Single-step probabilistic inversion of 3D seismic data of a carbonate reservoir in Southwest Iran

We use a sampling-based Markov chain Monte Carlo method to invert seismic data directly for porosity and quantify its uncertainty distribution in a hard-rock carbonate reservoir in Southwest Iran. The noise that remains on seismic data after the processing flow is correlated with the bandwidth in the range of the seismic wavelet. Hence, to account for the inherent correlated nature of the band-limited seismic noise in the probabilistic inversion of real seismic data, we assume the estimated seismic wavelet as a suitable proxy for capturing the coupling of noise samples. In contrast to the common approach of inserting a delta function on the main diagonal of the covariance matrix, we insert the seismic wavelet on its main diagonal. We also calibrate an empirical and a semi-empirical inclusion-based rock-physics model to characterize the rock-frame elastic moduli via a lithology constrained fitting of the parameters of these models, i.e. the critical porosity and the pore aspect ratio. These calibrated rock-physics models are embedded in the inversion procedure to link petrophysical and elastic properties. In addition, we obtain the pointwise critical porosity and pore aspect ratio, which can potentially facilitate the interpretation of the reservoir for further studies. The inversion results are evaluated by comparing with porosity logs and an existing geological model (porosity model) constructed through a geostatistical simulation approach. We assess the consistency of the geological model through a geomodel-to-seismic modeling approach. The results confirm the performance of the probabilistic inversion in resolving some thin layers and reconstructing the observed seismic data. We present the applicability of the proposed sampling-based approach to invert 3D seismic data for estimating the porosity distribution and its associated uncertainty for four subzones of the reservoir. The porosity time maps and the facies probabilities obtained via porosity cut-offs indicate the relative quality of the reservoir’s subzones.

Estimation of the depth-domain seismic wavelet based on velocity substitution and a generalized seismic wavelet model

Depth-domain seismic wavelet estimation is the essential foundation for depth-imaged data inversion, which is increasingly used for hydrocarbon reservoir characterization in geophysical prospecting. The seismic wavelet in the depth domain stretches with the medium velocity increase and compresses with the medium velocity decrease. The commonly used convolution model cannot be directly used to estimate depth-domain seismic wavelets due to velocity-dependent wavelet variations. We develop a separate parameter estimation method for estimating depth-domain seismic wavelets from poststack depth-domain seismic and well log data. This method is based on the velocity substitution and depth-domain generalized seismic wavelet model defined by the fractional derivative and reference wavenumber. Velocity substitution allows wavelet estimation with the convolution model in the constant-velocity depth domain. The depth-domain generalized seismic wavelet model allows for a simple workflow that estimates the depth-domain wavelet by estimating two wavelet model parameters. Additionally, this simple workflow does not need to perform searches for the optimal regularization parameter and wavelet length, which are time-consuming in least-squares-based methods. The limited numerical search ranges of the two wavelet model parameters can easily be calculated using the constant phase and peak wavenumber of the depth-domain seismic data. Our method is verified using synthetic and real seismic data and further compared with least-squares-based methods. The results indicate that the proposed method is effective and stable even for data with a low S/N.

Examination of the Seismic Characteristics of Onshore Reservoirs for Dom Gas Production Potentials in the Niger Delta Region of Nigeria

The objective of this research work is to examine two prominent dom gas reservoirs H1000 and H4000 in onshore Niger Delta region of Nigeria for potential production activities using seismic wavelet and well-to-seismic tie process to facilitate interpretation and evaluate dom gas (hydrocarbon) bearing formation. Well log and sidewall samples analyses show that the velocity attributes, high P-wave, S-wave and Vp/Vs ratio characterize sediments with high concentration of dom gas. The wells validated the presence of dom gas with total gas in place on the field estimated at 4.017 trillion ft3, GIIP 5,228.683 bscf, CIIP 445.136 MMstb, and STOIIP 34.647 MMstb, URg 4,120.494 bscf and URc 219.208 MMstbl, 90 % of which resides in the two reservoirs. The hydrocarbon intervals are estimated at H1000 (8864 ft, TVDSS) and H4000 (9577 ft, TVDSS). The borehole information was combined with seismic data to confirm lateral continuity of the dom gas reservoirs.

