Seismic Data Volume Research Articles

Prestack waveform inversion of three-dimensional seismic data — An example from the Rock Springs Uplift, Wyoming, USA

Applying seismic inversion to estimate subsurface elastic earth properties for reservoir characterization is a challenge in exploration seismology. In recent years, waveform-based seismic inversions have gained popularity, but due to high computational costs, their applications are limited, and amplitude-variation-with-offset/angle inversion is still the current state-of-the-art. We have developed a genetic-algorithm-based prestack seismic waveform inversion methodology. By parallelizing at multiple levels and assuming a locally 1D structure such that forward computation of wave equation synthetics is computationally efficient, this method is capable of inverting 3D prestack seismic data on parallel computers. Applying this inversion to a real prestack seismic data volume from the Rock Springs Uplift (RSU) located in Wyoming, USA, we determined that our method is capable of inverting the data in a reasonable runtime and producing much higher quality results than amplitude-variation-with-offset/angle inversion. Because the primary purpose for seismic data acquisition at the RSU was to characterize the subsurface for potential targets for carbon dioxide sequestration, we also identified and analyzed some potential primary and secondary storage formations and their associated sealing lithologies from our inversion results.

Time Slicing the Cooper Basin

An efficient and practical method of generating composite time slices using all available, non-confidential 3D seismic data recorded in the South Australian sector of the Cooper Basin has been developed. Twenty georeferenced tiff images of time slices between 1000 ms and 2900 ms at 100 ms intervals have been prepared and are intended to be made publicly available through the Department of State Development SARIG website. 2D seismic data has also been used in this project in an attempt to ‘fill in’ some of the gaps between 3D datasets. Forty eight 3D and 5076 2D seg-y data files were utilised in this project. All 3D and 2D segy files were scaled to normalise amplitude levels for gridding and imaging. The ability to time slice 3D volumes of seismic seg-y data is a basic method employed in seismic interpretation. This method is usually applied to a single survey as commonly used software packages are not designed to view and analyse multiple 3D surveys at the same time or such functionality is not yet well implemented. For large scale regional interpretation, such constraint limits interpreting potential, especially in terms of basin wide correlation of main structural features. Whilst the methodology developed in this project retains the quality and resolution inherent in the variety of surveys used, it provides a cost effective method of generating basin wide time slice images, compared to costly reprocessing required in merging of 3D data sets into one 3D volume. The time slice data suite prepared complements other value-added regional datasets prepared by the Department of State Development to stimulate petroleum exploration in South Australia.

Cryoseismology

AbstractThe last decade witnessed an explosion in yearly number of publications on passive glacier seismology. The seismic signals from a wide range of glacier‐related processes fill a broad band of frequencies (from 10−3to 102 Hz) and moment magnitudes (fromM–3 toM7) providing a fresh and unprecedented view on fundamental processes in the cryosphere. New insights into basal motion, iceberg calving, glacier, iceberg, and sea ice dynamics, and precursory signs of unstable glaciers and ice structural changes are being discovered with seismological techniques. These observations offer an invaluable foundation for understanding ongoing environmental changes and for future monitoring of ice bodies worldwide. In this review we discuss seismic sources in the cryosphere as well as research challenges for the near future. The field of glacier seismology is evolving so rapidly that some parts of this review will likely soon be outdated. Nevertheless, given an overwhelming number of recent publications and rapidly growing seismic data volumes provided by modern seismic installations in polar and mountain regions, this introduction to cryosphere seismicity aims to serve as a timely and comprehensive reference for glaciologists and seismologists.

Seismic volume visualization at your fingertips

Volume visualization has become an essential tool for geoscientists in the oil and gas industry. Using this technology, geosci¬entists interact with volumes of seismic data to locate, isolate, and understand the spatial relationships of important geologic features in a context-rich 3D environment. In the past decade, the continued evolution in hardware and software of mobile devices is putting desktop capabilities in everyone’s palms. As such, mobile devices are becoming more useful as an interactive 3D visualization platform. In this paper, I evaluate and demonstrate the effectiveness of mobile devices to perform seismic vol¬ume visualization. Sub-volumes of data containing different stratigraphic depositional environments were first extracted from three 3D seismic surveys. The rendered 3D graphics were examined in detail. The results illustrate that volume visualization on mobile devices enables the exploration of detailed variations in the seismic response. Therefore, it facilitates the interpretation of the imaged geologic features. I anticipate that mobile devices will revolutionize the interpretation of seismic data volumes by allowing geoscientists to visually examine their data anywhere and at any time.

