Angle Stacks Research Articles

Automatic Conditioning of Marine Seismic Angle Stack Data With a Convolutional Neural Network

Misalignment of reflections is a common problem in migrated prestack seismic data, which occurs due to moveout correction with incomplete knowledge of the velocity model. This issue persists in partial angle stack data often used for amplitude versus offset (AVO) analyses, and is traditionally treated with residual moveout and trim static corrections. However, these methods require time-consuming velocity selection and parameter tuning, and commonly lead to spurious alignment of reflections with noise. Therefore, we train a convolutional neural network (CNN) on synthetic examples to automatically perform conditioning and alignment of angle stack data. First, two-dimensional synthetic common depth point (CDP) gathers are created using a convolutional modeling method, and then made into input-target pairs where the inputs are poorly moveout-corrected (using inaccurate normal moveout velocities) and the targets are accurately moveout-corrected. These input-target examples are split into angle stacks for the near, mid, and far offsets, and then used to train a CNN to transform the misaligned angle stacks into their more-aligned counterparts. In testing, the trained network increases the alignment of unseen synthetic data, improving the correlation with the target far offset trace from 0.76 to 0.85 on average. The network is applied on two field examples from offshore Norway with Class 3 and Class 2P AVO responses, respectively. In both cases, the angle stack data predicted by the network shows improved alignment, greater resolution in the far offset stacked section, and increased correspondence to a well-tie synthetic seismogram, all while retaining the AVO responses. The CNN predictions are compared to angle stack data following traditional conditioning (residual moveout and trim static corrections), with the results being of similar or greater quality. This method enables high quality conditioning of angle stack data at a fraction of the time required for conventional methods, and is easily adaptable to different datasets.

Energy landscape of perylenediimide chromophoric aggregates.

Understanding the self-assembly of conjugated organic materials at the molecular level is crucial in their potential applications as active components in electronic and optoelectronic devices. The type of aggregation significantly influences the intriguing electronic and optical characteristics differing from their constituent molecules. Perylenediimides (PDIs), electron-deficient molecules exhibiting remarkable n-type semiconducting properties, are among the most explored organic fluorescent materials due to their high fluorescence efficiency, photostability, and optoelectronic properties. PDI derivatives are reported to form well-tailored supramolecular architectures: cofacial with minor slip (H-aggregates), staggered with major slip (J-aggregates), magic angle stacking (M-aggregates), rotated (X-aggregates), rotated orthogonal ((+)-aggregates), etc. H*-aggregates are defined here as an ideal case of H-aggregate with an eclipsed configuration. Although numerous reports regarding the formation and optical properties of various PDI aggregates are known, the key driving force within the PDI units guiding the self-assembly to form distinct aggregate systems remains elusive. To unravel the molecular-level mechanisms behind the self-assembly of PDI units by probing the intermolecular interactions, symmetry-adapted perturbation theory-based energy decomposition, potential energy surface scans, and non-covalent interaction index analyses were employed on PDI dimer models. Quantum theory of atoms in molecules and frontier molecular orbital analyses were implemented on the dimer models to comprehend the effect of heteroatoms and orbital interactions in stabilising the X-aggregates over the other PDI aggregate systems. Competition between the attractive and repulsive non-covalent interactions dictates a stability order of X > H > J > M > (+) > H* for the PDI aggregate system, while in the parent perylene system, the stability order was found to be X > (+) > H > M > J > H*.

Azimuthal Prestack Seismic Anisotropic Inversion on a Deep and Tight Carbonate Reservoir From the North Potwar Basin of Pakistan

