New-Age Kolmogorov Full-Function Neural Network KNN Offers High-Fidelity Reservoir Predictions via Estimation of Core, Well Log, Map and Seismic Properties

Instead of relying on analytical functions to approximate property relationships, this innovative hybrid neural network technique offers highly adaptive, full-function (!) predictions that can be applied to different subsurface data types ranging from (1.) core-to-log prediction (permeability), (2.) multivariate property maps (oil-saturated thickness maps), and, (3.) petrophysical properties from 3D seismic data (i.e., hydrocarbon pore volume, instantaneous velocity). For each scenario a separate example is shown. In case study 1, core measurements are used as the target array and well log data serve training. To analyze the uncertainty of predicted estimates, a second oilfield case study applies 100 iterations of log data from 350 wells to obtain P10-P50-P90 probabilities by randomly removing 40% (140 wells) for validation purposes. In a third case study elastic logs and a low-frequency model are used to predict seismic properties. KNN generates a high level of freedom operator with only one (or more) hidden layer(s). Iterative parameterization precludes that high correlation coefficients arise from overtraining. Because the key advantage of the Kolmogorov neural network (KNN) is to permit non-linear, full-function approximations of reservoir properties, the KNN approach provides a higher-fidelity solution in comparison to other linear or non-linear neural net regressions. KNN offers a fast-track alternative to classic reservoir property predictions from model-based seismic inversions by combining (a) Kolmogorov's Superposition Theorem and (b) principles of genetic inversion (Darwin's "Survival of the fittest") together with Tikhonov regularization and gradient theory. In practice, this is accomplished by minimizing an objective function on multiple and simultaneous outputs from full-function (via look-up table) Kolmogorov neural network runs. All case studies produce high correlations between actual and predicted properties when compared to other stochastic or deterministic inversions. For instance, in the log to seismic prediction better (simulated) resolution of neural network results can be discerned compared to traditional inversion results. Moreover, all blind tests match the overall shape of prominent log curve deflections with a higher degree of fidelity than from inversion. An important fringe benefit of KNN application is the observed increase in seismic resolution that by comparison falls between the seismic resolution of a model-based inversion and the simulated resolution from seismic stochastic inversion.

Connecting the Dots between Geology and Seismic to Mitigate Drilling Risks: Mapping & Characterization of the High Pressure High Temperature Gotnia Formation in Kuwait

As Kuwait focuses on developing the deep Jurassic reservoirs, the Gotnia Formation presents significant drilling challenges. It is the regional seal, consisting of alternating Salt and Anhydrite cycles, with over-pressured carbonate streaks, which are also targets for future exploration. The objective of this study was to unravel the Gotnia architecture, through detailed mapping of the intermediate cycles, mitigating drilling risks and characterizing the carbonate reservoirs. A combination of noise attenuation, bandwidth extension and seismic adaptive wavelet processing (SAWP)) was applied on the seismic data, to improve the signal-to-noise ratio of the seismic data between 50Hz to 70Hz and therefore reveal the Anhydrite cycles, which house the carbonate streaks. The Salt-Anhydrite cycles were correlated, using Triple Combo and Elastic logs, in seventy-six wells, and spatially interpreted on the band-limited P-impedance volume, generated through pre-stack inversion. Pinched out cycles were identified by integrating mud logs with seismic data and depositional trends. Pre-stack stochastic inversion was performed to map the thin carbonate streaks and characterize the carbonate reservoirs. The improved seismic resolution resulted in superior results compared to the legacy cube and aided in enhancing the reflector continuity of Salt-Anhydrite cycles. In corroboration with the well data, three cycles of alternating salt and anhydrite, with varying thickness, were mapped. These cycles showed a distinctive impedance contrast and were noticeably more visible on the P-impedance volume, compared to the seismic amplitude volume. The second Anhydrite cycle was missing in some wells and the lateral extension of the pinch-outs was interpreted and validated based on the P-impedance volume. As the carbonate streaks were beyond the seismic resolution, they were not visible on the Deterministic P-impedance. The amount of thin carbonate streaks within the Anhydrite cycles could be qualitatively assessed based on the impedance values of the entire zone. Areas, within the zone, with a higher number of and more porous carbonate streaks displayed lowering of the overall impedance values in the Anhydrite zones, and could pose drilling risks. This information was used to guide the pre-stack stochastic inversion to populate the thin carbonate streaks and generate a high-resolution facies volume, through Bayesian Classification. Through this study, the expected cycles and over-pressured carbonate layers in the Gotnia formation were predicted, which can be used to plan and manage the drilling risks and reduce operational costs. This study presents an integrated and iterative approach to interpretation, where the well log analysis, seismic inversion and horizon interpretation were done in parallel, to develop a better understanding of the sub-surface. This workflow will be especially useful for interpretation of over-pressured overburden zones or cap rocks, where the available log data can be limited.