Understanding the seismic disorder attribute and its applications

While reflections associated with conformal sedimentary layers are usually coherent and continuous, other reflections, such as mass-transport complexes, karst collapse, and salt, may appear to be quite chaotic, without any specific orientation. We also may see chaotic events that have little to do with the target geology but rather are artifacts due to variations in the overburden and surface or budget limitations resulting in a suboptimum acquisition program. While some of these artifact issues can be handled at the time of processing, a certain level of randomness remains in most seismic data volumes. Geologic features of interpretational interest, such as fault damage zones, unconformities, and gas chimneys, often have randomness associated with them. The published work on randomness describes techniques such as cross correlation, which measures randomness associated with noise, the chaos attribute based on eigen-analysis of gradient covariance, and the seismic disorder attribute based on application of second derivative operators in the three axial directions in a 3D seismic volume. We apply the seismic disorder attribute to two different data sets and find that it is a useful attribute for assessing the signal-to-noise ratio and data quality, in addition to helping delineate damage zones associated with large faults and the interior of salt dome structures.

3D seismic edge detection using magic squares and cubes

Edge detection is a category of geometric seismic attributes that has the capability to delineate vital information from seismic reflection data that can be used to aid qualitative and quantitative interpretation. We have evaluated a new method for geologic interpretation based on templates derived from magic squares and cubes. These are discrete differential operators that approximately calculate the spatial derivative of seismic amplitude through 2D and 3D convolution to locate edges and/or geologic features in seismic data. The new operator benefits from multidirectional scanning leading to efficient detection of different edge locations and their respective orientations. We have tested the new operators against the commonly used Sobel filter using two 3D seismic data volumes. Results of the [Formula: see text] magic cube operators provided better definition of seismic features than the [Formula: see text] magic cube operators. The overall results compared favorably with the Sobel operator, which suggests that the method can serve as a complementary tool to other existing seismic attributes.

A comparative study of 3D FZI and electrofacies modeling using seismic attribute analysis and neural network technique: A case study of Cheshmeh-Khosh Oil field in Iran

Abstract Electrofacies are used to determine reservoir rock properties, especially permeability, to simulate fluid flow in porous media. These are determined based on classification of similar logs among different groups of logging data. Data classification is accomplished by different statistical analysis such as principal component analysis, cluster analysis and differential analysis. The aim of this study is to predict 3D FZI (flow zone index) and Electrofacies (EFACT) volumes from a large volume of 3D seismic data. This study is divided into two parts. In the first part of the study, in order to make the EFACT model, nuclear magnetic resonance (NMR) log parameters were employed for developing an Electrofacies diagram based on pore size distribution and porosity variations. Then, a graph-based clustering method, known as multi resolution graph-based clustering (MRGC), was employed to classify and obtain the optimum number of Electrofacies. Seismic attribute analysis was then applied to model each relaxation group in order to build the initial 3D model which was used to reach the final model by applying Probabilistic Neural Network (PNN). In the second part of the study, the FZI 3D model was created by multi attributes technique. Then, this model was improved by three different artificial intelligence systems including PNN, multilayer feed-forward network (MLFN) and radial basis function network (RBFN). Finally, models of FZI and EFACT were compared. Results obtained from this study revealed that the two models are in good agreement and PNN method is successful in modeling FZI and EFACT from 3D seismic data for which no Stoneley data or NMR log data are available. Moreover, they may be used to detect hydrocarbon-bearing zones and locate the exact place for producing wells for the future development plans. In addition, the result provides a geologically realistic spatial FZI and reservoir facies distribution which helps to understand the subsurface reservoirs heterogeneities in the study area.

