Interval Velocity Model Research Articles

Second-order optimization for multiparameter reflection waveform inversion in acoustic VTI media

SUMMARY The seismic wave velocity in subsurface formations typically varies both spatially and directionally, resulting in a heterogeneous and anisotropic medium. To successfully image complex structures and potential reservoirs using multichannel seismic data, high-resolution interval velocity models are required. However, most controlled-source seismic recordings lack wide-angle signals, such as diving and refracted waves that propagate through deep formations. Consequently, geophysicists rely on the traveltimes and waveforms of reflections or back-scatterings in finite-frequency and finite-offset seismograms to estimate velocity and account for possible anisotropy. Recently, wave-equation based reflection waveform inversion (RWI) has emerged as an active research topic due to its ability to recover intermediate-wavelength model components that cannot be retrieved in reflection traveltime tomography. Nevertheless, the widely used gradient-type local optimization suffers from multiparameter trade-off and slow convergence of RWI in anisotropic media. Analysis of the Fréchet derivative reveals that the sensitivity of reflections to changes in long-to-intermediate wavelengths of the anisotropic velocities is jointly controlled by the specular reflection on the interface and the radiation pattern of scattered fields concerning the model parameters along the wave paths. Anatomy of the approximate Hessian reveals characteristics of parameter coupling and spatial resolution in the context of multiparameter RWI, inspiring the development of a matrix-free Gauss–Newton algorithm based on the second-order adjoint-state method for large-scale applications. Synthetic and real data examples demonstrate that the proposed approach can appropriately handle overburden heterogeneities and anisotropies, and thus improve imaging of underlying complex structures such as dipping and small-scale faults in the deep parts.

Evaluation of the Possibilities Validation of Interval Velocity Models Using Non-Seismic Data and Its Impact on Geological Interpretation of PreSDM Results

The paper presents the problem of generation and validation of Velocity Interval Depth (VID) models with the application of non-seismic geophysical and geological data. The study area is a part of the Carpathian Foredeep located close to its contact with the Carpathian Overthrust. In this area of complicated geological structure, hydrocarbon deposits have been successfully explored for decades with seismic methods and drilling. The research applied the Simultaneous Joint Inversion (SJI) of independent geophysical data, which is a modern methodology of geophysical data processing, that is still under development. Such an attempt was necessary due to the lack of a sufficiently dense grid of wells in the study area, in which seismic velocities would be correctly recorded. Such data would be then applied for the generation of relevant VID models, which in turn, could be used to perform the Prestack Depth Migration (PreSDM) procedures. The application of procedures taking advantage of independent geophysical and geological data enabled researchers to control the generation process of the spatial VID model in the areas without wells. The analyses aimed to verify the correctness of VID model evaluation and its influence on the quality of seismic imaging in the area of the Carpathian Overthrust. Precisely, the influence was tested of such non-standard generation procedure of seismic velocity fields, not only on the PreSDM results but also on the geological interpretation of both the Rączyna and the Jodłówka gas deposits. The latter aspect of the presented results seems to be crucial to the effectiveness of petroleum exploration in the transition zone between the Carpathian Orogen and the Carpathian Foredeep.

Hierarchical transfer learning for deep learning velocity model building

Deep learning is a promising approach to velocity model building because it has the potential of processing large seismic surveys with minimal resources. By leveraging large quantities of model-gather pairs, neural networks (NNs) can automatically map data to the model space, directly providing a solution to the inverse problem. Such mapping requires big data, which proves prohibitive for 2D and 3D surveys of realistic size. We have developed a transfer learning (TL) strategy. A network is first trained on a smaller subproblem, which then becomes the starting solution to a larger, more difficult data set, akin to the hierarchical multiscale strategy for full-waveform inversion. We perform TL by having subobjectives that escalate in complexity and by first training an NN at estimating horizontally layered velocity models and then proceeding to train an augmented network at estimating 2D dipping layered models. TL improves convergence and allows using a lesser quantity of 2D models for training. For synthetic tests, the structural similarity index measure of 2D interval velocity models in the time domain is [Formula: see text] and the root-mean-square (rms) error is [Formula: see text] m/s. We benchmark our algorithm on the Marmousi2 model and observe that our method can apply to velocity models with continuous deformed layers with dips up to 35°. We benchmark our algorithm on 2D marine field data and produce an rms velocity model that leads to coherent stacking and a time interval velocity model that reproduces salient features of the stacked section. TL expedites and regularizes training and data-driven techniques may be applied to field data with minimal preprocessing even though we lack real target velocity models.

