Characterization of Rock Fabric and Fluid Fairway for Hydrocarbon Imprint and Lateral Prediction.

This work made use of computed data from well logs, with migrated seismic data, to evaluate rock fabric, reservoir fluid, and lithology of an unconsolidated alluvial fan deposit. Acoustic and elastic parameters amongst other logs were computed and used to characterize the subsurface reservoir. This was done to ascertain the possibility and success of well logs derived rock physics parameters in characterizing reservoirs. With the use of soft computing methods and stochastic algorithms, the objectives of this study were achieved. Results were presented in maps and model volumes. Lambda, Mu, Rho, and SP logs were the main inputs in the characterization based on both their individual potential and an integrated convolved potential. Filtered zones identified on cross-plot were applied to simulated volumes of LambdaRho and MuRho, gave good account of its ability to discriminate rock and fluid distribution. RGB visualization tool applied to the models gave a volume that was used to condition litho-units simulation with commendable results

Characterizing Geometrical Anisotropy of Petrophysical properties in the middle Shahejie formation, Liaohe Depression, China.

Knowledge of reservoir body lateral extent is important information for estimation of hydrocarbon initially in place and the recoverable quantity. This study reports a stepwise approach to evaluate geometrical anisotropy of the rapidly changing alluvial fan Shahejie formation of Eocene age. This is towards understanding reservoir geometry of the deposit beneath the flank of Bohai bay, Northern China. Computation of Sand net to gross (Volume of shale), porosity and permeability was done on well logs as an initial analytical step, followed by computation of sample variograms, data transformation and property modeling. Computation of semivariance was based on first geometrical anisotropy for autocorrelation by finding major and minor directions of data consistency. Autocorrelation of data with distance of location made upscaled data useful for stochastic simulation. Minor data direction is almost perpendicular to the major direction with the bandwidth of not less than 4000. In the vertical direction, average bandwidth is 50. Porosity for the modeled zone is consistent with values between 17% and 35%. Permeability is consistent briefly away from well location but higher in shale units. These oil impregnated shale units are laterally consistent in the up-dip portion but were overtaken by the clastic units in the distal portion. This made draining of hydrocarbon better done in the down-dip portion of the area. An excellent comparative analysis was made of the litho-facies model, petrophysical properties, and inversion results obtained from the vintage seismic. This has yielded a good result in characterizing variation in rock properties of the subtle laterally inconsistent synsedimentary lithofacies of this ar

APPLICATION OF ROCK AND SEISMIC PROPERTIES FOR PREDICTION OF HYDROCARBON POTENTIAL

This study explores the use of well logs and seismic derived rock properties to predict hydrocarbon potentials. Crossplot analysis of well log data and seismic attributes extracted and captured over some depth windows from the vicinity of the prolific hydrocarbon zone was the main methodology. This made it possible to develop relationships through cross-plotting of different log types and different seismic attributes. Emphasis was placed on petrophysics based properties from well logs while the stratigraphic, complex and signal based seismic attributes were computed and analysed. Combination of one or more attributes was attempted in deriving a correlative relationship typifying the reservoir property. The well log derived properties predicted the hydrocarbon potential of the reservoir better as it gave better correlation of above 70% on the crossplots made. While seismic properties crossplots had poor correlation except those of signal based and complex attributes that gave negative correlations

Stratigraphy and reservoir quality of the turbidite deposits, western sag, Bohai bay, China P.R.

Stratigraphic and subtle reservoirs such as pinchouts, sand lenses and unconformities have been discovered in Bohai basin. These reservoirs occur in sub-basins and sag structures called depressions. A prolific depression is the Liaohe depression that has been filled with rapidly changing mixed alluvial fan deposit of the Cenozoic age. Attempts made at recovering residual hydrocarbon from the subtle reservoir have necessitated the re-evaluation of available data to characterize and model the prolific Shahejie Formation turbidite deposit occurring as pinchouts and sand lenses for hydrocarbon assessment, reservoir quality and possible recovery through enhanced methods. Methods employed covered well logs analysis, clustering analysis for electrofacies and fuzzy logic analysis to predict missing log sections. Stratigraphic and structural analysis was done on SEGY 3D seismic volume after seismic to well tie. Stochastic simulation was done on both discrete and continuous upscaled data. This made it possible to correctly locate and laterally track identified reservoir formation on seismic data. Petrophysical parameters such as porosity and permeability were modeled with result of clustering analysis. Result shows that electrofacies converged on 2 rock classes. The area is characterized by the presence of interbeded sand-shale blanket formations serving as reservoir and seal bodies. The reservoir quality of the formations as seen on the petrophysical analysis done is replicated in simulation volume results. Reservoir rocks have porosity between 0.1 and 0.25, permeability between 1 and 2mD and hydrocarbon saturation as high as 89%. Lithofacies are observed to be laterally inconsistent, sub-parallel to dipping and occurring as porous and permeable continuous beds or pinchouts hosting hydrocarbon. The stochastic stratigraphic model depicts rock units in associations that are synsedimentary. The prevalent configuration gotten from the model gave an insight into exploring and developing the field for enhanced oil recovery of the heavy hydrocarbon of this area

Integrated Multivariate Lateral Predictions For Reservoir Properties Via Geostatistical Modeling