Creation of Geological 3D-Model of Komyshnianske Field Based on the Sequence Stratigraphy Principles

Currently, the sequence-stratigraphic section dismemberment is only being implemented in Ukraine, so this article is highly relevant. The authors created geological 3D model of Komyshnianske gas condensate field based on sequence-stratigraphic section dismemberment for the first time at this area. This approach is effective for the following conditions:-insufficient field geological study;-thickness of productive horizons does not reach the seismic resolution boundaries;-no significant difference in impedance values on reflection horizons. The selected technique includes the following stages:-field geological study, facies analysis (integration of well geophysical complexes, cores);-deduction and correlation of sequence boundaries;-construction of discrete log, which corresponds to specific sequences distribution;-conducting seismic interpretation of the 3D seismic survey study of research area;-construction of a structural framework with the involvement of correlated sequences boundaries;-comparison of volume seismic attributes with selected sequences distribution. A geological 3D model of Komyshnianske gas condensate field was created based on sequence-stratigraphic principles. During the research, a geological structure of field was analyzed, the separated conditions of sedimentation (sequences) were deducted and interpreted. During the seismic interpretation of 3D seismic survey of study area, local features of wave field were identified, their reflection in the core material was found and linked to the concept of changing sedimentation conditions. With a general understanding of the material transportation and accommodation direction, used method allows to qualitatively outline the distribution boundaries of sedimentation certain conditions and predict their development outside the study area. Construction of facies discrete log and their distribution in the seismic field allows grouping thin bed layers of collectors to reach the seismic resolution and use them to predict the distribution of facies associated with changes in the rocks reservoir properties (tracking beach facies of deltas/avandeltas, sloping sediments, etc.). The constructed model could be used as a trend for reservoir distribution at the stage of construction of static geological model. Involvement of sequence-stratigraphy technique is new approach to sedimentation conditions study within Dnipro-Donetsk depression (DDD) areas. The paper shows that provided methodology gives:-improved geological understanding of field through sedimentation analysis and facies logging;-trends for reservoir properties distribution with the involvement of construction facies volumes;-proposals for further field E&D. The general provisions under conditions of geological materials sufficient base can be applied to other DDD areas, especially in pre-border zones. Involvement of sequence-stratigraphy technique is new approach for sedimentation conditions study within Dnipro-Donetsk depression (DDD) area. On the example of Komyshnianske gas condensate field, the article shows that provided methodology gives:-improved geological understanding of field through sedimentation analysis and facies logging;-trends for reservoir properties propagation with the involvement of seismic volume studies;-propositions for further field Exploration & Development.

Targeting and Developing the Remaining Pay in an Ageing Field: the Ovhor Field Experience

Understanding the complexity in the distribution of hydrocarbon in a simple structure with flow baffles and connectivity issues is critical in targeting and developing the remaining pay in a mature asset. Subtle facies changes (heterogeneity) can have drastic impact on reservoir fluids movement, and this can be crucial to identifying sweet spots in mature fields. This study evaluated selected reservoirs in Ovhor Field, Niger Delta, Nigeria with the objective of optimising production from the field by targeting undeveloped oil reserves or bypassed pay and gaining an improved understanding of the selected reservoirs to increase the company's reserves limits. The task at the Ovhor field, is complicated by poor stratigraphic seismic resolution over the field. 3-D geological (Sedimentology and stratigraphy) interpretation, Quantitative interpretation results and proper understanding of production data have been used in recognizing flow baffles and undeveloped compartments in the field. The full field 3-D model was constructed in such a way as to capture heterogeneities and the various compartments in the field. This was crucial to aid the simulation of fluid flow in the field for proper history matching, future production, prediction and design of well trajectories to adequately target undeveloped oil in the field. Reservoir property models (Porosity, Permeability and Net-To-Gross) were constructed by biasing log interpreted properties to a defined environment of deposition model whose interpretation captured the heterogeneities expected in the studied reservoirs. At least, two scenarios were modelled for the studied reservoirs to capture the range of uncertainties. This integrated approach led to the identification of bypassed oil in some areas of the selected reservoirs and an improved understanding of the studied reservoirs. Dynamic simulation and production forecast on the 4 reservoirs gave an undeveloped reserve of about 3.82 MMstb from two (2) identified oil restoration activities. These activities included side-tracking and re-perforation of existing wells. New wells have been drilled to test the results of our studies and the results confirmed our findings.

