and the number of fonts.

[019] Thus, there is a need for a new system and method that is capable of optimizing subsurface sampling using OBN and seismographic cables through the acquisition of distinct and complementary data sets, which can be further enriched by previously existing seismic data. collected using towed seismograph cables or OBNs.

Brief Summary of the Invention

[020] According to one embodiment, there is a system of correlated sparse nodes and seismographic minicables to collect seismic data, and the system includes several nodes 330 distributed on the ocean floor and a seismographic minicable spread 320 that includes several seismographic minicables. The multiple nodes and spread of seismographic mini-cables are configured to simultaneously collect seismic data from a surveyed subsurface. A length of seismograph mini-cables is selected to be equal to or less than three times a line distance between adjacent nodes of the various nodes.

[021] According to another embodiment, there is a system of sparse nodes and correlated seismographic mini-cables to collect seismic data, and the system includes several nodes distributed on the ocean floor, a spread of seismographic mini-cables that includes several seismographic mini-cables, several sources configured to generate sound waves and a vessel configured to simultaneously tow the various sources and the seismographic mini-cable propagated above the various nodes. A length of seismograph mini-cables is selected to be equal to or less than three times a line distance between adjacent nodes of the various nodes.

[022] According to yet another embodiment, there is a method for processing seismic data acquired over a body of water, and the method includes receiving seismic data from sparse nodes acquired with multiple seismic nodes distributed over the ocean floor; receive seismographic minicable propagation data acquired with several seismographic minicables towed with a vessel above the various seismic nodes; combine the seismic data from sparse nodes and the seismographic mini-cable dispersion data; and processing the combined sparse node seismic data and seismographic mini-cable scattering data to generate a subsurface image. A length of the various seismographic mini-cables is equal to or less than three times a line distance between adjacent nodes of the various nodes.

Brief Description of the Drawings

[023] For a more complete understanding of the present invention, reference is now made to the following descriptions taken in conjunction with the attached drawings, in which:

[024] Figure 1 is a schematic illustration of a seismic data acquisition system that uses seismographic cables;

[025] Figure 2 is a schematic illustration of a seismic data acquisition system that uses ocean floor nodes;

[026] Figure 3 illustrates a system of correlated sparse nodes and seismographic mini-cables to collect hybrid seismic data;

[027] Figure 4 illustrates a set of seismic data acquired with ocean floor nodes distributed with a traditional density;

[028] Figure 5 illustrates a set of seismic data acquired with traditional long seismographic cables;

[029] Figure 6 illustrates a set of seismic data acquired with correlated sparse nodes and seismographic minicables system;

[030] Figure 7 illustrates the configuration of traditional ocean floor nodes;

[031] Figure 8 illustrates the position of the common midpoint for waves recorded by the seismographic minicables and the nodes;

[032] Figure 9 illustrates how the seismographic mini-cables complement the seismic data acquired by a system of ocean floor nodes for a given reflector; It is

[033] Figure 10 is a diagram of several steps to process the acquired seismic data to generate an image of the surveyed subsurface.

Detailed Description of the Invention

[034] The following description of the modalities refers to the attached drawings. The same reference numerals in different drawings identify the same or similar elements. The following detailed description does not limit the present invention. Rather, the scope of the present invention is defined by the appended claims. For simplicity, the following modalities are discussed in relation to a marine seismic system that searches a subsurface for oil and gas resources. However, the embodiments discussed in this document are equally applicable to any subsurface resource, e.g. geothermal or hydrothermal survey and exploration, carbon capture and storage, ore detection, etc.

[035] Reference throughout the descriptive report to "an embodiment" or "the embodiment" means that a particular feature, structure or characteristic described in connection with an embodiment is included in at least one embodiment of the disclosed object. Thus, the appearance of the phrases "in a modality" or "in the modality" in various places throughout the specification does not necessarily refer to the same modality. Furthermore, the particular features, structures or features may be combined in any suitable manner in one or more embodiments.

