Skip to main content. This service is more advanced with JavaScript available. Advertisement Hide. General Approaches of Pipeline Defect Assessment. Authors Authors and affiliations G. Conference paper. This is a preview of subscription content, log in to check access. Translate PDF. Development of a proprietary software to evaluate the speed sound, linear localization and the transient analysis; iii.
Validation of the AE technique: monitoring of a full scale pipeline submitted to internal cycling pressure and simulating a long term operation. AE sources were localized by the AEHistory software. Linear localization evaluated by AEHistory. Hydraulic test 4. AE threshold amplitude 60dB. The energy content of the transient burst wave related to the first sensor hit, was evaluated in term of the integral and the rate versus the time. Giunta, L. Prandi, S.
Budano, A. Lucci, Methods Citations. Figures and Tables from this paper. Citation Type. Has PDF. Publication Type. More Filters. The integrity of oil and gas transmission pipelines is now the subject of new regulations, codes and standards in the USA and elsewhere. A key element of pipeline integrity and these new initiatives … Expand.
Smart pigs are used extensively as part of integrity management plans for oil and gas pipelines to detect metal loss defects, with magnetic flux leakage MFL technology being the most-widely used.
The Pipeline Defect Assessment Manual PDAM project is a joint industry project sponsored by fifteen international oil and gas companies, to produce a document specifying the best methods for … Expand. In the research presented in this paper, a failure analysis had been carried out to identify causes of an incident, which had taken place after an operation to repair a leak in an interstate natural … Expand.
It then relates these parameters to pipelines with high design factors above 0. It … Expand. View 2 excerpts, cites background. Geometric anomalies in pipelines are mainly represented by dents, ovalities and buckles. Dents can occur either during pipeline construction or in-service.
The partial safety factors used in the calculation methods are based on empirical data and are not directly related to the inevitable random variations of these parameters. The defect size of around the circumference of the pipe is usually not taken into account.
For the flat defects crack, delamination the main parameters are length and depth of the defect. It is not possible to single out a more accurate approximation on the available results of field tests of pipes with defects. Taking into account random variations in the shape and size of real defects, any approximation with an undefined error can be used. In conclusion, it should be noted that pipeline defects are random, unique and complex in shape and their sizes are depend on the operating conditions and the properties of the external environment.
The characteristics of defects cannot always be described by the current norms and calculation methods. The above analysis shows that pipeline will invariably contain defects at some stage during its life. The full-scale tests of pipelines with defects and limit state functions method are used for such assessment. The limit state function method allows determining the limit size of defect upon reaching which the pipeline will fail. The limit state function L for pipe with defect can be write as:.
The defects sizes l i are established during ILI. The allowable defects sizes l r are determined by calculation methods by the specified criteria for the strength and durability of structures, taking in to account the operating conditions and the character of the mechanisms of deformation and destruction [ 6 , 7 , 8 , 9 , 10 ]. It should be emphasized that in these methods the sizes of defects l i and l r are assumed to be deterministic values.
In reality, the defects have inevitable random dispersion of sizes. For detected defects, these are caused by the random nature of the defects, as well as by statistical errors and the probabilistic nature of the operational characteristics sensitivity and detectability of non-destructive testing methods [ 16 ].
The dispersion of the calculate sizes of defects determined by statistical scattering loads, operating conditions and scattering of mechanical properties. A certain contribution to the possible dispersion of defect sizes is made by idealization of the shapes and schemes of defects. Taking this into account, instead of single-valued sizes in the calculations, it is necessary to use the probability densities distribution functions of defect sizes f l i and f l r.
Using the functions f l i and f l r gives reason to believe that there are always nonzero probabilities P presence of defects with sizes l i larger than l r Figure 1 :. Probabilistic scheme of the defects hazard analysis. Moreover, the larger the defect, the more significant losses can be. It should be emphasized that the losses are also random in magnitude, since it depends on the many technical and socio-economic factors.
Joint analysis of the probabilistic nature of defects, their hazard and possible losses leads to the concept of the admissibility of defects according to risk criteria [ 11 , 18 ].
The essence of this concept is that the criterion condition for the admissibility of defects is represented in the form:. Assuming the defect size l i as a fixed random variable from 3 we can obtain the following condition for the admissibility of a defect:.
Due to the unresolved problem of assessment and statistical analysis of losses, currently, sufficiently substantiated proposals for determining the allowable risk have not been developed. As a rule, losses are categorized into some qualitative classes: negligible, acceptable, unacceptable, etc. Each class of losses is associated with a certain acceptable level of its probabilities [ R f ].
Taking this into account, instead of 3 , one can go to a simpler form of assessing the admissibility of defects by risk criteria, which does not require a direct assessment of damages, namely:. On this basis, similarly to 5 , the following condition for the admissibility of defects can be written:. Expressions 4 and 6 , in fact, are a semi-probabilistic solution to problems 3 and 5 , since they relate fixed random variables, one of which has a given probabilistic support.
In this section the probabilistic methodology is use for develop a semi-probabilistic method for assessing the admissible sizes of defects in subsea inter-field pipelines based on risk criteria. The basis of this method are requirements of standards [ 7 , 9 ]. The risk is defined as the probability R f negative consequences of pipeline accident, the scale of which is determined by the hazard class. The proposed hazard classes risk matrix for inter-field subsea pipelines are presented in Table 1.
Quantitative economic and environmental damage assessments are not considered here. The suitability of the pipeline for operation is determined by three-level assessment of the allowable size of defects by risk criteria Figure 2.
The first, basic level, determines the allowable defect sizes by the strength characteristics of metal for pipelines exposed to the main loads - internal overpressure and hydrostatic external pressure. The second, extended level, determines the allowable defect sizes by the strength characteristics for metal, taking into account the effect on pipelines of additional longitudinal and bending loads.
The third, special level, determines the allowable sizes of cracks, crack-like defects and delamination by the characteristics of crack resistance of the metal. Scheme for calculating the allowable size of defects. The calculations use information about: pipe sizes, location of the pipeline on the seabed, loads and impacts; the size, location and types of defects; mechanical properties, industry standard requirements, and pipe specifications. The hazard of pipe defects depends on their shape and size.
By shape the defects can be classified into volumetric and flat. These relative dimensions are used in this technique taking into account the classification of defects shape. Idealization of volumetric a and flat b defects shape.
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