Use of spectral decomposition technique for mapping geologic features of ‘Reigh’ field, Onshore Niger Delta

Spectral Decomposition Technique based on Short-Window Discrete Fourier Transform (SWDFT) was applied to threedimensional (3D) seismic data obtained from ‘Reigh’ field, onshore Niger Delta with a view to enhancing stratigraphic interpretation for geological features which are beyond seismic resolution. Two sands units from the study area were studied to produce spectrally decomposedsurfaces. The result of the study revealed thin bed layer at the centre of the field on sand unit ‘A’. Sand-filled meandering channel wasdetected and highlighted in the northern part of sand unit ‘B’ based on Red-Green-Blue frequency modulation of spectral decomposition. The study has enhanced geologic understanding of the field by improving thin bed resolution, highlighting geologic features and displaying bed thickness variation of studied sand units in the study area. Keywords: geologic features, Niger Delta, seismic data, spectral decomposition

Revisit Seismic Attenuation Attributes: Influences of the Spectral Balancing Operation on Seismic Attenuation Analysis

Seismic attenuation analysis is important for seismic processing and quantitative interpretation. Nevertheless, the classic quality factor estimation methods make certain assumptions that may be invalid for a given geologic target and seismic volume. For this reason, seismic attenuation attribute analysis, which reduces some of the theoretical assumptions, can serve as a practical alternative in apparent attenuation characterization. Unfortunately, most of the published literature defines seismic attenuation attributes based on a specific source wavelet assumption, such as the Ricker wavelet, rather than wavelets that exhibit a relatively flat spectrum produced by modern data processing workflows. One of the most common processing steps is to spectrally balance the data either explicitly in the frequency domain, or implicitly through wavelet shaping deconvolution. If the post-stack seismic data have gone through the spectral balancing/whitening to improve the seismic resolution, the wavelet would exhibit a flat spectrum instead of a Ricker or Gaussian shape. We address the influence of the spectral balancing on seismic attenuation analysis. Our mathematical analysis shows that attenuation attributes are still effective for the post-stack seismic data after certain types of spectral balancing. More importantly, this analysis explains why seismic attenuation attributes work for real seismic applications with common seismic processing procedures. Synthetic and field data examples validate our conclusions.

FLUVIAL RESERVOIR ARCHITECTURE INTERPRETATION BELOW THE SEISMIC RESOLUTION IN AN OFFSHORE OILFIELD

Reservoir discontinuity is a practical representation of reservoir heterogeneity, which leads to the non-uniformed flow of hydrocarbons during production and to the increase in the difficulties of producing the remaining oil in clastic reservoirs. A feasible solution is to detect the internal bounding surfaces of the reservoir based on infill drilling data. However, for offshore oilfields, reservoir discontinuity analysis will have to rely on seismic data due to their sparse well spacings. Moreover, from the interpretation of a fluvial reservoir system in Chinaapos;s Bohai Bay, it turns out that the thickness of the sandstone is usually smaller than the seismic tuning thickness. In order to interpret a fluvial reservoir architecture which is below the seismic resolution, we elaborated a hierarchy of the fluvial reservoir architectures and classified the compound sandstones as different architectural elements according to their sedimentary periods. Forward models were designed to analyze the seismic responses of the architectures. The results demonstrate that amplitude-related seismic attributes could be sensitive to different reservoir architectures below the seismic resolution. The amplitude-related seismic attributes can be extracted through a time window guided by the horizons. The horizon-based attributes can be treated as digital images which may contain the information of compound sandstones with hidden discontinuity boundaries. We propose a direction-adaptive mathematical morphology gradient algorithm that can detect the boundaries of reservoir architectures in different directions on horizon-based seismic attributes. The application to field data demonstrates that the boundaries detected by the proposed algorithm have a good consistency with well logs. This method could enhance our capability to visualize and understand the complexity of reservoir heterogeneity.