Simultaneously computing the 3D dip attributes for all the time samples of a seismic trace

The seismic dip attribute is regularly used to aid structural interpretation and is commonly adopted as a compulsory input for computing other seismic geometric attributes. One disadvantage of current dip computation algorithms is that interpreters compute the dip attribute time sample by time sample and do not consider the relationship between dip values of nearby samples. The classic convolution theory suggests one formation boundary should have the corresponding seismic event. However, the seismic wavelet always has a certain time duration. As a result, one formation boundary has a corresponding seismic event that consists of several time samples. Ideally, the time samples, which belong to the same boundary, should have approximately the same dip attributes. In this research, a sample by sample computation procedure is treated as an independent optimisation procedure. Then, simultaneously computing the seismic dip of time samples of one seismic trace can be regarded as a multi-objective optimisation procedure. The proposed method is based on analysing features of seismic waveform within user-defined windows. Considering that nearby time samples should have continuous dip values, we the dynamic time warping to simultaneously compute seismic reflectors’ dip values of a seismic trace. We applied our method to a field seismic data to demonstrate its effectiveness.

A new denoising strategy and the X-shaped supplement denoising operator targeting time-reversed mirror imaging technique

Imaging of vertical structures is a challenge in the seismic imaging field. The conventional imaging methods for vertical structures are highly dependent on the reference model or boreholes. Time-reversed mirror imaging can effectively image the vertical structures based on the multiples and a smoothed velocity model without the need of accurate seismic wavelet estimation. Although the Laplacian operator is applied in time-reversed mirror imaging, there still exists severe residual noise. In this study, we developed a new imaging denoising strategy and an X-shaped supplement denoising operator for time-reversed mirror imaging based on the geometric features of the image and the causes of imaging noise. Synthetic results for the single- and double-staircase model prove the powerful denoising capacity of the X-shaped supplement denoising operator. In addition, the results of a Marmousi model prove that the X-shaped denoising operator can also effectively suppress the noise when applying time-reversed mirror imaging method to image complex inclined structures. However, the X-shaped denoising operator still contains some limitations, such as non-amplitude-preserving.

Seismic-to-well tie of a field of the Nigerian Delta

This paper presents a rigorous but pragmatic and data driven approach to the science of making seismic-to-well ties. This pragmatic approach is consistent with the interpreter’s desire to correlate geology to seismic information by the use of the convolution model, together with least squares matching techniques and statistical measures of fit and accuracy to match the seismic data to the well data. Three wells available on the field provided a chance to estimate the wavelet (both in terms of shape and timing) directly from the seismic and also to ascertain the level of confidence that should be placed in the wavelet. The reflections were interpreted clearly as hard sand at H1000 and soft sand at H4000. A synthetic seismogram was constructed and matched to a real seismic trace and features from the well are correlated to the seismic data. The prime concept in constructing the synthetic is the convolution model, which represents a seismic reflection signal as a sequence of interfering reflection pulses of different amplitudes and polarity but all of the same shape. This pulse shape is the seismic wavelet which is formally, the reflection waveform returned by an isolated reflector of unit strength at the target depth. The wavelets are near zero phase. The goal and the idea behind these seismic-to-well ties was to obtain information on the sediments, calibration of seismic processing parameters, correlation of formation tops and seismic reflectors, and the derivation of a wavelet for seismic inversion among others. Three seismic-to-well ties were done using three partial angle stacks and basically two formation tops were correlated. Keywords: seismic, well logs, tie, synthetics, angle stacks, correlation,

A frequency-decomposed nonstationary convolutional model for amplitude-versus-angle-and-frequency forward waveform modeling in attenuative media

