Advance Wave Modeling and Diffractions for High-Resolution Subsurface Seismic Imaging

Seismic modeling and Imaging for the small-scale feature in a complex subsurface geology such as salt deposit, fracture reservoir, and Carbonate is not casual because of propagated wave affected by many objects once it hits the geologic structure in the subsurface. The principal goal of newly developed seismic modeling & imaging is to get a subsurface image of structural features with greatest sharpness or resolution. Using model dataset the Sigsbee and Marmousi, we illustrate the accuracy of conventional and advance wave modeling techniques. However, in conventional a Finite difference (FD) algorithm is used to generate the data and in advanced wave modeling, the low-rank (LR) approximation is used to acquire zero-offset configuration data. A field dataset from Malaysian basin is re-processed and imaged using diffraction imaging which shows an enhancement in structural interpretation. Furthermore, the results gained from the proposed modeling and imaging approach significantly enhance the bandwidth of the imaged data. Finally, a frequency spectrum shows a recovery of low-frequency from 0 to 60 Hz which is an optimal resolution of seismic imaging

Elastic-Based Brittleness Estimation from Seismic Inversion

Information about mechanical rock properties is essential when tight reservoir is to be stimulated using hydrofracturing technique. The brittle area has to be considered as a priority region for determining the location of hydrofracturing initiation. Seismic data are commonly used to estimate the geomechanical properties such as brittleness average from elastic properties: Poisson’s ratio and Young’s modulus. This paper discusses the process of brittleness estimation based on elastic properties, which can be derived by inverting the pre-stack seismic data that can produce acoustic impedance, shear impedance, and density simultaneously. Novel methods, scaled inverse quality factor of P-wave (SQp) and scaled inverse quality factor of S-wave (SQs) attributes, have been used for identification of brittleness, fracture density, and hydrocarbon bearing in the fractured basement reservoir. The effectiveness of the proposed method has been tested in the field, which is consistent with fracture density log from formation micro-imager (FMI) log and hydrocarbon column data. The result showed that there is a significant correlation between brittleness, estimated from elastic properties, and fracture density logs. New attributes, the SQp attribute is potentially to be used as a fracture density indicator, while SQs attribute indicates the existence of hydrocarbon, which is confirmed with neutron porosity-density logs

Optimizing acquisition geometry in shallow gas cloud using particle swarm optimization approach

Many hydrocarbon explorations in mature fields have been severely affected by complex and overburdening issues, such as shallow gas accumulation, gas pockets, and gas seepage. In this work, a new forward modelling technique is proposed in evaluating the potential survey design for fields affected by shallow gas cloud. In recent years, the implementation of innovative acquisition layouts has been producing significantly better seismic images, especially in the low illumination subsurface area. However, the uncertainty of the effectiveness in new acquisition design subsurface coverage always become a major stumbling block. To overcome this constraint, an optimization approach is suggested through the smart source and receiver location arrangement on the surface, with significant alignment to the conventional source and receiver arrangement approach. The particle swarm optimization (PSO) method is used to find the source-receiver configuration with maximum subsurface illumination coverage for the gas affected field situated in Malaysia Basin. Implementation of the PSO algorithm requires both a velocity model building process and wave field extrapolation from a target reflector to the surface level. The wave field data then was used to simulate receiver optimization outputs which eventually determined the subsurface illumination coverage. The results from the new optimization method for both synthetic model and Malaysia Basin data, offer a greater understanding of the consequences of obstacles caused by shallow anomalies with respect to seismic acquisition, data processing, and interpretation

INNOVATIVE WORKFLOW FOR SEISMIC ACQUISITION DESIGN

Any new survey geometry design must be based on thorough integrated analysis and modeling of project goals and objectives, exploration and/or field development targets’ requirements, available technologies, operational constraints, terrain conditions and project budgets. A critical matrix for a good quality seismic acquisition geometry design is dense and uniform distribution of seismic traces in areal extent and within CDP, bins with sufficiently high trace density, high fold, wide azimuth, long inline/crossline/maximum offsets and small largest minimum offset. That said, operational considerations could be a hindrance for such quality as in heavily congested fields, extensive network of wells, platforms, production facilities and terrain obstacles leading to gaps in coverage and severe irregularities of fold, offset and azimuth distributions. This work demonstrates the essential value of using all available data and information about the project area. Such as well logs, RMS and interval velocities, legacy 2D and 3D seismic acquisition and processing reports, satellite and positioning maps, scouting reports, multi-physics maps and data and near surface environmental reports are all relevant. Thus, detailed, accurate and realistic estimates of the design’s attributes are generated including desired temporal and spatial resolution, focused target illumination parameters, signal penetration, recording requirements and noise minimization processes

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

New approach towards the classification of microporosity in Miocene carbonate rocks, Central Luconia, offshore Sarawak, Malaysia

