Development of intelligent systems for well drilling and petroleum production

Domains where knowledge representation is too complex to be described analytically and in a deterministic way is very common in the petroleum industry, particularly in the field of exploration and production. In these domains, applications of artificial intelligence techniques are very suitable, especially in cases where the preservation of corporate and technical knowledge is important. The Laboratory for Research on Artificial Intelligence Applied to Petroleum Engineering (LIAP) at Unicamp, has, during the last 10 years, dedicated research efforts to build intelligent systems in well drilling and petroleum production fields. In the following sections, recent advances in intelligent systems, under development in the research laboratory, are described. (C) 2001 Published by Elsevier B.V. B.V.

Comparative analysis of drilling frequencies in recent brachiopod-mollusk associations from the Southern Brazilian Shelf

Over 14,000 specimens-5,204 brachiopods, 9,137 bivalves, and 178 gastropods-acquired from 30 collecting stations (0 to 45 m depth) in the Ubatuba and Picinguaba bays, southern Brazil, were compared for drilling frequencies. Beveled (countersunk) circular-to-subcircular borings (Oichnus-like drill holes) were found in diverse bivalves but also in the rhynchonelliform brachiopod Bouchardia rosea-a small, semi-infaunal to epifaunal, free-lying species that dominates the brachiopod fauna of the southern Brazilian shelf. Drill holes in bivalve mollusks and brachiopods are comparable in their morphology, average diameter, and diameter range, indicating attacks by a single type of drilling organism. Drill holes in brachiopods were rare (0.4%) and found only at five sampling sites. Drillings in bivalves were over 10 times as frequent as in brachiopods, but the average drilling frequency was still low (5.6%) compared to typical boring frequencies of Cenozoic mollusks. Some common bivalve species, however, were drilled at frequencies up to 50 times higher than those observed for shells of B. rosea from the same samples. Due to scarcity of drilled brachiopods, it is not possible to evaluate if the driller displayed a nonrandom (stereotyped) site, size, or valve preference. Drilled brachiopods may record (1) naticid or muricid predation, (2) predation by other drillers, (3) parasitic drillings, and (4) mistaken or opportunistic attacks. Low drilling frequency in brachiopods is consistent with recent reports on ancient and modern examples. The scarcity of drilling in brachiopods, coupled with much higher drilling frequencies observed in sympatric bivalves, suggests that drilling in brachiopods may have been due to facultative or erroneous attacks. The drilling frequencies observed here for the brachiopod-bivalve assemblages are remarkably similar to those reported for Permian brachiopod-bivalves associations. This report adds to the growing evidence for an intriguing macroecological stasis: multiple meta-analytical surveys of present-day and fossil rhynchonelliform brachiopods conducted in recent years also point to persistent scarcity and low intensity of biotic interactions between brachiopods and drilling organisms throughout their evolutionary history.

Repair characteristics of horizontal root fracture: a case report

Radicular fractures in permanent teeth are uncommon injuries among dental traumas, comprising 0.5-7% of the cases. Fracture occurs most often in the middle-third of the root and rarely at the apical-third. The present paper reports a clinical case of a horizontal radicular fracture located between the middle- and apical-third of a upper left-central incisor followed-up for over 3 years. The tooth was extracted owing to periodontal reasons. Histomorphologically, it showed pulp-vitality preservation and root healing by hard-tissue deposition.

Revisiting horizontal transfer of transposable elements in Drosophila

Horizontal transfer ( HT), defined as the transfer of genetic material between species, is considered to be an essential step in the 'life cycle' of transposable elements. We present a broad overview of suspected cases of HT of transposable elements in Drosophila. Hundred-one putative events of HT have been proposed in Drosophila for 21 different elements (5.0% refer to non-long terminal repeat (LTR) retrotransposons, 42.6% to LTR retrotransposons and 52.4% to DNA transposons). We discuss the methods used to infer HT, their limits and the putative vectors of transposable elements. We outline all the alternative hypotheses and ask how we can be almost certain that phylogenetic inconsistencies are due to HT.

Horizontal distribution of megalopae of Brachyura (Crustacea, Decapoda) in a South American tropical estuary

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The copia retrotransposon and horizontal transfer in Drosophila willistoni

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Electromyographic analysis of the pectoralis major and deltoideus anterior muscles in horizontal flyer exercises with loads

The effective activity of the pectoralis major and deltoideus anterior muscles in horizontal flyer exercises with external loads of 25, 50, 75 and 100% of the maximum load was studied in 11 male volunteers. The electromyographic analysis was done by using MEDI-TRACE-200 surface electrodes connected to a biological signal acquisition mode coupled to a PC/AT computer. The electromyographic signals were processed and the values obtained were normalized through maximum voluntary isometric contraction. It was statistically observed that in all types and loads of this exercise, the muscles presented significant differences in the concentric and eccentric phases. In the concentric phase, when different loads were compared, the muscles were more active with 75 and 100% of the maximum load, while in the eccentric phase, higher activity was observed with 100% of the maximum load. By analyzing each load effect in the concentric phase, it was verified that the muscles on the left side were more active than those on the right side with 25, 75 and 100% of the maximum load.

Application of ARX neural networks to model the rate of penetration of petroleum wells drilling

Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.

Remoção de etanol e benzeno em reator anaeróbio horizontal de leito fixo na presença de sulfato

In this study it is reported the operation of a horizontalflow anaerobic immobilized biomass (HAlB) reactor under sulfate-reducing condition which was also exposed to different amounts of ethanol and benzene. The HAIB reactor comprised of an immobilized biomass on polyurethane foam and ferrous and sodium sulfate solutions were used (91 and 550 mg.l -1, respectively), to promote a sulfate-reducing environment. Benzene was added at an initial concentration of 2.0 mg.l -1 followed by an increased to 9 e 10 mg. l -1, respectively. Ethanol was added at an initial concentration of 170 mg.l -1 followed by an increased range of 960 mg.l -1. The reactor was operated at 30 (± 2) °C with hydraulic detention time of 12 h. Organic matter removal efficiency of 90% with a maximum benzene degradation rate of 0.07 mv, benzene.mg -1 vss.d -1 Thus, this work corroborate the data obtained for Cattony et al (2005) and also demonstrate that compact units of HAIB reactors, under sulfate reducing conditions, are a potential alternative for in situ aromatic compounds bioremediation.

Applying a genetic neuro-model reference adaptive controller in drilling optimization

Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.

Classification of petroleum well drilling operations using Support Vector Machine (SVM)

During the petroleum well drilling operation many mechanical and hydraulic parameters are monitored by an instrumentation system installed in the rig called a mud-logging system. These sensors, distributed in the rig, monitor different operation parameters such as weight on the hook and drillstring rotation. These measurements are known as mud-logging records and allow the online following of all the drilling process with well monitoring purposes. However, in most of the cases, these data are stored without taking advantage of all their potential. On the other hand, to make use of the mud-logging data, an analysis and interpretationt is required. That is not an easy task because of the large volume of information involved. This paper presents a Support Vector Machine (SVM) used to automatically classify the drilling operation stages through the analysis of some mud-logging parameters. In order to validate the results of SVM technique, it was compared to a classification elaborated by a Petroleum Engineering expert. © 2006 IEEE.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Horizontal co-operation on environmental issues in Latin America and the Caribbean: the challenges of an idea in time of crisis

Includes bibliography

Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm

This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.