Regression analysis and its application to oil and gas exploration:A case study of hydrocarbon loss recovery and porosity prediction,China

In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.Meanwhile,Kernel Ridge Regression emerges as a noteworthy strategy in ameliorating porosity-logging curve prediction for well A,evidencing its aptness for intricate geological structures.This research attests to the scientific ascendancy and broad-spectrum relevance of these regression techniques over conventional methods while heralding new horizons for their deployment in the oil and gas sector.The insights garnered from these advanced modeling strategies are set to transform geological and engineering practices in hydrocarbon prediction,evaluation,and recovery.

RTP-Packets’ Loss Recovery Scheme Based on Layered Buffer-Routers

This paper introduces an RTP-packets' loss recovery scheme in MPEG-4 playback type multicast application model, which is based on retransmission scheme. Through the auxiliary and coordinated buffer playing scheme of layered “buffer-routers”, the RTP-packets' loss recovery in limited time is made possible. We consider in the scheme to handle retransmission request with buffer waiting when network congestion occurs. Thus, neither the degree of congestion will be worsened nor the retransmission request will be lost when sending the request to higher-level buffer router. The RTP-packets' loss recovery scheme suggested by us is not only applied to MPEG-4 multicast application in LAN, but also can be extended to more spacious WAN (wide area network) when user groups comparatively centralize in certain number of local areas. Key words MPEG-4 - retransmission - RTP - loss recovery CLC number TP 393 Foundation item: Supported by the “Tenth Five-year Plan” 211 Engineering Construction ItemBiography: XU Xian-bin(1954-), male, professor Ph. D candidate, research directions: computer network and communication, distributed parallel processing, mass information storage.

Hybrid approach for loss recovery mechanism in OBS networks

This letter reports a study of a hybrid burst assembly and a hybrid burst loss recovery scheme （delay-based burst assembly and hybrid loss recovery （DBAHLR）） which selectively employs proactive or reactive loss recovery techniques depending on the classification of traffic into short term and long term, respectively. Traffic prediction and segregation of optical burst switching network flows into the long term and short term are conducted based on predicted link holding times using the hidden Markov model （HMM）. The hybrid burst assembly implemented in DBAHLR uses a consecutive average-based burst assembly to handle jitter reduction necessary in real-time applications, with variations in burst sizes due to the non-monotonic nature of the average delay handled by additional burst length thresholding. This dynamic hybrid approach based on HMM prediction provides overall a lower blocking probability and delay and more throughput when compared with forward segment redundancy mechanism or purely HMM prediction-based adaptive burst sizing and wavelength allocation （HMM-TP）.

Anatomical changes in the somatosensory system after large sensory loss predict strategies to promote functional recovery after spinal cord injury

Among cases of spinal cord injury are injuries involving the dorsal column in the cervical spinal cord that interrupt the major cutaneous afferents from the hand to the cuneate nucleus（Cu）in the brainstem.Deprivation of touch and proprioceptive inputs consequently impair skilled hand use.

An efficient QoS enhancement mechanism of VoIP using erasure array codes

In order to solve the problem of losing voice packets in voice over internet protocol(VoIP),a kind of lost packets double recovery algorithm is proposed. The algorithm is based on erasure coding technique which comes from highly available data storage systems. An efficient coding scheme with higher tolerance based on STAR and Reed-Solomon( RS) erasure code is described. An efficient method is also provided which could transform the voice data packets of one dimensional bit stream into two dimensional array according to given window size. If the lost rate has increased beyond the error correction capability,packet-loss concealment will be adopted. Under various conditions of packet-loss simulation during the experiments,the algorithm has proved its better performance on MOS rating and coding rate.