[036] According to one embodiment, a new methodology of seismic acquisition data is employed to reduce the cost and time associated with OBN data, while improving the subsurface image using mini seismographic cables whose separation of receivers in line and cross line is coordinated with those of the OBNs. In one application, the node dataset and mini-cable seismographic dataset are acquired simultaneously and used in conjunction with a traditional dataset (OBN or seismographic cable) to further enhance subsurface imaging. For example, one method of using the above datasets could include defining an ideal receiver and source grid to achieve suitable coverage criteria, utilizing seismograph mini-cables (and/or near-field hydrophone (NFH)) towed by the vessel to improve displacement coverage, joint processing of acquired node data, seismograph mini-cable data, and seismic data from existing towed seismograph cables using Earth reflectivity as a key criterion. For imaging, joint pre-stacked inversion, either via least squares migration or full waveform inversion (FWI) imaging, can improve resolution, suppress migration artifacts, and balance subsurface illumination

[037] According to one embodiment, the system and method that acquires and processes seismographic node and mini-cable data sets take full advantage of (i) prior knowledge of the subsurface from existing data, proprietary information (if permitted) and within the geoscience community, (ii) the various source types, blended acquisition methodologies, source diversion and source targeting technologies available in marine seismic systems, (iii) the real-time positioning of seismic equipment, (iv) the recent improvements in node sensors and associated deployment techniques, and (v) recent improvements in seismograph minicable technologies

[038] The proposed method will bring several benefits to seismic exploration and asset development, especially near-field opportunities, by: (1) improving subsurface images and reducing geological and geophysical uncertainties due to better OBN FWI speed and improved images OBN and complementary datasets, (2) reduce environmental footprint by eliminating the need for multiple searches for optimal images, (3) reduce capital expenditures for exploration, and (4) minimize acquisition time and associated health exposure , safety and environment (HSE).

[039] Optimal subsurface sampling is required to obtain a representative seismic image of the subsurface. The sampling required during data acquisition is highly dependent on the complexity of the subsurface and therefore varies greatly. For optimal subsurface sampling, the key factors evaluated during a marine survey design phase are compartment size, structural dips, lateral velocity contrasts, target depth and required resolution, maximum displacement, bending, and aperture. These factors are impacting the new system and method proposed here and therefore these factors are now briefly discussed.

onde V é a velocidade da onda de propagação em uma determinada camada, n é o número de ciclos, f é a frequência da onda registrada e θ é a inclinação angular do refletor. As definições acima são apenas totalmente aplicáveis a uma camada de velocidade constante. Para uma sobrecarga mais complexa, serão necessárias abordagens sofisticadas envolvendo FWI e migração dos dados modelados para frente. O empilhamento dentro do compartimento também pode atenuar a energia de um evento que tenha uma queda em um compartimento imaginário.[040] The maximum acceptable initial size of the imaginary compartment can be estimated by calculating the maximum unallied frequency required for a given maximum dive of subsurface events. An imaginary compartment is typically a certain imaginary square or rectangular area on or under the ocean floor with a size of tens of meters. Considering the diffractions in the datasets, a minimum dip of ~45° is considered for all cases. In general, the maximum size of the imaginary compartment, X, can be defined as

where V is the velocity of the wave propagating in a given layer, n is the number of cycles, f is the frequency of the recorded wave and θ is the angular inclination of the reflector. The above definitions are only fully applicable to a constant velocity layer. More complex overhead will require sophisticated approaches involving FWI and migration of the modeled data forward. Stacking within the compartment can also attenuate the energy of an event that has a fall into an imaginary compartment.

[041] The maximum displacement for a seismic survey has a large impact on the overall cost of the survey, regardless of land/sea acquisition. The displacement is considered the distance between the source and the first receiver (or another receiver) in the seismograph cable. Thus, receivers on the seismograph cable that are proximal to the vessel (and implicitly the source) are considered near displacements and receivers on the seismograph cable that are distal to the vessel are considered distant displacements. The maximum required displacement is obtained by estimating the target's deepest depth R, interference with direct waves, normal motion stretching (NMO) effects, and critical displacement required at target depth. The angle at which refraction occurs at an interface can be calculated based on the velocity change across the interface and the angle of incidence. From Snell's law, sin( ) = 1/ 2 , where V1 and V2 are the wave speeds above and below the interface, and V1 < V2.

