Mortality of Migratory Birds from Marine Commercial Fisheries and Offshore Oil and Gas Production in Canada

There is an imminent need for conservation and best-practice management efforts in marine ecosystems where global-scale declines in the biodiversity and biomass of large vertebrate predators are increasing and marine communities are being altered. We examine two marine-based industries that incidentally take migratory birds in Canada: (1) commercial fisheries, through bycatch, and (2) offshore oil and gas exploration, development, and production. We summarize information from the scientific literature and technical reports and also present new information from recently analyzed data to assess the magnitude and scope of mortality. Fisheries bycatch was responsible for the highest levels of incidental take of migratory bird species; estimated combined take in the longline, gillnet, and bottom otter trawl fisheries within the Atlantic, including the Gulf of St. Lawrence, and Pacific regions was 2679 to 45,586 birds per year. For the offshore oil and gas sector, mortality estimates ranged from 188 to 4494 deaths per year due to the discharge of produced waters resulting in oil sheens and collisions with platforms and vessels; however these estimates for the oil and gas sector are based on many untested assumptions. In spite of the uncertainties, we feel levels of mortality from these two industries are unlikely to affect the marine bird community in Canada, but some effects on local populations from bycatch are likely. Further research and monitoring will be required to: (1) better estimate fisheries-related mortality for vulnerable species and populations that may be impacted by local fisheries, (2) determine the effects of oil sheens from produced waters, and attraction to platforms and associated mortality from collisions, sheens, and flaring, so that better estimates of mortality from the offshore oil and gas sector can be obtained, and (3) determine impacts associated with accidental spills, which are not included in our current assessment. With a better understanding of the direct mortality of marine birds from industry, appropriate mitigation and management actions can be implemented. Cooperation from industry for data collection, research to fill knowledge gaps, and implementation of mitigation approaches will all be needed to conserve marine birds in Canada.

Use of the LMS adaptive signal processing technique to improve signal data rates from practical oil well logging equipment

The simulation and development work that has been undertaken to produce a signal equaliser used to improve the data rates from oil well logging instruments is presented. The instruments are lowered into the drill bore hole suspended by a cable which has poor electrical characteristics. The equaliser described in the paper corrects for the distortions that occur from the cable (dispersion and attenuation) with the result that the instrument can send data at 100 K.bits/second down its own suspension cable of 12 Km in length. The use of simulation techniques and tools were invaluable in generating a model for the distortions and proved to be a useful tool when site testing was not available.

Using modelling tools to optimise the calculation and subsequent reduction of cable distortion parameters with application to oil well logging systems

This paper discusses how the use of computer-based modelling tools has aided the design of a telemetry unit for use with oil well logging. With the aid of modern computer-based simulation techniques, the new design is capable of operating at data rates of 2.5 times faster than previous designs.

GULF OF MEXICO'S OFFSHORE OIL PLATFORM WIND POTENTIAL

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Cinemática de partículas em fluidos de viscosidade variável com o tempo e sua aplicação na construção de poços de petróleo: avaliação durante paradas operacionais

The new oil reservoirs discoveries in onshore and ultra deep water offshore fields and complex trajectories require the optimization of procedures to reduce the stops operation during the well drilling, especially because the platforms and equipment high cost, and risks which are inherent to the operation. Among the most important aspects stands out the drilling fluids project and their behavior against different situations that may occur during the process. By means of sedimentation experiments, a correlation has been validated to determe the sedimentation particles velocity in variable viscosity fluids over time, applying the correction due to effective viscosity that is a shear rate and time function. The viscosity evolution over time was obtained by carrying out rheologic tests using a fixed shear rate, small enough to not interfere in the fluid gelling process. With the sedimentation particles velocity and the fluid viscosity over time equations an iterative procedure was proposed to determine the particles displacement over time. These equations were implemented in a case study to simulate the cuttings sedimentation generated in the oil well drilling during stops operation, especially in the connections and tripping, allowing the drilling fluid project in order to maintain the cuttings in suspension, avoiding risks, such as stuck pipe and in more drastic conditions, the loss of the well