Summary Quantitative characterization of deep, tight, and heterogeneous reservoirs plays an important role in identifying hydrocarbon pathways for effective and optimal reservoir field development. In this case study, we used an azimuthal prestack seismic anisotropic inversion approach to estimate attributes of horizontal transverse isotropy (HTI) caused by a set of vertical fractures, oriented cracks, and stress. Anisotropic inversion facilitated the conversion of interface properties to the corresponding layer-based properties, which led to the quantitative interpretation of reservoir properties related to azimuthal variation in seismic amplitudes. To estimate the anisotropy magnitude and the direction of the isotropy axis in HTI media, elastic properties (P-impedance and Vp/Vs) obtained from prestack seismic inversion (using six azimuth × four angle stack) served as inputs. The isotropic low-frequency model (LFM) is used as the foundation of the inversion for all azimuths, and the anisotropy effects are later added by updating the model along the azimuths. The direction of the isotropy plane resulting from the anisotropic inversion is determined by using the maximum horizontal stress as a prior constraint, which eliminates any inherent uncertainty. The workflow used effectively characterized the orientation and density of fractures from the recently discovered oilfield reservoirs of the Paleocene (Lockhart) formation located in Pakistan’s north Potwar Basin. It also helped improve the prediction accuracy for fractures in the study area. According to the observations (fractures) from the exploratory drilled well (D1) in the tight carbonate (Lockhart) reservoir, a significant amount of anisotropy magnitude is observed. This provides the basis for hydrocarbon exploration, field development, and reliable drilling decisions.

Amplitude-Versus-Angle (AVA) Inversion for Pre-Stack Seismic Data with L0-Norm-Gradient Regularization

Amplitude-versus-angle (AVA) inversion for pre-stack seismic data is a key technology in oil and gas reservoir prediction. Conventional AVA inversion contains two main stages. Stage one estimates the relative change rates of P-wave velocity, S-wave velocity and density, and stage two obtains the P-wave velocity, S-wave velocity and density based on their relative change rates through trace integration. An alternative way merges these two stages to estimate P-wave velocity, S-wave velocity and density directly. This way is less sensitive to noise in seismic data compared to conventional two-stage AVA inversion. However, the regularization for the direct AVA inversion is more complex. To regularize this merged inverse problem, the L0-norm-gradient of P-wave velocity, S-wave velocity and density was used. L0-norm-gradient regularization can provide inversion results with blocky features to make formation interfaces and geological edges precise. Then, L0-norm-gradient regularized AVA inversion was performed on the synthetic seismic traces. Next, a real seismic data line that contains three partial angle stack profiles was used to test the practice application. The inversion results from synthetic and real seismic data showed that L0-norm-gradient regularized AVA inversion is an effective way to estimate P-wave velocity, S-wave velocity and density.

Real-time prediction of stomach motions based upon gastric contraction and breathing models

Objective. Precision radiation therapy requires managing motions of organs at risk that occur during treatment. While methods have been developed for real-time respiratory motion tracking, non-breathing intra-fractional variations (including gastric contractile motion) have seen little attention to date. The purpose of this study is to develop a cyclic gastric contractile motion prediction model to support real-time management during radiotherapy. Approach. The observed short-term reproducibility of gastric contractile motion permitted development of a prediction model that (1) extracts gastric contraction motion phases from few minutes of golden angle stack of stars scanning (at patient positioning), (2) estimate gastric phase of real-time sampled data acquired during treatment delivery to these reconstructed phases and (3) predicting future gastric phase by linear extrapolation using estimation results from step 2 to account for processing and system latency times. Model was evaluated on three parameters including training time window for step 1, number of spokes for real-time sampling data in step 2 and future prediction time. Main results. The model was tested on a population of 20 min data samples from 25 scans from 15 patients. The mean prediction error with 10 spokes and 2 min training was 0.3 ± 0.1 mm (0.1–0.7 mm) with 5.1 s future time, slowly rising to 0.6 ± 0.2 mm (0.2–1.1 mm) for 6.8 s future time and then increasing rapidly for longer forward predictions, for an average 3.6 ± 0.5 mm (2.8–4.7 mm) HD95 of gastric motion. Results showed that reducing of train time window (5–2 min) does not influence the prediction performance, while using 5 spokes increased prediction errors. Significance. The proposed gastric motion prediction model has sufficiently accurate prediction performance to allow for sub-millimeter accuracy while allowing sufficient time for data processing and machine interaction and shows the potential for clinical implementation to support stomach motion tracking during radiotherapy.