[042] In this context, it is also desirable to consider the critical distance, i.e. the distance at which the refracted wave is first observed according to ray theory, and the overtaking distance after which refracted arrivals will be more earlier than direct arrivals. Considering plane layers of constant velocity and assumption of radii, the critical distance is given by ∆ = 2ℎ , where θ is the critical angle and h is the depth to the interface. Under the same assumptions, it is also possible to calculate the overtaking distance, that is, the distance at which the refracted arrival exceeds the direct arrival, as being

[043] Although a larger minimum near displacement is economically attractive, it may affect the ability to image shallow geology. Therefore, the critical distance is an important parameter to be evaluated during the research design phase. To ensure good imaging of shallow geology layers with strong velocity contrast, it is preferable to have good close displacement coverage within the critical distance. At the same time, it may be preferable to have a displacement greater than the overtaking distance: "clean" section of refractive energy without strong interference from other waves (direct arrival, guided waves, etc.) inversion, refractive tomography and so on against.

[044] The imaginary compartment size and maximum displacement normally define the geometry and bending for marine seismic surveys. In this regard, there are well-defined criteria (see, for example, Krey, Th C., 1987, Attenuation of random noise by 2D and 3D CDP stacking and Kirchhoff migration: Geophysical Prospecting, 35, no. 2, 135-147, https ://doi.org/10.1111/j.1365-2478.1987.tb00809.x.) for accurate estimation of fold and opening, and therefore these two parameters are not discussed here.

[045] Another design consideration for seismic surveys lately is design "friendliness" for FWI processing. FWI can dramatically change the understanding of the subsurface by reconstructing a velocity field model that accurately explains the recorded seismic data. With high-frequency FWI, it was recently demonstrated [1] that detailed models of subsurface properties generated with FWI provided an accurate description of the overhead complexity and helped to mitigate image distortions. The resulting image elevation allowed a better structural definition, stratigraphic characterization of the reservoir and quantitative interpretation.

[046] Recent reviews of OBN datasets and research published by Huang et al., (see, for example, https://doi.org/10.1190/tle40050324.1) indicate that with FWI frequencies equivalent to the width of bandwidth required for imaging, the reflectivity image emitted directly from the FWI often provides additional structural information with better illumination and higher signal-to-noise ratio naturally as a result of many iterations of least-squares fitting of the full-wavefield data. Note that seismic acquisition is typically done at a 2 ms sampling rate, which results in the Nyquist limit at 250 Hz. However, due to attenuation, the frequency at the desired targets is often much lower. This expected frequency at depth for a target is considered for the modeling exercise to optimize sampling parameters.

[047] To derive an optimized sampling grid for acquisition, the above mentioned variables are first estimated after interrogating the existing data for a given area. Subsequently, these parameters are validated through 3D full waveform modeling followed by FWI and migration, during which attributes such as illumination patterns (diving wave, reflection, and so on) and trace amplitudes are also evaluated.

[048] According to one embodiment, the subsurface sampling obtained using OBN receivers is optimized through the acquisition of distinct, complementary, sparse and seismographic mini-cable data sets, which can be further enriched using existing seismic data for the area target, being towed seismographic cable or OBN. The terms "stray nodes" and "seismograph mini-cables" are understood in the following embodiments to refer to nodes that are separated, along the cross-line direction, by more than 600 m, and to seismograph cables with lengths of less than 3,000 m , respectively. Note that typical nodes are distributed along the cross-line direction with distances between 300 m and 400 m, while seismograph cables have lengths greater than 3000 m. Thus, sparse nodes and seismographic mini-cables are different from typical seismographic nodes and cables in the art. This means that the acquired data corresponding to these settings is different from the typical node and seismographic cable data. Also note that the sensor distribution along a given seismograph cable is typically about 40 feet (12.5 m) or less. However, signals (traces) from multiple sensors (a group of sensors) can be combined to form a single trace. In other words, each trace used for analysis can be registered by a single sensor or by a group of sensors. If the trace is the result of recordings from a group of sensors, then the spacing of the trace is given by the distance between such groups, not the individual sensors.