Utilization of multiple scattering: the next big step forward in seismic imaging

Surface removal and internal multiple removal are explained by recursively separating the primary and multiple responses at each depth level with the aid of wavefield prediction error filtering. This causal removal process is referred to as “data linearization.” The linearized output (primaries only) is suitable for linear migration algorithms. Next, a summary is given on the migration of full wavefields (primaries multiples) by using the concept of secondary sources in each subsurface gridpoint. These secondary sources are two-way and contain the gridpoint reflection and the gridpoint transmission properties. In full wavefield migration, a local inversion process replaces the traditional linear imaging conditions. Finally, Marchenko redatuming is explained by iteratively separating the full wavefield response from above a new datum and the full wavefield response from below a new datum. The redatuming output is available for linear migration (Marchenko imaging) or, even better, for full wavefield migration. Linear migration, full wavefield migration, and Marchenko imaging are compared with each other. The principal conclusion of this essay is that multiples should not be removed, but they should be utilized, yielding two major advantages: (i) illumination is enhanced, particularly in the situation of low signal-to-noise primaries; and (ii) both the upper side and the lower side of reflectors are imaged. It is also concluded that multiple scattering algorithms are more transparent if they are formulated in a recursive depth manner. In addition to transparency, a recursive depth algorithm has the flexibility to enrich the imaging process by inserting prior geological knowledge or by removing numerical artefacts at each depth level. Finally, it is concluded that nonlinear migration algorithms must have a closed-loop architecture to allow successful imaging of incomplete seismic data volumes (reality of field data).

Pitfalls in seismic processing: An application of seismic modeling to investigate acquisition footprint

The term acquisition footprint is commonly used to define patterns in seismic time and horizon slices that are closely correlated to the acquisition geometry. Seismic attributes often exacerbate footprint artifacts and may pose pitfalls to the less experienced interpreter. Although removal of the acquisition footprint is the focus of considerable research, the sources of such artifact acquisition footprint are less commonly discussed or illustrated. Based on real data examples, we have hypothesized possible causes of footprint occurrence and created them through synthetic prestack modeling. Then, we processed these models using the same workflows used for the real data. Computation of geometric attributes from the migrated synthetics found the same footprint artifacts as the real data. These models showed that acquisition footprint could be caused by residual ground roll, inaccurate velocities, and far-offset migration stretch. With this understanding, we have examined the real seismic data volume and found that the key cause of acquisition footprint was inaccurate velocity analysis.

Automatic detection of alpine rockslides in continuous seismic data using hidden Markov models

AbstractData from continuously recording permanent seismic networks can contain information about rockslide occurrence and timing complementary to eyewitness observations and thus aid in construction of robust event catalogs. However, detecting infrequent rockslide signals within large volumes of continuous seismic waveform data remains challenging and often requires demanding manual intervention. We adapted an automatic classification method using hidden Markov models to detect rockslide signals in seismic data from two stations in central Switzerland. We first processed 21 known rockslides, with event volumes spanning 3 orders of magnitude and station event distances varying by 1 order of magnitude, which resulted in 13 and 19 successfully classified events at the two stations. Retraining the models to incorporate seismic noise from the day of the event improved the respective results to 16 and 19 successful classifications. The missed events generally had low signal‐to‐noise ratio and small to medium volumes. We then processed nearly 14 years of continuous seismic data from the same two stations to detect previously unknown events. After postprocessing, we classified 30 new events as rockslides, of which we could verify three through independent observation. In particular, the largest new event, with estimated volume of 500,000 m3, was not generally known within the Swiss landslide community, highlighting the importance of regional seismic data analysis even in densely populated mountainous regions. Our method can be easily implemented as part of existing earthquake monitoring systems, and with an average event detection rate of about two per month, manual verification would not significantly increase operational workload.

Characterization of gas hydrate distribution using conventional 3D seismic data in the Pearl River Mouth Basin, South China Sea

A new 3D seismic reflection data volume acquired in 2012 has allowed for the detailed mapping and characterization of gas hydrate distribution in the Pearl River Mouth Basin in the South China Sea. Previous studies of core and logging data showed that gas hydrate occurrence at high concentrations is controlled by the presence of relatively coarse-grained sediment and the upward migration of thermogenic gas from the deeper sediment section into the overlying gas hydrate stability zone (BGHSZ); however, the spatial distribution of the gas hydrate remains poorly defined. We used a constrained sparse spike inversion technique to generate acoustic-impedance images of the hydrate-bearing sedimentary section from the newly acquired 3D seismic data volume. High-amplitude reflections just above the bottom-simulating reflectors (BSRs) were interpreted to be associated with the accumulation of gas hydrate with elevated saturations. Enhanced seismic reflections below the BSRs were interpreted to indicate the presence of free gas. The base of the BGHSZ was established using the occurrence of BSRs. In areas absent of well-developed BSRs, the BGHSZ was calculated from a model using the inverted P-wave velocity and subsurface temperature data. Seismic attributes were also extracted along the BGHSZ that indicate variations reservoir properties and inferred hydrocarbon accumulations at each site. Gas hydrate saturations estimated from the inversion of acoustic impedance of conventional 3D seismic data, along with well-log-derived rock-physics models were also used to estimate gas hydrate saturations. Our analysis determined that the gas hydrate petroleum system varies significantly across the Pearl River Mouth Basin and that variability in sedimentary properties as a product of depositional processes and the upward migration of gas from deeper thermogenic sources control the distribution of gas hydrates in this basin.