The conventional convolutional model (CCM) is widely applied to generate synthetic seismic data for numerous applications including amplitude variation with offset forward modeling, seismic well tie, and inversion. This approach assumes frequency-independent reflection coefficients and time-invariant seismic wavelets in laterally homogeneous elastic media. We have extended CCM to heterogeneous poroelastic media in which reflection coefficients are frequency dependent and the seismic wave is attenuated as it propagates. First, we decompose the seismic wavelet into monofrequency components through the Fourier transform. Then, to account for the attenuation effects at the reflection interfaces, we multiply the frequency-dependent reflection coefficients series with an attenuation function of frequency-variant quality factor [Formula: see text]. Finally, we convolve this product results with a monofrequency wavelet and sum all of the frequencies together to obtain the synthetic seismograms. The advantage of the proposed frequency-decomposed nonstationary convolutional model is that it takes into account the effects of attenuation on the wave reflections and propagation in attenuative media. In addition, it uses the frequency-dependent [Formula: see text] instead of the constant [Formula: see text] that is used by the traditional nonstationary convolutional model. The technique has been applied to amplitude-versus-angle-and-frequency forward waveform modeling in attenuative media, and it shows good agreement between synthetic and real data on seismic well ties.

Seismic well tie by aligning impedance log with inverted impedance from seismic data

The accuracy of seismic inversion is affected by the seismic wavelet and time-depth relationship generated by the process of the seismic well tie. The seismic well tie is implemented by comparing the synthetic seismogram computed from well logs and the poststack seismogram at or nearby the borehole location. However, precise waveform matching between the synthetic seismogram and the seismic trace does not guarantee an accurate tie between the elastic properties contained represented by the seismic data and well logs. We have performed the seismic well tie using the impedance log and the impedance inverted from poststack seismic data. We use an improved dynamic time warping to align the impedance log and impedance inverted from seismic data. Our workflow is similar to the current procedure of the seismic well tie except that the matching is implemented between the impedance log and the inverted impedance. The current seismic well-tie converges if there is no visible changes for the wavelets and time-depth relationship in the previous and current tying loops. Similarly, our seismic well tie converges if there are no visible changes for the wavelets, inverted impedance, and time-depth relationship in the previous and current tying loops. The real data example illustrates that more accurate inverted impedance is obtained by using the new wavelet and time-depth relationship.

A method to compensate for migration stretch to improve the resolution of amplitude variation with offset, S-impedance (ZS), and density (ρ)

Because of their improved leverage against ground roll and multiples, as well as the ability to estimate azimuthal anisotropy, wide-azimuth 3D seismic surveys routinely now are acquired over most resource plays. For a relatively shallow target, most of these surveys can be considered to be long offset as well, containing incident angles up to 45°. Unfortunately, effective use of the far-offset data often is compromised by noise and normal moveout (NMO) (or, more accurately, prestack migration) stretch. The conventional NMO correction is well-known to decrease the frequency content and distort the seismic wavelet at far offsets, sometimes giving rise to tuning effects. Most quantitative interpreters work with prestack migrated gathers rather than unmigrated NMO-corrected gathers. However, prestack migration of flat reflectors suffers from the same limitation called migration stretch. Migration stretch leads to lower S-impedance ([Formula: see text]) and density ([Formula: see text]) resolution estimated from inversion, misclassification of amplitude variation with offset (AVO) types, and infidelity in amplitude variation with azimuth (AVAZ) inversion results. We have developed a matching pursuit algorithm commonly used in spectral decomposition to correct the migration stretch by scaling the stretched wavelets using a wavelet compensation factor. The method is based on hyperbolic moveout approximation. The corrected gathers show increased resolution and higher fidelity amplitudes at the far offsets leading to improvement in AVO classification. Correction for migration stretch rather than conventional “stretch-mute” corrections provides three advantages: (1) preservation of far angles required for accurate [Formula: see text] inversion, (2) improvement in the vertical resolution of [Formula: see text] and [Formula: see text] volumes, and (3) preservation of far angles that provide greater leverage against multiples. We apply our workflow to data acquired in the Fort Worth Basin and retain incident angles up to 42° at the Barnett Shale target. Comparing [Formula: see text], [Formula: see text], and [Formula: see text] of the original gather and migration stretch-compensated data, we find an insignificant improvement in [Formula: see text], but a moderate to significant improvement in resolution of [Formula: see text] and [Formula: see text]. The method is valid for reservoirs that exhibit a dip of no more than 2°. Consistent improvement is observed in resolving thick beds, but the method might introduce amplitude anomalies at far offsets for tuning beds.