Lithofacies control on depositional environments in shallow offshore Niger Delta: implication on reservoir quality

The KEN field lies within latitude 4⁰52ꞌ44ꞌꞌ N to 4⁰53'04'' N and 6⁰22'50'' E to 6⁰22'26'' E. The geological and geophysical data sets were used to describe reservoir depositional facies and their environment of deposition. A detailed and accurate environment of sediment delineation is a solid basis to enhance characterization and providing measures for improving hydrocarbon reservoirs. This study aims to presents an effective method for accurately defining depositional environment with different data sets. The data used comprises of biostratigraphy, well logs from three wells and 3D full angle stack seismic data. The biostratigraphic data help to ascertain the age of the formation delineated to be middle Miocene to late Miocene based on the marker shale. It also helps in picking the stratigraphic surfaces. Three depositional sequences were delineated and dated with maximum flooding surfaces of 15.0, 12.6 and 11.5 Ma, respectively. Log sequence analysis reveals the internal geometry and stacking pattern of the mapped sequences. The gamma ray signature varies from serrated cylindrical, funnel to the bell-shaped log motif. The seismic stratigraphy involved facies analysis and reflection termination patterns, which aided the mapping of depositional sequence. The internal geometry is composed of Highstand, transgressive, and lowstand systems tracts. The stacking patterns vary from progradational, aggradational and retrogradational. Based on the seismic facies analysis, the integrated results show that the field of study is of pelagic and debris flow origin deposited in shallow marine settings, which also conform with the other data sets used for this study. The depositional environment of the three delineated reservoirs (Reservoir A, B and C) vary from deltaic upper to lower shoreface channels sand. Reservoir C, which is laterally continuous across the three studied wells shows that the connectivity of reservoir C is loosely amalgamated. The integrated data used for this study indicate that the environment of deposition varies from inner neritic to outer neritic environment. The results of this research are essential for reservoir quality, exploration, appraisal and development phases.

Characterization of seismic anisotropy using azimuthal AVO analysis (AVAz) - An application case study in the deep and tight carbonate reservoirs from Potwar Basin onshore Pakistan

Reliable characterization of subsurface fractures information within the carbonate's resources plays a key role in reservoir description in terms of the storage and movement of fluid. Commonly, anisotropy information classifies heterogeneity in the rock fabric due to fractures, pores, and local stress variations. Amplitude Variation with Azimuth investigation examines azimuthal variations in the seismic amplitude information to provide useful information about fractures and anisotropy of a horizontally transverse isotropic (HTI).This paper presents modeling, analysis, and interpretation of Azimuthal amplitude variation with angles (AVAz) from 3D seismic and calibrate results with the wells data to extract fractures information in terms of fractures magnitude and orientations. We employed two most used data-driven alternate approaches 1) near-offset Rüger's equation and 2) azimuthal Fourier Coefficient (FC) for analyzing the AVAz responses in seismic data to estimate the fractures density and their orientations, and results are calibrated with the bore hole image data (FMI). These approaches proved practically convenient to quantify the azimuthal amplitude variations with two sets of AVAZ attributes. The results of AVAz modeling and analysis required good quality of input data. Before AVAZ modeling and attributes analysis, seismic data is pre-conditioned, and the data quality of the 3D seismic dataset is improved. Several qualitative and quantitative QC measures (e.g., comparison of angle stacks, AVAz analysis, cross-plots of correlation coefficients, and time shifts) are employed to ascertain the improvement of the health of the seismic data. Azimuthal AVA modeling helped to understand the azimuthal amplitude response due to anisotropy caused by fractures/stress. The predicted seismic response from the models is used to assess the sensitivity of AVAZ with the parameters of the anisotropic model. After the AVAZ modeling, the outcomes of the AVAZ attributes are generated using to 3D seismic and calibrated with the well data set to identify the anomaly of anisotropic gradient (Bani) and second Fourier coefficients (R2) by relating to fractures density or stress magnitude. These attributes helped to identify the amplitude variations with offset and azimuth in the deep inhomogeneous tight carbonate reservoir interval (Patala) of DS hydrocarbon field discovered in the north Potwar Basin, onshore Pakistan. High score of Bani or R2 observed at well location at the tight Paleocene carbonate (Patala formation) reservoirs exhibited the presence of fractures which is confirmed from the image logs (e.g., FMI).The results demonstrated that the studied formations exhibit significant heterogeneity due to the faults/fractures and stresses associated with the complex geological structure of the basin as well as variations in the rock fabric. Hence, accurate analysis of the fractures information from seismic data is quite useful not only in understanding the reservoir heterogeneity to optimize the production, but also in predicting the completion and development strategies that may be most effective.