[049] In one embodiment, not only are sparse nodes and short seismograph cables used instead of typical seismograph nodes and cables, but also their in-line and cross-line characteristics are coordinated, to obtain "correlated sparse nodes and seismographic mini-cables ," that is, a configuration in which the cross-line distance covered by the seismograph mini-cables between adjacent lines of sparse nodes is mathematically related to the cross-line distance of the sparse nodes, and the line length of the seismograph mini-cable is mathematically a function of the separation in line of sparse nodes. In this regard, in one embodiment, if the in-line distance between the sparse nodes is between 100 m and 300 m, the length of the seismograph mini-cables can be between 200 m and 600 m, respectively, i.e. twice the in-line distance of the nodes . In one application, it is possible for the length of seismograph mini-cables to be up to three times the in-line distance of adjacent nodes. Furthermore, if the cross-line distance between the sparse nodes is 900 m, the seismograph mini-cable spread will have a width of about 1200 m (for example, 12 seismograph cables, each pair of adjacent cables separated by 100 m) of so that after 6 passes of the ship towing the source and the seismograph cable spread, the seismograph cable spread completely covered the cross-line distance between two adjacent nodes to provide close angle coverage with relatively dense angle sampling along the direction of the cross line for shallow geology events. For the above discussion, the triple source configuration with 50 m cross-line source separation (100 m outside to outside, 150 m crossline spacing) is assumed.

[050] In other words, the system of sparse nodes and correlated seismographic minicables is characterized by a length L of the seismographic minicables being N times the line distance l of the nodes (capital letters are used for seismographic cables and lowercase letters are used for o us), where N is 2, 3 or more. In one application, ≤ 3 , that is, the length L of the seismograph mini-cables is equal to or less than three times the distance l between two adjacent nodes along the in-line direction. In one embodiment, the ratio ≤ 3 , is further limited by a hard limit on the length of the seismograph mini-cable, ie ≤ 3 . In this or any other modality, there is a relationship between the number of channels (or traces) N that the seismographic mini-cable has and the line distance l between consecutive nodes. If the seismographic cable has N channels, each pair of adjacent channels is separated by a distance M, where one channel corresponds to a single sensor or a group of sensors that are processed together, then the number of N channels needed to acquire the data seismic data obeys the ratio ≤ 3 / . For example, if M is 12.5 m and l is 300 m, then the number of channels N needed is 3 x 300/12.5 = 72. This corresponds to L = 72 x 12.5 = 900 m. Distance M can also be 3.125, 6.25, 25 m, etc. or even less than 3.125 for Ultra High Resolution Cables. For M = 3.125 and l = 300, the number of channels N is 288 and L is 900 m or less. In addition, correlated sparse nodes and seismographic mini-cables can also be characterized by seismographic cable propagation having a width W (along the cross-line direction) substantially equal to or greater than a distance w between two adjacent lines of nodes (along the cross line direction). The seismograph cable propagation travels the distance between adjacent lines 332 of nodes M times. For a node line spacing of 600m and a trigger spacing of 50m with triple source configuration, the navigation line spacing of 150m leads to M = 4

[051] For example, as shown in Figure 3, a seismographic mini-cable system and correlated sparse nodes 300 includes a vessel 302 that simultaneously tows several sources 310 (three in this case) and several seismographic mini-cables 322 that form the propagation of the seismographic cable 320 A seismograph cable spread width 320 is W, a seismograph cable length is L, a line distance between adjacent nodes 330 is l, and a cross line distance between adjacent nodes 330 is w. The nodes are distributed along parallel straight lines 332. The nodes 330 can be fixed to the ocean floor or can float in the water (for example, they can be located in corresponding autonomous underwater vehicles). The vessel follows navigation lines 304-I (only navigation lines I = 1 to 4 are marked in the figure). It is observed that some of the navigation lines (eg, 304-1 and 304-4) coincide in the cross-line direction with the node lines 332. It is also observed that after navigating along four consecutive navigation lines 304-I , vessel 302 again sails above a node line. For this specific modality, the line spacing of node l can be 300 m, the length L of the seismograph cable can be 600 m, that is, twice the distance l, the distance D between adjacent navigation lines is 225 m there are 12 seismographic cables, the width W of the seismographic cable propagation is 1200 m, and the distance w between adjacent nodes is 900 m, that is, the width of the seismographic cable propagation W can be greater than the distance w between adjacent nodes. Those skilled in the art would understand that this is just an example and other values for all these lengths and widths can be used depending on the type of subsurface, the depth of the target, the frequency used, etc. For example, if both close angle sampling and dense angle sampling for a wider angle range is important to de-risk exploration and production activity for relatively shallow prospects, the seismograph cable length L can be more than double of l-node line spacing to provide the necessary lighting. In the example with 300 m WB, shooting grid 50 m x 50 m, the seismograph cable will have an x-displacement increment of 100 m, and for a shallow reflector at 600 m, the 600 m cable can cover an angle of up to 27o , with sampling of angle ~ 4.5o . For the reflector at 1200m depth, a 600m cable will cover an angle of up to 14o, and a 1000m cable will cover an angle of up to 23o.