BiInNet: Bilateral Inversion Network for Real-Time Velocity Analysis

Most previous studies focus on using complex deep neural networks to learn diverse features of massive synthetic data. In more realistic situations with a limited number of data pairs, complex networks not only have higher computational complexity, increasing training time and reducing inference speed, but also tend to over-fit a small amount of training data, thus having weak generalization capability. To address the aforementioned problem, we propose a lightweight architecture for real-time velocity inversion in realistic situations, the bilateral inversion network (BiInNet). BiInNet uses lightweight ResNet18, ShuffleNetV2, and modified MobileNetV2 as backbones, taking into account the inversion accuracy and inference speed. To reduce the redundant information in common shot gathers and focus on graphical property features which are strongly correlated with velocity, the intermediate results of velocity analysis, semblances, and interval velocity models are prepared as data pairs. Numerical experiments show that BiInNet can infer interval velocity models in real-time, with frames per second (FPS) up to 76.90 when ResNet18 is used as the backbone. Moreover, BiInNet achieves the best inversion accuracy on more realistic fold models, fault models, salt models, and noisy dataset (NFOMD) when adopting ShuffleNetV2 as the backbone, which illustrates that BiInNet can be applied to velocity inversion tasks of different geological structures and is robust to noise. Adopting transfer learning to fine-tune pretrained model, BiInNet is effectively applicable to velocity reversal models and field data, which further demonstrates the reliability of the proposed method and provides a practical velocity inversion scheme when the field data pairs are insufficient.

Comparison of velocity models computed using different velocity variants and algorithms on a 2D seismic profile for poststack time migration

This article presents a construction method of the velocity field for poststack time migration for 2D seismic calculated on the basis of interval velocities in boreholes and structural interpretation, as well as the results of poststack time migration based on this solution. Three velocity field models have been developed. The models used differ in the way of spatial interpolation and extrapolation in the adopted calculation grid in the depth domain, which was created on the basis of a structural interpretation of 2D seismic profiles. Three methods of interpolation and extrapolation were used: Gaussian distribution, kriging and moving average. The spatial distribution of the interval velocities in the boreholes was made using the Petrel software by Schlumberger. The interval velocities along the analyzed seismic profile were extracted from the computed spatial interval velocity models, and after conversion from the depth to the time domain, they were used for the poststack time migration. For comparison, poststack time migration was calculated for the same seismic profile based on the stacking velocities obtained in the seismic processing data as a result of velocity analyzes. The velocity field calculated on the basis of interval velocities and structural interpretation was used for the poststack time migration procedure performed with the Implicit FD Time Migration algorithm (finite difference), while the stacking velocities were used for the poststack time migration procedure performed with the Stolt and Kirchhoff algorithms in accordance with the technical conditions of correct operation of these algorithms. The selected percentage ranges of 60%, 100%, and 140% have been used for all velocity fields. Application of the element of directional velocity variation resulting from the spatial distribution of interval velocities in the boreholes to the velocity field for the poststack time migration allowed to obtain a better seismic image in relation to the one obtained as a result of applying the stacking velocities. The most reliable seismic image after poststack time migration was obtained for the velocity field calculated on the basis of the interval velocities with Gaussian distribution, using the finite difference algorithm with 60 percent value of the velocity field.