Integrating rock physics and sequence stratigraphy for characterization of deep-offshore turbidite sand system

Definition and understanding deep water depositional environment is essential, especially in exploration and development phase. This study is aimed at improving characterization and environment of deposition assessment of deepwater turbidite sands systems as a way of evaluating reservoir geometry and quality in “NOJA” field, deep-offshore Niger Delta. The data used for the analysis comprise 3D full angle stack seismic, biofacies and logs from five wells. Seismic sequence analysis using reflection termination patterns were used for the mapping of depositional sequences. The sequences have internal reflection geometries ranging from parallel, subparallel and chaotic. Seismic structural maps gave insight into rock deformation and hydrocarbon potential of the field. The probable structure responsible for the trapping of oil and gas was a faulted anticlinal structure. Amplitude maps of the two stratigraphic surfaces gave insight into sand and shale distributions and possible environment of sediment deposition. Rock physics concepts were utilised to evaluate reservoir continuity, diagenetic and environment of deposition effects influencing reservoir properties. Two reservoirs (R1 and R2) of interest occurred at a depth interval of 2398–2461 m. Reservoir (R1) has average volume of shale of 22%, effective porosity 20%, hydrocarbon saturation 53%, and permeability 556 mD. Reservoir (R2) has average volume of shale of 10%, effective porosity 26%, hydrocarbon saturation 79%, and permeability 1044 mD. Environment of sediment deposition of the reservoirs was weakly confined with distributary channel complexes. Reservoir (R1) had low degree of connectivity (loosely amalgamated turbidite sand system) and reservoir (R2) possessed high degree of connectivity (highly amalgamated turbidite sand system). Rock physics templates of constant, contact and friable showed that the reservoir sands were poorly cemented to unconsolidated. These models indicated that the reservoir sands were both influenced by depositional and depth related diagenetic effects.

Elastic Impedance Simultaneous Inversion for Multiple Partial Angle Stack Seismic Data with Joint Sparse Constraint

Elastic impedance (EI) inversion for partial angle stack seismic data is a key technology in seismic reservoir prediction within the oil and gas industry. EI inversion provides a consistent framework to invert partial angle stack seismic data, just as the AI inversion does for post-stack data. The commonly used EI inversion process is angle by angle. Hence, the inverted EI for different angles may be nonconforming, especially for the seismic data with a low signal-to-noise ratio. This paper proposes to simultaneously invert multiple partial angle stack seismic data to obtain EI for different angles at once. To obtain conformable EI, we used the joint sparse constraint on the reflection coefficients for different angles. Then, the objective function for simultaneous EI inversion was constructed. Next, synthetic seismic data profiles with three different angles were used to show the superiority of the proposed EI inversion method compared to the conventional method. At last, a real seismic data line was used to test the feasibility of the proposed method in practice. The inversion results of synthetic data and real data showed that it provides an effective new alternative method to estimate EI from partial stack seismic data.

Reservoir characterization for hydrocarbon detection using Amplitude Variation with Angles constrained by localized rock physics template

Seismic data are prone to ambiguities because different scenarios of geological structures and rock properties can produce similar seismic reflections. The poorly compacted sandstone reservoirs of the ‘Jay’ Field produced seismic amplitude anomalies which may not be diagnostic of hydrocarbon presence. In this study, the different seismic amplitude reflections from ‘Jay’ Field reservoirs were investigated to determine the effect of fluids and lithologies on the observed seismic amplitudes for possible hydrocarbon identification away from well location. Amplitude Variation with Angles (AVA) and Rock physics techniques were used to analyze amplitude responses from sandstone reservoirs. These seismic amplitudes were extracted from the near and far partial angle stacks to identify changes in amplitudes with angles. Reservoir properties were examined to determine their influence on seismic responses through Rock Property Template (RPT) analysis. Well logs revealed that three of the seven identified reservoirs (Sands A, B and C) are brine saturated, Sand D is oil while Sands E, F and G are gas bearing. The reservoirs stratification is mainly the juxtaposition of low impedance sandstone and high impedance shale, such that P-velocity and density significantly influence impedance contrast in sandstone reservoirs and shale lithologies respectively. Changes in seismic amplitudes from near to far angles around Well location show that the gas reservoirs produce different AVOs that correspond to Classes II, III and IV respectively. The established Well log RPT supports AVA results of gas presence in the identified area away from Well location. This helps to reduce the risk associated with seismic amplitude ambiguities and enhanced certainty of gas presence at the location away from Well log information. In similar geological scenario, this work can serve as a useful guide to gas sand detection from seismic data.