Hydrocarbon production is a function of various elements such as reservoir quality, petrophysical properties, geophysical properties and also volume. Lateral extent of reservoir body is important information for estimation of hydrocarbon initially in place and the recoverable quantity. A method of integrated lateral prediction towards understanding reservoir geometry and rock properties towards enhanced hydrocarbon production is explored with dataset from Bohai bay, Northern China. The methods of conventional well log analysis, seismic interpretation and geostatistical modeling has been employed for this study. Computation of useful logs like Volume of shale, porosity, permeability, Acoustic impedance and Elastic impedance was primarily done on well logs followed by the identification of potential reservoir formation. Lateral extent of reservoir horizons was traced on seismic reflection data with precision through continuity and dominance. Seismic attributes were also computed to assist in better understanding of the characteristics of the rock units in structure and stratigraphy. Computation of variograms and data transformation was done prior to geostatistical simulations for all rock properties considered. The result shows an all encompassing realization on a static model of lateral rock properties within the zone of interest thereby making it easy for making decisions locating parts of the field with high values in rock and fluid properties as potential portions towards hydrocarbon production

Facies and Depositional Environment Analysis of Alternate Channel Bodies in the Flank of a Sag Structure

The down-dip (40o) portion turbidite Cenozoic deposits of the western sag structure in the Bohai bay been characterized for stratigraphy. Laterally tracking continuity in temporal data becomes challenging with increase in offset. In achieving this and ground-truthing results from core data, spatial data is indispensable. A good subsurface resolution on seismic data is key to understanding both the distribution and extent of lithological units earlier identified as hydrocarbon prolific. Rock physics and petrophysical properties when understood and appropriately utilized does well in showing vital correlations inherent in subsurface lithological units. Deterministic approach to linking pattern on logs proved slightly useful in this study. Each have its’ distinct depositional cycle ranging from 3 cycles for wells 13-2, 35-4 and 46-2 to 4 cycles for 24-5. It has been discovered that well 13-2 has less complex structure while well 46-2 is most distal occurring at the toe of the sag structure, has the most complex geometry. However, hidden vital information became obvious when methods of seismic interpretation and post-inversion multi-attribute analyses were used within the same cross section to discover subtle alternating channel sand lobes that is explorable within an unfaulted and slightly com-pacted synsedimentary sequence. These were presented in log panels, cross-sections and maps

AdaMEC: Towards a Context-Adaptive and Dynamically-Combinable DNN Deployment Framework for Mobile Edge Computing

With the rapid development of deep learning, recent research on intelligent and interactive mobile applications (e.g., health monitoring, speech recognition) has attracted extensive attention. And these applications necessitate the mobile edge computing scheme, i.e., offloading partial computation from mobile devices to edge devices for inference acceleration and transmission load reduction. The current practices have relied on collaborative DNN partition and offloading to satisfy the predefined latency requirements, which is intractable to adapt to the dynamic deployment context at runtime. AdaMEC, a context-adaptive and dynamically-combinable DNN deployment framework is proposed to meet these requirements for mobile edge computing, which consists of three novel techniques. First, once-for-all DNN pre-partition divides DNN at the primitive operator level and stores partitioned modules into executable files, defined as pre-partitioned DNN atoms. Second, context-adaptive DNN atom combination and offloading introduces a graph-based decision algorithm to quickly search the suitable combination of atoms and adaptively make the offloading plan under dynamic deployment contexts. Third, runtime latency predictor provides timely latency feedback for DNN deployment considering both DNN configurations and dynamic contexts. Extensive experiments demonstrate that AdaMEC outperforms state-of-the-art baselines in terms of latency reduction by up to 62.14% and average memory saving by 55.21%

Effect of the Dependent Paths in Linear Hull

Linear Hull is a phenomenon that there are a lot of linear paths with the same data mask but different key masks for a block cipher. In 1994, K. Nyberg presented the effect on the key-recovery attack such as Algorithm 2 with linear hull, in which the required number of the known plaintexts can be decreased compared with that in the attack using an individual linear path. In 2009, S. Murphy proved that K. Nyberg\u27s results can only be used to give a lower bound on the data complexity and will be no use on the real linear cryptanalysis. In fact, the linear hull produces such positive effect in linear cryptanalysis only for some keys instead of the whole key space. So the linear hull can be used to improve the classic linear cryptanalysis for some weak keys. In the same year, K. Ohkuma gave the linear hull analysis on reduced-round PRESENT block cipher, and showed that there are $32\%$ weak keys of PRESENT which make the bias of a given linear hull with multiple paths more than a lower bound. However, K. Ohkuma has not considered the dependency of the multi-path, and his results are based on the assumption that the linear paths are independent. Actually, most of the linear paths are dependent in the linear hull. In this paper, we will analyze the dependency of the linear paths in a linear hull and the real effect of linear hull with the dependent linear paths. Firstly, we give the relation between the bias of a linear hull and its linear paths in linear cryptanalysis. Secondly, we present the formula to compute the rate of weak keys corresponding to the expected bias of the dependent paths. Based on the formula, we show that the dependency of linear paths reduces the number of weak keys corresponding to higher biases of the linear hull compared with that in the independent case. It means that the dependency of linear paths reduces the effect of linear hull. At last, we verify our conclusion by analyzing reduced-round of PRESENT