Predictive coherence

Detection and interpretation of fault systems and stratigraphic features and the relationship between them are crucial for seismic interpretation and reservoir characterization. To provide better interpretation insight and to be able to extract overlooked features out of seismic data volumes, we have developed a new attribute that detects faults and other discontinuities while handling local nonstationary variations across them. First, we used predictive painting to form a structural prediction of seismic events from neighboring traces (left and right neighboring traces in 2D and neighboring traces in all directions around a reference trace in 3D) according to the local structural slopes. Then, we computed prediction residuals by subtracting each prediction from the original data, and we found the smallest prediction-error interval for each point that best represented discontinuity information at that point. The extracted fault information changed with location (spatially and temporally), and it was nonstationary. Conventional coherence measures operate on a spatial window of neighboring traces and a temporal (vertical) analysis window of samples above and below the analysis point, and they can hardly cope with nonstationarity in fault information. In contrast, in our method, neither temporal nor spatial windows were involved in coherence computation, which allowed us to honor nonstationary changes of fault information and to achieve high resolution in the vertical and lateral directions. To assess the performance of the proposed attribute, we compared it with the conventional coherence attribute over the same data set. The comparison demonstrated the effectiveness of discontinuity detection using predictive coherence and showed its value in extracting additional information from seismic data.

A comparison of classification techniques for seismic facies recognition

During the past decade, the size of 3D seismic data volumes and the number of seismic attributes have increased to the extent that it is difficult, if not impossible, for interpreters to examine every seismic line and time slice. To address this problem, several seismic facies classification algorithms including [Formula: see text]-means, self-organizing maps, generative topographic mapping, support vector machines, Gaussian mixture models, and artificial neural networks have been successfully used to extract features of geologic interest from multiple volumes. Although well documented in the literature, the terminology and complexity of these algorithms may bewilder the average seismic interpreter, and few papers have applied these competing methods to the same data volume. We have reviewed six commonly used algorithms and applied them to a single 3D seismic data volume acquired over the Canterbury Basin, offshore New Zealand, where one of the main objectives was to differentiate the architectural elements of a turbidite system. Not surprisingly, the most important parameter in this analysis was the choice of the correct input attributes, which in turn depended on careful pattern recognition by the interpreter. We found that supervised learning methods provided accurate estimates of the desired seismic facies, whereas unsupervised learning methods also highlighted features that might otherwise be overlooked.

Noise-robust detection and tracking of salt domes in postmigrated volumes using texture, tensors, and subspace learning

The identification of salt-dome boundaries in migrated seismic data volumes is important for locating petroleum reservoirs. The presence of noise in the data makes computer-aided salt-dome interpretation even more challenging. We have developed noise-robust algorithms that could label boundaries of salt domes effectively and efficiently. Our research is twofold. First, we used a texture-based gradient to accomplish salt-dome detection. We found that by using a dissimilarity measure based on the 2D discrete Fourier transform, the algorithm was capable of efficiently detecting salt-dome boundaries with accuracy. At the same time, our analysis determined that the proposed algorithm was robust to noise. Once the detection is performed for an initial 2D seismic section, we track the initial boundaries through the data volume to accomplish an efficient labeling process by avoiding the parameter tuning that would have been necessary if detection had been performed for every seismic section. The tracking process involves a tensor-based subspace learning process, in which we built texture tensors using patches from different seismic sections. To accommodate noise components with various levels in a texture tensor, we used noise-adjusted principal component analysis, so that principal components corresponding to greater signal-to-noise-ratio values might be selected for tracking. We validated our detection and tracking algorithms through experiments using seismic data sets acquired from the Netherlands offshore F3 block in the North Sea with very encouraging results.