SEMBLANCE RESIDUAL MOVEOUT ANALYSIS TO FIND ERORRS AND UPDATING THE INTERVAL VELOCITY MODEL MODE IN THE HORIZON BASED TOMOGRAPHY METHOD

The tomography method requires an excellent initial velocity model. On the horizon based tomography, it will correct the travel time error of seismic waves along the horizon which is analysed using input results from the analysis of residual depth moveout. In this study, a semblance residual moveout analysis will be conducted after the interval velocity model has applied to the SBI field seismic data (CDP Gathers and RMS velocity). Based on the imaging results generated by the PSDM running process, an aperture value of 550 for inline and 800 for crossline is selected. PSDM generated from the initial interval velocity model has an acoustic impedance value between 1000 kg/m2s to 14339.2 kg/m2s. The PSDM process, residual moveout analysis, and horizon-based tomography are carried out iteratively until the error in the interval velocity model approaches zero. In this study, five iterations were performed. The resulting residual moveout is increasingly oscillating around zero after the 5th iteration, which indicates that the error in the interval velocity model is getting smaller. There are two types of residual moveout, namely residuals moveout positively and residuals moveout negatively. Residual moveout positive indicates that the velocity used is too high, while the residual moveout negative indicates that the velocity used is too low. The identification of interval velocity model errors with analysis of residual moveout semblance is calculated from depth gathers. The semblance residual moveout analysis is used for the Pre Stack Depth Migration (PSDM) depth image analysis stage along with the marker (well data). .

Capture the variation of the pore pressure with different geological age from seismic inversion study in the Jaisalmer sub-basin, India

Geoscientific evidence shows that various parameters such as compaction, buoyancy effect, hydrocarbon maturation, gas effect and tectonic activities control the pore pressure of sub-surface geology. Spatially controlled geoscientific data in the tectonically active areas is significantly useful for robust estimation of pre-drill pore pressure. The reservoir which is tectonically complex and pore pressure is changing frequently that circumference motivated us to conduct this study. The changes in pore pressure have been captured from the fine-scale to the broad scale in the Jaisalmer sub-basin. Pore pressure variation has been distinctly observed in pre- and post-Jurassic age based on the current study. Post-stack seismic inversion study was conducted to capturing the variation of pore pressure. Analysis of low-frequency spectrum and integrated interval velocity model provided a detailed feature of pore pressure in each compartment of the study area. Pore pressure estimated from well log data was correlated with seismic inversion based result. Based on the current study one well has been proposed where pore pressure was estimated and two distinguished trends are identified in the study zone. The approaches of the current study were analysed thoroughly and it will be highly useful in complex reservoir condition where pore pressure varies frequently.

An Analysis of the Accuracy of Time Domain 3D Image Geology Model Resulted from PSTM and Depth Domain 3D Image Geology Model Resulted from PSDM in Oil and Gas Exploration

This study aims to obtain a geological model which is close to the truth and compare accuracy between the time domain 3D image of the PSTM results with the depth domain 3D image of PSDM results. There are 3 parameters to determine the accuracy of an interval velocity model in the production of a geology model: depth gathering that is already flat, semblance that has concurred with zero residual move-out axes, and depth image which conforms to the marker (well seismic tie). The analytical method employed is Horizon Based Tomography, which is a method to correct the seismic wave travel time error along the analyzed horizon. Reducing errors in the travel time of the seismic wave will decrease depth errors. This improvement is expected to provide correct information about subsurface geological conditions. The results showed that the depth domain image generated by the PSDM process represents the actual geological model better than time domain image produced by the PSTM process, evidenced by the sharpening of the reflector continuity, reduction of pull-up effect, and high resolution.