[052] In simple geology with sufficient lighting, generally migrated gather curvature and attributes such as AVO/AVA can be reliably extracted from the in-line direction. There are cases where cross-line reflection angle coverage and sampling rate are important due to factors such as strong azimuthal anisotropy, complex lighting pattern due to overhead, etc. In a sparse node survey, spacing between w-node cross lines between 600 m to 1000 m leads to an x-offset increment from 1200 m to 2000 m, so sampling the angle of reflection by the OBN data will be very sparse. In Figure 3, the distance w between adjacent nodes is 1100 m, and the propagation width W of the seismograph cable is 1200 m, so the mini seismograph cable can provide the near reflection angle coverage and sampling density along of the cross line direction not possible by OBN. With cable spacing of 100m, the y offset increment will be 200m if the trigger grid is less than 100m, the seismograph cable data can provide 4 offsets (0m, 200m, 400m, 600m) coverage that may be important for shallow geologies.

[053] While the modality illustrated in Figure 3 has the length of the seismographic mini-cables twice the spacing of the node in line, in another modality it is possible to have the length of the seismographic mini-cables twice the distance from the node of the crossed line, assuming that the distance cross-line spacing is greater than line spacing, and the seismograph mini-cable spread can be as wide as desired, as long as acquisition efficiency is not affected

[054] The most significant challenge with OBN datasets, and compounded by the sparse cross-line receiver spacing, is VOC coverage. The configuration shown in Figure 3 overcomes this problem by utilizing the propagation 320 of seismograph mini-cables, towed behind the source vessel 302 used for OBN acquisition, to improve close displacement sampling. Variations from the sizes shown in Figure 3 are possible and acceptable depending on individual scenarios.

[055] In one application, a traditional OBN system uses a receiver spacing of 100 and 300 meters for in-line and cross-line, respectively. The modeled parameters were verified using an existing OBN dataset in the area. For a deepwater configuration, the inventors arrived at a node spacing of 400 m x 400 m using the same methodology, without any optimization discussed in this document. In both scenarios, S-wave sampling was also considered in conjunction with P-wave sampling. In this regard, Figure 4 shows a baseline survey of a given area performed exclusively with standard configuration OBNs, which is illustrated in Figure 7 (note that the density of nodes 330 in Figure 7 is twice as high as the density of nodes in Figure 3), while Figure 5 shows a survey of the same area performed exclusively with 8,000 m long towed seismographic cables . When the same area is surveyed with the setup shown in Figure 3, it is expected that the seismic data shown in Figure 6 will be acquired. The arrows in these figures point to the same subsurface features, which shows that the dataset in Figure 6 captures these features at the same, if not better, resolution. it is observed that the data set shown in Figure 4 was acquired with very dense nodes (100 m x 300 m), the data set shown in Figure 5 was acquired with long seismograph cables (8,000 m), while the data set shown in Figure 6 is simulated for less dense nodes (100 m x 900 m) and much shorter seismographic cables (about 200 m). Even if the quality of the data set obtained in Figure 6 is not better than those shown in Figures 4 and 5, the cost and time to define such a search are much better due to the reduced density of the nodes and the short length of the cables. seismographics.

[056] Optimized grid derivation of OBNs is based on target illumination analysis and subsequent calculation of surface grid and OBN patch area requirement for optimal illumination. The required acquisition grid can then be modeled and compared with the lighting analysis for validity. Previously acquired towed seismographic cable data can also be used for modeling purposes. For clarity, the optimized node design shown in Figure 3 does not need to follow a regular grid practice. Variable in-line and cross-line spacing within a survey is possible, again depending on geology-driven lighting challenges.

[057] Figure 8 shows the combination of seismographic and OBN minicable data for a CMP 800 position. For a single shallow layer, the displacements contributed by the seismographic minicable are indicated by lines 810 and those contributed by the OBN are indicated by lines 820 and 822. The overlay coverage has not been added as a map, which will be the case when considering multilayer geology.