Role of rift transection and punctuated subsidence in the development of the North Falkland Basin

The results of well-constrained seismic interpretation and new mapping of three-dimensional (3D) seismic data volumes demonstrates that the North Falkland Basin consists of two superimposed failed rift basins: a Late Jurassic NW–SE-striking Southern Rift Basin (SRB); and an Early Cretaceous north–south-striking Northern Rift Basin (NRB). The SRB is best developed in coastal waters of the Falkland Islands, where it comprises a series of extensional sub-basins that are transected by faults belonging to the more substantive NRB. Regional interpretation demonstrates that the NRB consists of a southward-tapering, asymmetric extensional basin containing a thick (in excess of 10 km) sequence of sediments. Its syn-rift subsidence history was controlled by a major west-dipping normal fault array comprising several fault segment precursors, which, together with corresponding antithetic faults, effectively subdivides the hanging wall into a series of sub-basins throughout its length. The NRB initially developed in a fluvial and later lacustrine environment before becoming predominantly marine in the Tertiary. A prograding delta system filled the basin from the north during the early post-rift phase. Contemporaneously, sediment was shed off the segmented basin-bounding fault via long-established feeder drainage systems through breached relay ramps into the depocentre. The resultant sediment dispersal led to deposition of numerous lacustrine turbidites that created the Sea Lion fans and its affiliates, the location of which mimics, and is thus interpreted to have been controlled by, the underlying syn-rift sub-basins. Post-rift subsidence was punctuated by an important, but short-lived, phase of basin inversion during the Aptian that created a large, broad and gentle north–south-striking anticline that runs along the central basin axis. Whilst the episode of basin inversion arrested subsidence, it did not inhibit petroleum prospectivity. The syn-rift lacustrine source intervals did subsequently pass through the critical moment in the Cretaceous leading to hydrocarbon maturation and the migration of waxy oil, a process that continues to the present day.

Slicing and dicing HR seismic acquisition: Varied approaches to delivery of high-resolution 3D seismic data volumes for drilling-hazard studies

Experiences are described in delivering high-resolution 3D (HR3D) volumes to support the definition of drilling hazards for exploration and development drilling in different geologic settings around the world using differing levels of acquisition and processing intensity. The robustness of the HR3D approach delivers high-resolution volumetric imaging for the study of potential drilling hazards. Through acquisition trials and processing simulations, starting with a single-streamer, single-source approach to acquisition of HR3D, data can be delivered at equivalent effort to standard HR2D approaches but as a volume that allows all the advantages of 3D spatial analysis to be applied. Increasing the acquisition intensity increases the quality of the final processed volume and allows more advanced analysis approaches to be applied to the data. Use of multistreamer and multisource approaches offers the opportunity to improve acquisition efficiency with careful consideration of spread designs to maintain high frequencies without introducing directivity effects into the final data. In cases in which there is a need for HR data to support drilling-hazard or development studies, there is now no reason to not always acquire HR3D data. Similarly, in the processing of HR3D data, the full power of modern processing approaches, up to and including prestack depth migration, can be applied to provide further improvements in imaging in complex geologic settings to the benefit of drilling-hazard identification and ongoing improvements to drilling safety and operational integrity.

Pitfall experiences when interpreting complex structure with low-quality seismic images

Structural interpretation of seismic data presents numerous opportunities for encountering interpretational pitfalls, particularly when a seismic image does not have an appropriate signal-to-noise ratio (S/N), or when a subsurface structure is unexpectedly complex. When both conditions exist — low S/N data and severe structural deformation — interpretation pitfalls are almost guaranteed. We analyzed an interpretation done 20 years ago that had to deal with poor seismic data quality and extreme distortion of strata. The lessons learned still apply today. Two things helped the interpretation team develop a viable structural model of the prospect. First, existing industry-accepted formation tops assigned to regional wells were rejected and new log interpretations were done to detect evidence of repeated sections and overturned strata. Second, the frequency content of the 3D seismic data volume was restricted to only the first octave of its seismic spectrum to create better evidence of fault geometries. A logical and workable structural interpretation resulted when these two action steps were taken. To the knowledge of our interpretation team, neither of these approaches had been attempted in the area at the time of this work (early 1990s). We found two pitfalls that may be encountered by other interpreters. The first pitfall was the hazard of accepting long-standing, industry-accepted definitions of the positions of formation tops on well logs. This nonquestioning acceptance of certain log signatures as indications of targeted formation tops led to a serious misinterpretation in our study. The second pitfall was the prevailing passion by geophysicists to create seismic data volumes that have the widest possible frequency spectrum. This interpretation effort showed that the opposite strategy was better at this site and for our data conditions; i.e., it was better to filter seismic images so that they contained only the lowest octave of frequencies in the seismic spectrum.