Novo método para estimativa do gradiente de fratura para poços de petróleo

The development of oil wells drilling requires additional cares mainly if the drilling is in offshore ultra deep water with low overburden pressure gradients which cause low fracture gradients and, consequently, difficult the well drilling by the reduction of the operational window. To minimize, in the well planning phases, the difficulties faced by the drilling in those sceneries, indirect models are used to estimate fracture gradient that foresees approximate values for leakoff tests. These models generate curves of geopressures that allow detailed analysis of the pressure behavior for the whole well. Most of these models are based on the Terzaghi equation, just differentiating in the determination of the values of rock tension coefficient. This work proposes an alternative method for prediction of fracture pressure gradient based on a geometric correlation that relates the pressure gradients proportionally for a given depth and extrapolates it for the whole well depth, meaning that theses parameters vary in a fixed proportion. The model is based on the application of analytical proportion segments corresponding to the differential pressure related to the rock tension. The study shows that the proposed analytical proportion segments reaches values of fracture gradient with good agreement with those available for leakoff tests in the field area. The obtained results were compared with twelve different indirect models for fracture pressure gradient prediction based on the compacting effect. For this, a software was developed using Matlab language. The comparison was also made varying the water depth from zero (onshore wellbores) to 1500 meters. The leakoff tests are also used to compare the different methods including the one proposed in this work. The presented work gives good results for error analysis compared to other methods and, due to its simplicity, justify its possible application

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

Artificial immune systems for classification of petroleum well drilling operations

This paper presents two approaches of Artificial Immune System for Pattern Recognition (CLONALG and Parallel AIRS2) to classify automatically the well drilling operation stages. The classification is carried out through the analysis of some mud-logging parameters. In order to validate the performance of AIS techniques, the results were compared with others classification methods: neural network, support vector machine and lazy learning.

Petroleum well drilling monitoring through cutting image analysis and artificial intelligence techniques

Petroleum well drilling monitoring has become an important tool for detecting and preventing problems during the well drilling process. In this paper, we propose to assist the drilling process by analyzing the cutting images at the vibrating shake shaker, in which different concentrations of cuttings can indicate possible problems, such as the collapse of the well borehole walls. In such a way, we present here an innovative computer vision system composed by a real time cutting volume estimator addressed by support vector regression. As far we know, we are the first to propose the petroleum well drilling monitoring by cutting image analysis. We also applied a collection of supervised classifiers for cutting volume classification. (C) 2010 Elsevier Ltd. All rights reserved.

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.

Fast petroleum well drilling monitoring through optimum-path forest

Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the Optimum-Path Forest classifier. Given that the cutting's volume at the vibrating shale shaker can provide several information about drilling, we used computer vision techniques to extract texture informations from cutting images acquired by a digital camera. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and effciency. We used the Optimum-Path Forest (OPF), EOPF (Efficient OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP) Support Vector Machines (SVM), and a Bayesian Classifier (BC) to assess the robustness of our proposed schema for petroleum well drilling monitoring through cutting image analysis.

A Note on US Royalty Relief, Rent Sharing and Offshore Oil Production

This paper offers an economic analysis explaining why royalty relief under US Federal legislation is expensive in terms of revenue foregone, but is largely ineffective in increasing US offshore oil production. Repeal of royalty relief is therefore justified.

Geospatial analysis of groundwater depth for manual well drilling suitability in the Zinder Region, Niger

Manual and low-tech well drilling techniques have potential to assist in reaching the United Nations' millennium development goal for water in sub-Saharan Africa. This study used publicly available geospatial data in a regression tree analysis to predict groundwater depth in the Zinder region of Niger to identify suitable areas for manual well drilling. Regression trees were developed and tested on a database for 3681 wells in the Zinder region. A tree with 17 terminal leaves provided a range of ground water depth estimates that were appropriate for manual drilling, though much of the tree's complexity was associated with depths that were beyond manual methods. A natural log transformation of groundwater depth was tested to see if rescaling dataset variance would result in finer distinctions for regions of shallow groundwater. The RMSE for a log-transformed tree with only 10 terminal leaves was almost half that of the untransformed 17 leaf tree for groundwater depths less than 10 m. This analysis indicated important groundwater relationships for commonly available maps of geology, soils, elevation, and enhanced vegetation index from the MODIS satellite imaging system.

Assessment of environmental fate and effects of discharges from offshore oil and gas operations /

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