[058] There are several types of mini seismograph cables available in the industry and they are significantly different from a typical long offshore towed seismographic cable. While both can contain a pressure sensor and a particle sensor, the individual sensors are spaced farther apart (with in-line spacing ranging from sub 1 meter to 3.125 meters primarily) on the mini seismograph cables to achieve smaller imaginary compartment sizes and are also towed shallower (2 -10 m from sea surface) to improve bandwidth at higher frequencies. Therefore, this dataset can also be used to generate independent high-resolution images of the near surface, further reducing the environmental footprint of seismic surveys.

[059] The number of sources 310 used for the search is proposed as flexible and determined based on modeling for individual scenarios. Registered near-field (NFH) hydrophones can also complement the seismograph mini-cable dataset, as they are effectively zero-displacement seismic. NFH datasets are typically single-channel and therefore processed separately in practice.

[060] In another embodiment, the inventors propose to use the existing towed seismographic cable and/or OBN data (ie previously acquired seismic data) to improve the sampling gaps left between the mini seismographic cable and the OBN receivers. This creates yet another significant challenge for seismic imaging, as the two datasets (seismograph minicable/towed seismic vs. OBN) are not localized and therefore the recorded wavefronts are at different stages of propagation. As illustrated in Figure 9, seismograph mini-cable receivers 324 are located on the water surface 900 while nodes 330 are located on the ocean floor 910. Figure 9 also shows the reflector of interest R, below the ocean floor 910. This challenge is proposed in this embodiment to be negated by using reflectivity-based imaging techniques.

[061] More specifically, as illustrated in Figure 9, these two non-colocalized datasets sample the same subsurface reflectivity R. For a shallow water environment, between neighboring nodes 330, the seismograph mini-cable 322 can provide close-angle coverage (dotted lines 912) for shallow reflectors that cannot be illuminated by upward (solid lines 914) or downward (dashed lines 916) OBN waves. Using this common reflectivity as a constraint, an inversion-based solution is proposed to merge the sparse node and seismographic minicable datasets. Additional near angle illumination 912 provided by seismograph mini-cable propagation 320 can improve shallow section resolution and accelerate inversion convergence. There are several ways to achieve this goal. Two examples would be least squares migration techniques where the velocity is fixed (if there is high confidence in the velocity), and FWI imaging techniques that extract subsurface reflectivity from the FWI model.

[062] In all cases, it should be noted that this new setup and method does not require a simultaneously acquired towed long displacement seismograph cable dataset and OBN dataset to create a meaningful subsurface image for the area being explored. This significantly reduces the environmental footprint of research, creates a commercially advantageous and more flexible design envelope for OBN sourcing and sampling. This methodology lends itself to variable node sampling to effectively address the variability of geological complexity within the exploration area, keeping costs under control.

[063] The methodology discussed above can be summarized in relation to Figure 10 as now discussed. In step 1000, from existing seismographic cable data, a pre-stack depth migration (PSDM) can be performed and this data is used to design an OBN survey. Then, in step 1002, determination of the OBN acquisition parameter is performed based on synthetic forward modeling and FWI and migration. In step 1004, the sparse OBN and seismograph mini-cable configuration shown in Figure 3 is used to acquire new seismic data. In step 1006, the new seismic data is pre-processed by OBN with existing seismograph cable, NFH and mini seismograph cable. In step 1008, data from existing seismograph cables is reprocessed with NFH and mini seismograph cable from the OBN survey, and the datasets obtained in steps 1006 and 1008 are combined in step 1010. In step 1012, the velocity model is updated based on in the OBN and seismograph cable data, and in step 1014, the datasets from the OBN sparse least squares migrations, mini seismograph cable, and existing seismograph cable are merged to generate a final subsurface image. At step 1016, it is possible to generate a subsurface image based only on the sparse OBN and seismographic minicable datasets using FWI imagination.

