A Three-Dimensional Model for the Formation Pressure in Wellbores under Uncertainty

Formation pressure is the key parameter for the analysis of wellbore safety.With increasing drilling depth,how-ever,the behavior of this variable becomes increasingly complex.In this work,a 3D model of the formation pres-sure under uncertainty is presented.Moreover a relevant algorithm is elaborated.First,the logging data of regional key drilling wells are collected and a one-dimensional formation pressure profile along the well depth is determined.Then,a 3D model of regional formation pressure of the hierarchical group layer is defined by using the Kriging interpolation algorithm relying on a support vector machine(SVM)and the formation pressure of the drilled wells.To validate the method,the formation pressure of one pre-drilled well is compared with the well logging results.The comparison reveals that the maximum relative error is less than 4.5%.The software based on this model is complemented by a computer visualization technology,which provides a relevant tool for under-standing and analyzing the 3D formation pressure.The outcomes of this study are intended to support the char-acterization of areas with missing or poor 3D seismic data and provide more accurate information for the analysis of wellbore integrity.

An Artificial Intelligence Algorithm for the Real-Time Early Detection of Sticking Phenomena in Horizontal Shale Gas Wells

Sticking is the most serious cause of failure in complex drilling operations.In the present work a novel“early warning”method based on an artificial intelligence algorithm is proposed to overcome some of the known pro-blems associated with existing sticking-identification technologies.The method is tested against a practical case study(Southern Sichuan shale gas drilling operations).It is shown that the twelve sets of sticking fault diagnostic results obtained from a simulation are all consistent with the actual downhole state;furthermore,the results from four groups of verification samples are also consistent with the actual downhole state.This shows that the pro-posed training-based model can effectively be applied to practical situations.

Boosting Hydrogen Evolution and Oxygen Reduction Performances of Pd/C upon Surface Phosphorization

Simultaneous heterostructure and composition engineering is an effective route to construct electrocatalyst of high performance. Conjugated microporous polymer(CMP) is a new emerging platform material with designable porosity and functionality. Here, a facile CMP-guest chemistry method was presented to prepare PdP2@Pd/C heterostructure with bifunctional electrocatalytic activity. The formation of heterostructure relies on a CMP precursor consisting of nitrogen groups that allow binding Pd species and introducing phosphorus inclusion. The Pd-bound CMP precursor formed in-situ could be directly converted into nitrogen-and phosphide-doped porous carbon(NPC) during pyrolysis, while P diffused to the Pd/C interface results in shallow phosphorization. The as-prepared NPC consisting of PdP2@Pd/C(Pd content 4 wt%) heterostructure demonstrated significantly enhanced electrocatalytic performances including a promising HER activity(58mV @ 10 mA/cm2), and an ORR activity approaching commercial 20 wt% Pd/C together with excellent long-term stability. Our work illustrates the intriguing power of CMP-guest potential in heterostructure engineering.