Microporosity is recognized as a significant concern in limestone reservoirs throughout the world because it presence can highly complicate the hydrocarbon estimation and production. Numerous studies around the globe emphasises on the physical appearance, occurrence, and abundance of microporosity, but no published study has been emphasises on the presence of microporosity in Miocene carbonate reservoirs. Miocene carbonates from Central Luconia, offshore Sarawak, Malaysia, contains a significant amount of micropores, which occurs in grain, matrix, and cement. For a better understanding of the presence of micropores, it is necessary to consider grains, matrix, cement, and pore types. Based on the qualitative and quantitative knowledge of these components a classification of micropores is proposed and their effect on reservoir quality. These results can reduce the number of the assumption made about the internal rock connectivity and quality.For quantitative analysis, 32 high-resolution images of each thin sections were taken under the transmitted light microscopy. Succeeding these 32 images were stacked together as a photo panel to enable quantifying the amount of grain, matrix, cement, pore types and macroporosity using Digital Image Analysis and J.Microvision software. Furthermore, Field Emission Scanning Electron Microscopy images were also used for the measurement of crystallometry of micrite particles, classification of micrite particles and the micropores.Eight facies scheme is introduced based on the detailed lithofacies study of five wells. The qualitative observation of thin sections unveiled that corals, red algae, green algae, foraminifera, echinoderms, sponge, bivalve, and bryozoans are the most dominant components. Foraminifera, red algae, and corals are the far most dominant components covering almost 50% of the total intervals. Regarding porosity types, the mouldic porosity is the far most dominant pore types with converting the total 50% of the interval. Lithofacies observed in these wells indicate a good reservoir quality, but diagenesis plays a vital role in enhancing or reducing their porosity and permeability. Most of the depositional textures of the reservoir are leached, making this location unique to study facies distribution and diagenetic history.Result exhibits that the micrite particles are classified into five classes, which are very fine, fine, medium, coarse and very coarse, with a diameter of 0.1–2 μm, 2–4 μm, 4–6 μm, 6–8 μm and 8–10 μm respectively. The texture and morphology of micrite microtexture are classified into six classes. Among these six classes, rounded, subrounded, trigonal, rhombic (micro-sub)-polyhedral micrite are representing porous micrite particles, whereas fitted bounded subhedral, and fitted fused anhedral are interpreted as tight micrite particles. Furthermore, five micropores classes are introduced based on the size of these particles. The empirical porosity-permeability relationship is affected by the presence of microporosity and its influences the assessment of ultimate recovery of hydrocarbons in Central Luconia, offshore Sarawak, Malaysia. Keywords: Quantification, Grain types, Porosity, Microporosity, Micrite particles, Central Luconi

Diffraction Enhancement Through Pre-Image Processing: Applications to Field Data, Sarawak Basin, East Malaysia

The future exploration plans of the industry is to find a small-scale reservoir for possible economic hydrocarbon reserves. These reserves could be illuminated by the super-resolution of full seismic data, including fractured zones, pinch-outs, channel edges, small-scale faults, reflector unconformities, salt flanks, karst, caves and fluid fronts, which are generally known as small scattering objects. However, an imaging approach that includes the diffraction event individually and images it constitutes a new approach for the industry; it is known as diffraction imaging. This paper documents results of a seismic processing procedure conducted to enhance diffractions in Sarawak Basin, using datasets from the Malaysian Basin to which no diffraction processing has been applied. We observed that the diffraction amplitude achieves maximum value when the detector is positioned vertically above the end point of the reflector, but drops off with increasing offset-distance from the point. Furthermore, the rate of attenuation of the diffracted wave energy is greater than that of the normal reflected wave energy in the same medium. In addition, the results indicate that the near offset and far angle stack data provide better diffraction events. In the other hand far offset and near angle stack provides the poor diffraction response. These results were revealed by angle-stacking of near-, mid-, and far-offsets data (4.5, 22.5 and 31.5 degrees) that was conducted to study amplitude and phase change of the diffraction curve. The final imaged data provides better faults definition in the carbonate field data

Inspiration for Seismic Diffraction Modelling, Separation, and Velocity in Depth Imaging

Fractured imaging is an important target for oil and gas exploration, as these images are heterogeneous and have contain low-impedance contrast, which indicate the complexity in a geological structure. These small-scale discontinuities, such as fractures and faults, present themselves in seismic data in the form of diffracted waves. Generally, seismic data contain both reflected and diffracted events because of the physical phenomena in the subsurface and due to the recording system. Seismic diffractions are produced once the acoustic impedance contrast appears, including faults, fractures, channels, rough edges of structures, and karst sections. In this study, a double square root (DSR) equation is used for modeling of the diffraction hyperbola with different velocities and depths of point diffraction to elaborate the diffraction hyperbolic pattern. Further, we study the diffraction separation methods and the effects of the velocity analysis methods (semblance vs. hybrid travel time) for velocity model building for imaging. As a proof of concept, we apply our research work on a steep dipping fault model, which demonstrates the possibility of separating seismic diffractions using dip frequency filtering (DFF) in the frequency–wavenumber (F-K) domain. The imaging is performed using two different velocity models, namely the semblance and hybrid travel time (HTT) analysis methods. The HTT method provides the optimum results for imaging of complex structures and imaging below shadow zones