Techniques and best practices in multiattribute display

All color monitors display images by mixing red, green, and blue (RGB) components. These RGB components can be defined mathematically in terms of hue, lightness, and saturation (HLS) components. A fourth alpha-blending (also called opacity) component provides a means to corender multiple images. Most, but not all, modern commercial interpretation workstation software vendors provide multiattribute display tools using an opacity model. A smaller subset of vendors provide tools to interactively display two or three attributes using HLS, CMY, and RGB color models. I evaluated a technique (or trick) to simulate the HLS color model using monochromatic color bars and only opacity. This same trick only approximates true color blending of RGB or CMY components. There are three basic objectives in choosing which attributes to display together. The first objective is to understand the correlation of one attribute to another, and most commonly, of a given attribute to the original seismic amplitude data. The second objective is to visualize the confidence or relevance of a given attribute by modulating it with a second attribute. The third objective is to provide a more integrated image of the seismic data volume by choosing attributes that are mathematically independent but correlated through the underlying geology. I developed the interpretation value of the HLS display technique on a 3D data volume acquired over the Central Basin Platform of west Texas exhibiting faults, fractures, folds, channels, pinch outs, and karst features. To be a useful “technique,” I need to demonstrate these workflows within a specific package. Although I implemented the workflow in Petrel 2014, similar images can be generated using any software with flexible opacity capabilities. I also developed a short list of attribute combinations that are particularly amenable to corendering in HLS.

Pitfalls and limitations in seismic attribute interpretation of tectonic features

Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence (or variance) cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Seismic attributes are at their best in extracting subtle and easy to overlook features on high-quality seismic data. However, seismic attributes can also exacerbate otherwise subtle effects such as acquisition footprint and velocity pull-up/push-down, as well as small processing and velocity errors in seismic imaging. As a result, the chance that an interpreter will suffer a pitfall is inversely proportional to his or her experience. Interpreters with a history of making conventional maps from vertical seismic sections will have previously encountered problems associated with acquisition, processing, and imaging. Because they know that attributes are a direct measure of the seismic amplitude data, they are not surprised that such attributes “accurately” represent these familiar errors. Less experienced interpreters may encounter these errors for the first time. Regardless of their level of experience, all interpreters are faced with increasingly larger seismic data volumes in which seismic attributes become valuable tools that aid in mapping and communicating geologic features of interest to their colleagues. In terms of attributes, structural pitfalls fall into two general categories: false structures due to seismic noise and processing errors including velocity pull-up/push-down due to lateral variations in the overburden and errors made in attribute computation by not accounting for structural dip. We evaluate these errors using 3D data volumes and find areas where present-day attributes do not provide the images we want.

Classification of reservoir sand-facies distribution using multiattribute Probabilistic Neural Network transform in “Bigola” field, Niger Delta, Nigeria

This study estimated reservoir properties, classified the reservoir sand-facies distribution and identified potential hydrocarbon pay zones. This was with a view to optimizing placements of wells in “Bigola” Field. Conventional interpretation of seismic and well datasets was carried out to provide the sub-surface structures and general stratigraphy of the study area. The 3-D seismic data volume along with well logs were analysed using multiattribute Probabilistic Neural Network (PNN) transform to generate target reservoir properties (V Shale , Porosity shale and Resistivity) and consequently horizon based maps. The generated structure maps of target horizons TMTS4 and TMTS5 showed closures at the north central and north eastern parts. The generated reservoir property maps showed the distribution of reservoir sand-facies in the wells and inter-well regions. Average porosity values ranged from 22-30%, V Shale values ranged between 8 and 12 % and resistivity values ranged between 112 and 199ohm-m for hydrocarbon reservoir sands. The study concluded that the reservoir sand-facies of the north eastern and north central parts of the study area were more indicative of hydrocarbon presence than those of other parts. Keywords : Porosity, Resistivity, V shale , Multi-Attribute, Neural Networks, Well and Niger Delta.