KUALITAS FISIK PAKAN PELLET BERBAHAN AMPAS SAGU DENGAN PENAMBAHAN INDIGOFERA MENGGUNAKAN LEVEL TEPUNG TAPIOKA YANG BERBEDA

This study aims to determine the physical quality of water content, specific gravit, stack angle, pile density, pile compaction density, and collision resistance pellet product with sago pulp utilization and indigofera leaves. This research used CRD Factorial. Factor A consist of 5 treatments A4 = 40% Sago Pulp (SP) + 60% Indigofera Leaves (IL), A3 = 30% SP + 70% IL, A2 = 20% (SP) + 80% (IL), A1 = 10% (SP) + 90%, (IL), A0 = 100% (IL) and Factor B consisting of 2 treatments B1 = 5% Tapioca Flour B2 = 10% Tapioca Flour with 3 replications each. The results showed that the interaction between sago pulp feed ingredients with the addition of indigofera leaves used adhesive material at different levels. It was concluded that the combination of sago and indigofera dregs (40% SP + 60% IL) levels can improve the quality of pellets in terms of density, pile angle, and pellet stack density

Prediction of Gamma Ray data from pre-stack seismic reflection partial angle stacks using Continuous Wavelet Transform and convolutional neural network approach

Seismic inversion is one of the critical issues for geophysicists in the oil and gas industry. It is commonly used to estimate the distribution of facies-types and fluids in reservoirs across the value chain from exploration to development. However, the low vertical and spatial resolution of seismic data leads to large uncertainties in these estimations, which makes direct use of inversion results challenging. The objective of this study was the estimation of a 3D volume of Gamma Ray data from pre-stack seismic reflectivity partial angle stacks based on the Convolutional Neural Network architecture by representing data through the Continuous Wavelet Transform. The proposed methodology used 132 deviated wells from the Azeri and Chirag parts of the Azeri – Chirag – Gunashli field in the South Caspian Basin as training data. Blind tests show promising Gamma Ray predictions. To optimize the predictions, sensitivity analysis was performed on the Continuous Wavelet Transform parameters (wavelet types, range of pseudo-frequencies, etc.), the Convolutional Neural Network architecture (number of convolutional and pooling layers, dropout, activation functions) and the network parameters (batch size, number of epochs, optimizers, etc.). Due to the vast amount of data required to speed up the learning process, simulations were performed on a Graphics Processing Unit based on the Compute Unified Device Architecture platform.

Metaheuristic Optimization of Laminated Composite Plates with Cut-Outs

The stacking sequence optimization of laminated composite plates while maximizing the structural performance or minimizing the weight is a subject investigated extensively in the literature. Meanwhile, research on the optimization of laminates with cut-outs has been relatively limited. Cut-outs being an indispensable feature of structural components, this paper concentrates on the stacking sequence optimization of composite laminates in the presence of circular cut-outs. The buckling load of a laminate is used as a metric to quantify the structural performance. Here the laminates are modeled as carbon fiber-reinforced composites using the finite element analysis software, ABAQUS. For the optimization, the widely used harmony search algorithm is applied. In terms of design variables, ply thickness, and fiber orientation angles of the plies are used as continuously changing variables. In addition to the stacking sequence, another geometric variable to consider is the aspect ratio (ratio of the length of the longer sides to the length of the shorter sides of the plate) of the rectangular laminates. The optimization is carried out for three different aspect ratios. It is shown that, by using dispersed stacking sequences instead of the commonly used 0°/±45°/±90° fiber angle stacks, significantly higher buckling loads can be achieved. Furthermore, changing the cut-out geometry is found to have a significant effect on the structural performance.