Seismic Imaging in Complex Geological Area Using Pre-Stack Depth Migration (PSDM) and Tomography Method

Pre-Stack Depth Migration (PSDM) method is required for seismic imaging in the area with complex geological structures such as fault, anticline, or syncline. Result of the PSDM depends on the interval velocity model as its input. A valid interval velocity model can yield appropriate seismic section and vice versa. One way to get an accurate interval velocity model is tomography method. This method can refine interval velocity model until it has minimum error. In this research, it’s used 2 kinds of tomography method, i.e. horizon based tomography and grid based tomography. Horizon based tomography considers the depth model in interval velocity refinement process, while grid based tomography doesn’t. Tomography is done till 6th iteration where the result of 6th iteration show the best quality of seismic section. The results show that the best quality section is PSDM using horizon based tomography. It has more geological sense than the PSDM section using grid based tomography and PSDM without tomography. Furthermore, PSDM using horizon based tomography is capable to correct pull-up effect with better continuity.

The nature of crustal reflectivity at the southwest Iberian margin

Reprocessing of multi-channel seismic reflection data acquired over the northern margin of the Gulf of Cádiz (SW Iberian margin) places new constraints on the upper crustal structure of the Guadalquivir-Portimão Bank. The data presented have been processed with optimized stacking and interval velocity models, a better approach to multiple attenuation, preserved amplitude information to derive the nature of seismic reflectivity, and accurate time-to-depth conversion after migration. The reprocessed data reveal a bright upper crustal reflector just underneath the Paleozoic basement that spatially coincides with the local positive free-air gravity high called the Gulf of Cádiz Gravity High. To investigate the nature of this reflector and to decipher whether it could be associated with pieces of mantle material emplaced at upper crustal levels, we calculated its reflection coefficient and compared it to a buried high-density ultramafic body (serpentinized peridotite) at the Gorringe Bank. Its reflection coefficient ratio with respect to the sea floor differs by only 4.6% with that calculated for the high-density ultramafic body of the Gorringe Bank, while it differs by 35.8% compared to a drilled Miocene limestone unconformity. This means that the Gulf of Cádiz reflector has a velocity and/or density contrast similar to the peridotite at the Gorringe Bank. However, considering the depth at which it is found (between 2.0 and 4.0km) and the available geological information, it seems unlikely that the estimated shortening from the Oligocene to present is sufficient to emplace pieces of mantle material at these shallow levels. Therefore, and despite the similarity in its reflection coefficient with the peridotites of the Gorringe Bank, our preferred interpretation is that the upper crustal Gulf of Cádiz reflector represents the seismic response of high-density intracrustal magmatic intrusions that may partially contribute to the Gulf of Cádiz Gravity High.

Automatic, geologic layer-constrained well-seismic tie through blocked dynamic warping

Well-log-to-seismic tying is a key step in many interpretation workflows for oil and gas exploration. Synthetic seismic traces from the wells are often manually tied to seismic data; this process can be very time consuming and, in some cases, inaccurate. Automatic methods, such as dynamic time warping (DTW), can match synthetic traces to seismic data. Although these methods are extremely fast, they tend to create interval velocities that are not geologically realistic. We have described the modification of DTW to create a blocked dynamic warping (BDW) method. BDW generates an automatic, optimal well tie that honors geologically consistent velocity constraints. Consequently, it results in updated velocities that are more realistic than other methods. BDW constrains the updated velocity to be constant or linearly variable inside each geologic layer. With an optimal correlation between synthetic seismograms and surface seismic data, this algorithm returns an automatically updated time-depth curve and an updated interval velocity model that still retains the original geologic velocity boundaries. In other words, the algorithm finds the optimal solution for tying the synthetic to the seismic data while restricting the interval velocity changes to coincide with the initial input blocking. We have determined the application of the BDW technique on a synthetic data example and field data set.