[064] Some of the possible technical and/or commercial advantages of the proposed sparse correlated nodes and seismographic mini-cable configuration are now discussed. The proposed combination can substantially reduce the cost compared to current techniques for acquiring ocean floor data, while still providing a high-quality, scalable image of the subsurface. Current sparse OBS acquisition methodologies result in an inadequately sampled subsurface, especially close to the surface, which further limits detailed imaging of geological targets and overburden. The proposed new methodology can also provide, when used in combination with proprietary full-wavefield imaging methodologies, highly detailed shallow subsurface imaging that further reduces the need for alternative datasets to mitigate drilling risks (shallow risk cube ), well placement and subsurface planning. Although the authors do not claim that the optimized image obtained using the methodology described here will be equal to or better than the non-optimized denser OBN grid, i.e., the image results of the described optimized solution are very close to the denser OBN grid. unoptimized, in certain embodiments it is possible that a superior image of the subsurface is obtained with the method illustrated in Figure 10.

[065] The disclosed embodiments provide correlated sparse nodes and data acquisition system of seismographic minicables to obtain an image of a subsurface faster and cheaper than the more traditional OBN or OBN configurations of seismographic cables. It is to be understood that this description is not intended to limit the present invention. Rather, the embodiments are intended to cover alternatives, modifications and equivalents, which are included in the spirit and scope of the present invention as defined by the appended claims. Furthermore, in the detailed description of embodiments, several specific details are presented to provide a comprehensive understanding of the claimed invention. However, one skilled in the art would understand that various modalities can be practiced without these specific details.

[066] Although the features and elements of the present embodiments are described in the embodiments in particular combinations, each feature or element can be used alone without the other features and elements of the embodiments or in various combinations with or without other features and elements described in this document.

[067] This written description uses examples of the disclosed subject matter to enable anyone skilled in the art to practice the same, including making and using any devices or systems and executing any incorporated methods. The patentable scope of the matter is defined by the claims, which may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims.

References

[068] The entire content of all publications listed herein is incorporated by reference in this patent application. [1] P Routh et al., 2017, Impact of high-resolution FWI in the Western Black Sea: Revealing overburden and reservoir complexity, The Leading Edge 36: 60-66, http://dx.doi.org/10.1190/ tle36010060.1.

Claims (10)

System of correlated sparse nodes and seismographic mini-cables (300) for collecting seismic data, the system (300) characterized by the fact that it comprises: several nodes (330) distributed on the ocean floor; and a seismograph mini-cable spread (320) including multiple seismograph mini-cables (322), wherein the multiple nodes (330) and the seismograph mini-cable spread (320) are configured to simultaneously collect seismic data from a surveyed subsurface, and wherein a length of the seismograph mini-cables (322) is equal to or less than three times a line distance between adjacent nodes of the plurality of nodes. System, according to claim 1, characterized in that the various nodes are distributed in a grid along the in-line and cross-line directions, which are perpendicular to each other, while the various seismographic mini-cables are towed by a vessel along sailing lines, which are parallel to the line heading of the nodes. System, according to claim 1, characterized by the fact that the length of the seismographic mini-cables is less than 3 km. System, according to claim 1, characterized in that a cross-line distance between adjacent nodes of the various lines is at least 600 m and the line distance is at least 100 m. System, according to claim 1, characterized in that it additionally comprises: seismic sources towed simultaneously with the propagation of a seismographic mini-cable by the same vessel. System, according to claim 1, characterized in that a seismographic mini-cable propagation width is substantially equal to a cross-line distance between adjacent lines of the various nodes. System, according to claim 1, characterized by the fact that a cross-line distance between adjacent nodes is 900 m. System of correlated sparse nodes and seismographic mini-cables (300) for collecting seismic data, characterized in that it comprises: several nodes (330) distributed on the ocean floor; the propagation of seismographic mini-cables (320) which includes several seismographic mini-cables (322); a plurality of sources (310) configured to generate sound waves; and a vessel (302) configured to simultaneously tow the various sources (310) and propagating seismographic minicables (320) above the various nodes (330), wherein a length of the seismographic minicables (322) is equal to or less than three times a line distance between adjacent nodes of several nodes. System, according to claim 8, characterized by the fact that the various nodes are distributed in a grid along the in-line and cross-line directions, which are perpendicular to each other, while the various seismographic mini-cables are towed by the vessel along navigation lines, which are parallel to the line direction of the nodes. System, according to claim 8, characterized by the fact that the length of the seismographic mini-cables is less than 3 km.

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