Simultaneous Seismic Inversion for Reservoir Characterization at Poseidon Field, Browse Basin, Australia

Seismic inversion method has been widely used to obtain reservoir property in an oil and gas field. In this research, one of inversion methods known as simultaneous inversion is used to analyze reservoir characterization at Poseidon Field, Browse Basin. Simultaneous inversion is applied to partial angle stack data and result in volume of Acoustic Impedance (AI), Shear Impedance (SI) and Lame parameter (LMR). The objective of this study is to determine distribution of sandstone lithology with gas saturated in Plover reservoir formation. Sensitivity analysis is done by cross-plotting elastic and Lame parameter from five well log data and analyzing lithology type and fluid saturation. Based on those cross-plots, lithological type can be identified from AI, λρ, µρ and λ/µ parameters. Meanwhile, the presence of gas can be discriminated using SI, λρ, and λ/µ parameters. Gas-saturated sandstone presence is characterized by Lambda-Rho value less than 50 GPa g cc-1 and Lambda over Mu value less than 0.8 GPa g cc-1. Maps of each parameter are generated at reservoir interval. Based on those maps, it can be concluded that gas sand spread out in the eastern and western areas of research area.

Hydrocarbon reservoir delineation using simultaneous and elastic impedance inversions in a Niger Delta field

The global energy demand is increasing while production from mature fields is drastically reducing consequently, oil and gas industries are expanding activities into more challenging areas. The inability of the traditional seismic data to properly delineate hydrocarbon reservoirs from subtle seismic features in ‘Sandfish’ field located offshore, Niger Delta informed the use of simultaneous and elastic impedance inversion. The elastic and derived volumes from seismic inversion would reduce risk, enhance hydrocarbon discovery and optimize development plans in the study area. Four ‘Sandfish’ (Sfn) wells (Sfn-01, Sfn-02, Sfn-04 and Sfn-05), check-shots and 3D seismic data of five angle stacks (6–12°, 12–18°, 18–26°, 26–32° and 32–42°) were used in the study. Low frequency (0–2 Hz) models were generated from interpolation of high-cut-filtered compressional wave velocity log (P-sonic), shear wave velocity log (S-sonic) and density log guided by interpreted four seismic horizons. The low frequency models broaden the spectrum of the elastic volumes and also served as inversion constraints. The five partial angle stacks varying from 6–42° were simultaneously inverted using Jason’s Rock-Trace® inversion software which iterated trial inversions until the model sufficiently matched the seismic data. The near (6–12°) angle and far-far (32–42°) angle stacks were also inverted and compared with the inverted volumes from the simultaneous inversion. This was carried out to determine the effectiveness of near and far-far elastic impedance volume in delineating hydrocarbon reservoirs. The inverted elastic volumes P-impedance (ZP), S-impedance (ZS), density (ρ), near and far-far elastic and derived volumes lambda-rho (λρ), mu-rho (µρ), Poisson’s-ratio (σ) reveal vertical and lateral continuity of the reservoirs identified (K01, N01 and P01) at 2179 m, 2484 m and 3048 m, respectively. The delineated reservoirs showed good match with the sand tops away from the well control validated by a blind well test. The cross-plot of inverted ZP from simultaneous inversion and well ZP gave correlation coefficient of 86% indicative of high quality inverted volume which will reduce exploration risk. The plot of inverted ZP from simultaneous inversion and inverted far-far elastic volume reflected 82% correlation coefficient indicating that this method could be adopted in other fields with limited data and similar geological setting. Hence, the study has shown the efficacy of elastic volumes in delineating hydrocarbon reservoirs which can help locate optimum region for development wells.