Identification of Reservoir Thickness and Estimation of Hydrocarbon Reservation used the Pre-Stack Depth Migration (PSDM) in Cikung Area

Information from the geological data shows that the Cikung field has the complex structure which is characterized by carbonate reef. Therefore, it is required in the domain depth migration (PSDM) using interval velocity model is sensitive to variations in vertical and horizontal velocity to identify the thickness of the reservoir and estimation of hydrocarbon reserves. Stages include making the depth structure maps, map making the thickness of the reservoir, and the calculation of hydrocarbon reserves. The results showed that the thickness of the reservoir in Cikung Field, estimated to range from 71 meters to 175 meters with the prospect reservoir is at a depth of 1216 meters to 1247 meters from the surface. Hydrocarbon deposits (oil) is estimated at 1,134 × 106 𝑆𝑇𝐵 or 1,311 × 108 kilo litre by the porosity of 22.6% and 70.7% water saturation.

Method Comparison of Model Based Tomography and Grid Based Tomography to refine interval velocity

<span>The input data for pre stack time migration and pre stack depth migration is velocity model. <span>The exact velocity model can provide maximum result in seismic section. The best seismic <span>section can minimize possibility of errors during interpretation. Model based and grid based <span>tomography are used to refine the interval velocity model. The interval velocity will be used as <span>input in the pre stack depth migration. Initial interval velocity is obtained from RMS velocity<br /><span>using Dix formula. This velocity will be refined by global depth tomography method. The <span>global depth tomography method is divided into model based and grid based tomography. <span>Velocity analysis is performed along the horizon (depth model). Residual depth move out is <span>obtained from picking velocity. It is used as input in tomography method. The flat gather is <span>obtained at tenth iteration. The interval velocity that is obtained from tenth iteration has the <span>small errors. Tomography method can provide maximum result on velocity refinement. That is <span>shown by the result that the pre stack depth migration is much better than using initial interval <span>velocity. The pull up effect can be corrected by tomography method.</span></span></span></span></span></span></span></span></span></span></span></span><br /></span>

Applying the Horizon Based Tomography Method to Update Interval Velocity Model, Identify The Structure of Pre-Stack Depth Migration 3D and Estimate The Hydrocarbon Reserve In SBI Field of North West Java Basin

Seismic data processing is one of the three stages in the seismic method that has an important role in the exploration of oil and gas. Without good data processing, it is impossible to get seismic image cross section for good interpretation. A research using seismic data processing was done to update the velocity model by horizon based tomography method in SBI Field, North West Java Basin. This method reduces error of seismic wave travel time through the analyzed horizon because the existence velocity of high lateral variation in research area. There are three parameters used to determine the accuracy of the resulting interval velocity model, namely, flat depth gathers, semblance residual moveout that coincides with the axis zero residual moveout, and the correspondence between image depth (horizon) with wells marker (well seismic tie). Pre Stack Depth Migration (PSDM) form interval velocity model and updating using horizon-based tomography method gives better imaging of under-surfaced structure results than PSDM before using tomography. There are three faults found in the research area, two normal faults have southwest-northeast strike and the other has northwest-southeast strike. The thickness of reservoir in SBI field, North West Java Basin, is predicted between 71 to 175 meters and the hydrocarbon (oil) reserve is predicted about with 22.6% porosity and 70.7% water saturation.

Topographic migration of 2D and 3D ground‐penetrating radar data considering variable velocities

ABSTRACTWe present a 2D/3D topographic migration scheme for ground‐penetrating radar (GPR) data which is able to account for variable velocities by using the root mean square (rms) velocity approximation. We test our migration scheme using a synthetic 2D example and compare our migrated image to the results obtained using common GPR migration approaches. Furthermore, we apply it to 2D and 3D field data. These examples are recorded across common subsurface settings including surface topography and variations in the GPR subsurface velocity field caused by a shallow ground water table. In such field settings, our migration strategy provides well focused images of common‐offset GPR data without the need for a detailed interval velocity model. The synthetic and field examples demonstrate that our topographic migration scheme allows for accurate GPR imaging in the presence of variations in surface topography and subsurface velocity.

Estimation of seismic attenuation of gas hydrate bearing sediments from multi-channel seismic data: A case study from Krishna–Godavari offshore basin

Seismic attenuation of gas hydrate bearing sediments is estimated from the multi-channel seismic data acquired in Krishna–Godavari (KG) offshore basin in the vicinity of Site NGHP-01-10, where ∼128 m of fracture-filled hydrate is confirmed by drilling/coring, to understand the effect of gas hydrate on the seismic attenuation. The seismic quality factor (Q), which is the inverse of seismic attenuation, is estimated from two methods – first, the spectral ratio method which utilizes the logarithmic ratio of the seafloor and bottom simulating reflector (BSR) spectra; and second, the peak frequency method which depends upon the variations of the peak frequency of the BSR spectrum as a function of traveltime. In the study area, the complex fault system has perturbed the seafloor resulting in noisy seafloor spectrum. As a result, the logarithm of the spectral ratio was also noisy and the Q-values obtained from spectral ratio method were found to be unstable. On the other hand, the peak frequency method is found to be relatively stable as it depends only on the peak frequency of the BSR which can be reliably obtained by conventional processing. This method yields an effective Q value of BSR which represents a weighted average of the interval Q-values of the water column and the gas hydrate bearing sediments. Since the Q-value of water column can be treated as a constant, the variations in effective Q-value can be interpreted in terms of the variations of Q in the gas hydrate bearing sediments for a constant thickness of water column.The estimated effective Q-values, along the inline and crossline seismic profiles, depend on several factors such as gas hydrate, free gas and the complex fault system. The combined interpretation of the quality factor and the interval velocity model helps to understand these effects in different zones of the seismic data. The attenuation of the background marine sediments is estimated from the analysis of crossline seismic profile. The gas hydrate bearing sediments, as inferred from the velocity model, show low attenuation as compared to that of the background sediments. In contrast, active migration of free gas across the fault system leads to increase in seismic attenuation within the gas hydrate stability zone. The complex fault zone may also lead to an increase in seismic attenuation. The blanked seismic zone shows a marginal decrease in seismic attenuation probably related to load-bearing form of gas hydrate. Our attenuation results are compared against the results obtained from waveform inversion, albeit with a higher resolution. The relative variation of Q estimated from the proposed method is close to the average Q-values estimated from full waveform inversion for most of the CDPs. The proposed methodology can be a useful technique to estimate seismic attenuation from multi-channel seismic data.

Gas hydrate and associated free gas in the Dongsha Area of northern South China Sea

A large ongoing cold seep, named Jiulong Methane Reef, was discovered in the Dongsha Area of northern South China Sea (SCS) in 2004. To understand links among seafloor methane seepage, subsurface gas hydrate, origin of gas source and structural styles controlling the formation and accumulation of gas hydrate, high resolution multi-channel seismic data were interpreted in this region. Bottom Simulating Reflectors (BSRs), known as the base of gas hydrate stability zone, were identified and mapped. Additionally, seismic attributes, interval velocity model, and acoustic P wave impedance were obtained to better delineate the spatial distribution of gas hydrate. Hydrate-bearing sediments are characterized by weak reflection (i.e. blanking zone) above BSRs, high velocities and relatively small acoustic impedance differences, while enhanced reflection, low frequency, and low velocities beneath BSRs suggest the presence of underlying free gas beneath solid hydrate. A number of faults, mud diapirs and a possible submarine landslide were observed in seismic profiles. Both faults and mud diapirs are useful conduits, allowing methane gas to migrate upward and linking free gas zones beneath BSRs, hydrate zones and seafloor methane seepage. A submarine landslide with a length scale of ∼10 km is observed in a seismic profile. The landslide may trigger dissociation of gas hydrate, accounting for the occurrence of Jiulong Methane Seepage. Seismic observations and estimated heat flow coupled with geochemical analyses suggest that gas source of methane in this region probably originates from mixture of biogenic and thermogenic methane. This study would not only help to understand gas hydrate system in the Dongsha Area, but also provide insights to geological hazards associated with the dissociation of gas hydrate.