Extended Elastic Impedance Inversion for Better Delineation of Gasbearing Sand Reservoir, Saffron Gas Field, Offshore Nile Delta, Egypt

Extended Elastic Impedance (EEI) is a very useful seismic reconnaissance attribute. EEI logs can directly correspond to the petrophysical properties of the reservoir and the seismic. EEI reflectivity volumes can be obtained directly from the pre-stack seismic data. Better discrimination between the seismic anomaly caused by either lithology or fluid content can be utilized by applying this approach. The concept of extended elastic impedance is used to derive the petrophysical properties and distribute the reservoir facies. The study area was a Pliocene gas field, that lies in the deep marine, Offshore Nile Delta, Egypt. The workflow is simple, efficient, and uses very few inputs. We started with the fluid/ lithology logs and investigated the optimum projection in the intercept/gradient domain. Then, we used the conditioned angle stacks, to calculate the intercept/ gradient volumes, using Shuey’s two-term Approximation. The intercept and gradient volumes are converted directly to the fluid and lithology 3D volumes, without any of the pre-stack inversion constraints. The outputs were tested using a blind well and the correlation exceeds 80%. The results show that the EEI is a worthy effort to highlight the difference between the reservoir and nonreservoir sections, to identify the hydrocarbon area.

Anisotropic 3D elastic full-wavefield inversion to directly estimate elastic properties and its role in interpretation

Elastic properties from seismic data are important to determine subsurface hydrocarbon presence and have become increasingly important for detailed reservoir characterization that aids to derisk specific hydrocarbon prospects. Traditional techniques to extract elastic properties from seismic data typically use linear inversion of imaged products (migrated angle stacks). In this research, we attempt to get closer to Tarantola's visionary goal for full-wavefield inversion (FWI) by directly obtaining 3D elastic properties from seismic shot-gather data with limited well information. First, we present a realistic 2D synthetic example to show the need for elastic physics in a strongly elastic medium. Then, a 3D field example from deepwater West Africa is used to validate our workflow, which can be practically used in today's computing architecture. To enable reservoir characterization, we produce elastic products in a cascaded manner and run 3D elastic FWI up to 50 Hz. We demonstrate that reliable and high-resolution P-wave velocity can be retrieved in a strongly elastic setting (i.e., with a class 2 or 2P amplitude variation with offset response) in addition to higher-quality estimation of P-impedance and VP/VS ratio. These parameters can be directly used in interpretation, lithology, and fluid prediction.

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,

Application of spectral decomposition as a direct hydrocarbon indicator within the challenging rock physics environment

A study was conducted to use low-frequency amplitudes obtained through spectral decomposition as a direct hydrocarbon indicator within the geologically and seismically challenging area. An offshore data set from the Gulf of Thailand with well-known geology and good well control for both water and hydrocarbon bearing zones were used in this study. The rocks physics reveals similar P-impedance for gas and water-wet sands. Moreover, organic shales have similar Poisson’s ratio as of gas saturated zones. This makes differentiation of fluids and lithologies through post-stack seismic inversion and AVO analysis difficult. Reservoir wedge modelling, spectral decomposition of the synthetic and field data and analyses were conducted to understand the spectral decomposition response to thickness variation and reservoir fluids. Spectral decomposition was also applied on partial angle stacks (near, mid and far). Gas sands show bright amplitudes at low frequencies (from 10 to 15 Hz). However, spectral decomposition of the synthetic seismogram of the organic shales indicates that it consists of only relatively higher frequencies (greater than 25 Hz). Therefore, low-frequency amplitudes of spectral decomposition may help to identify hydrocarbon saturated zones.

Effects of ply angle and blocking on open-hole tensile strength of composite laminates: A design and certification perspective

The failure strength of carbon-fibre reinforced plastic laminates under open-hole tension varies considerably with ply angle, ply blocking and loading direction. Here, laminates with various standard-angle and non-standard angle stacking sequences are subjected to both on- and off-axis loading in a comprehensive experimental and progressive damage finite element analysis testing campaign. It is found that interlaminar and intralaminar matrix damage can be beneficial when accumulated sub-critically in ply blocks aligned with loading direction, but can also lead to significant strength decreases owing to edge failure. In such cases, a numerical edge treatment is proposed for more accurate representation of open-hole tensile strength in large structures where holes are positioned away from free edges. The solution suppresses edge failure and results in up to 80% strength increases, challenging the validity of standard open-hole tension testing and current design rules for some applications.