Characterization of Intrabasin Faulting and Deformation for Earthquake Hazards in Southern Utah Valley, Utah, from High-Resolution Seismic Imaging

We conducted active and passive seismic imaging investigations along a 5.6‐km‐long, east–west transect ending at the mapped trace of the Wasatch fault in southern Utah Valley. Using two‐dimensional (2D) P ‐wave seismic reflection data, we imaged basin deformation and faulting to a depth of 1.4 km and developed a detailed interval velocity model for prestack depth migration and 2D ground‐motion simulations. Passive‐source microtremor data acquired at two sites along the seismic reflection transect resolve S ‐wave velocities of approximately 200 m/s at the surface to about 900 m/s at 160 m depth and confirm a substantial thickening of low‐velocity material westward into the valley. From the P ‐wave reflection profile, we interpret shallow (100–600 m) bedrock deformation extending from the surface trace of the Wasatch fault to roughly 1.5 km west into the valley. The bedrock deformation is caused by multiple interpreted fault splays displacing fault blocks downward to the west of the range front. Further west in the valley, the P ‐wave data reveal subhorizontal horizons from approximately 90 to 900 m depth that vary in thickness and whose dip increases with depth eastward toward the Wasatch fault. Another inferred fault about 4 km west of the mapped Wasatch fault displaces horizons within the valley to as shallow as 100 m depth. The overall deformational pattern imaged in our data is consistent with the Wasatch fault migrating eastward through time and with the abandonment of earlier synextensional faults, as part of the evolution of an inferred 20‐km‐wide half‐graben structure within Utah Valley. Finite‐difference 2D modeling suggests the imaged subsurface basin geometry can cause fourfold variation in peak ground velocity over distances of 300 m.

Reducing Uncertainty With Seismic Measurements While Drilling

This paper discusses both seismic checkshot data inversion and seismic waveform look-ahead imaging while drilling. We investigate the estimation under real-time data uncertainties of interval velocity profiles calculated from checkshot measurements acquired while drilling. It is found that real-time checkshots may suffer from downhole time-picking errors in addition to an unpredictable clock drift uncertainty. We developed a method to account for these uncertainties and to provide drillers with reliable formation interval velocity models in real time, regardless of whether the direct arrival times are detected by an automated downhole process or picked by an interpreter uphole once the seismograms have been transmitted to the surface through mud-pulse telemetry. By quantifying the posterior uncertainties in the interpreted velocity measurements, we then demonstrate: 1) the value of making the seismic waveforms recorded in downhole memory available in real time at the surface and 2) the benefit of quantifying and accounting for the standard deviations, which describe the downhole time-picking errors, in the case when the real-time seismograms are not available. This is exemplified with the application of the proposed methodology to measurements collected in deep water in the Gulf of Mexico, with inverted real-time velocity models that are consistent and comparable to the ones obtained from travel times picked after the drilling is complete. Finally, a case study is shown combining real-time checkshot inversion and downhole-to-surface transmitted seismic waveforms to look ahead while drilling for an optimal well steering in high-probability hydrocarbon sands.

Using a fine-tuned interval velocity model for improving the quality of time-to-depth conversion

Building a velocity model is a requirement for converting interpretation and seismic features from time to depth. The quality of all results obtained in downstream workflows depends on the quality of the velocity model, and, eventually, the quality of the velocity model might even affect directly the volume of produced hydrocarbons. Velocity modeling should therefore be treated with the utmost care to represent as faithfully as possible all lateral and vertical velocity variations found in the subsurface geology. But building such a velocity model could be a very challenging business indeed, since available data might be scarce and/or of poor quality, and geologic complexity might be very high.