Modified approach for identifying weak zones for effective sand management
Abstract Sand production is a major problem that the oil and gas industry has been facing for years. It can lead to loss of production, equipment damage or complete well abandonment. Prediction of sand has been historically challenging due to the periodic nature of sand production, insufficient labo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2019-10-01
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| Series: | Journal of Petroleum Exploration and Production Technology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1007/s13202-019-00784-5 |
| _version_ | 1828203618798403584 |
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| author | Aliyu Adebayo Sulaimon Lim Lee Teng |
| author_facet | Aliyu Adebayo Sulaimon Lim Lee Teng |
| author_sort | Aliyu Adebayo Sulaimon |
| collection | DOAJ |
| description | Abstract Sand production is a major problem that the oil and gas industry has been facing for years. It can lead to loss of production, equipment damage or complete well abandonment. Prediction of sand has been historically challenging due to the periodic nature of sand production, insufficient laboratory tests and lack of field tests validation. Analyses have been performed to identify weak zones for planned wells, and common technique is the application of shear modulus and mechanical properties log (MPL) criteria developed by Tixier et al. (J Pet Technol 27:283–293, 1975). However, the set criteria have been found to be generally inadequate to detect transition zone or predict weak formation in some fields. In this study, using the knowledge of rock behavior, geomechanical properties and well log data, we have established new simple criteria for identifying fragile sections within a transition zone. In situ logging data from a field X, located in Sabah, Malaysia, and Field Y, located in Shimokita, Japan, were used in this study. Using the threshold for shear modulus and MPL, the criteria for the geomechanical properties are set to differentiate formation strengths at different depths. The threshold for Poisson’s ratio is 0.34, Young’s modulus at 1.6 × 106 psi and the unconfined compressive strength at 2400 psi. The MPL and geomechanical models were generated to predict sanding incident. The results were subsequently validated with artificial neural network using MATLAB. Also, critical wellbore pressure is calculated and acts as a guide to operate outside the sand failure envelope. Thus, the prediction of the weak formation using geomechanical properties has been further established in this study. |
| first_indexed | 2024-04-12T12:09:03Z |
| format | Article |
| id | doaj.art-65b82c8375eb4f758aa25d8cfa9b9010 |
| institution | Directory Open Access Journal |
| issn | 2190-0558 2190-0566 |
| language | English |
| last_indexed | 2024-04-12T12:09:03Z |
| publishDate | 2019-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Petroleum Exploration and Production Technology |
| spelling | doaj.art-65b82c8375eb4f758aa25d8cfa9b90102022-12-22T03:33:37ZengSpringerOpenJournal of Petroleum Exploration and Production Technology2190-05582190-05662019-10-0110253755510.1007/s13202-019-00784-5Modified approach for identifying weak zones for effective sand managementAliyu Adebayo Sulaimon0Lim Lee Teng1Petroleum Engineering Department, Universiti Teknologi PETRONASPetroleum Engineering Department, Universiti Teknologi PETRONASAbstract Sand production is a major problem that the oil and gas industry has been facing for years. It can lead to loss of production, equipment damage or complete well abandonment. Prediction of sand has been historically challenging due to the periodic nature of sand production, insufficient laboratory tests and lack of field tests validation. Analyses have been performed to identify weak zones for planned wells, and common technique is the application of shear modulus and mechanical properties log (MPL) criteria developed by Tixier et al. (J Pet Technol 27:283–293, 1975). However, the set criteria have been found to be generally inadequate to detect transition zone or predict weak formation in some fields. In this study, using the knowledge of rock behavior, geomechanical properties and well log data, we have established new simple criteria for identifying fragile sections within a transition zone. In situ logging data from a field X, located in Sabah, Malaysia, and Field Y, located in Shimokita, Japan, were used in this study. Using the threshold for shear modulus and MPL, the criteria for the geomechanical properties are set to differentiate formation strengths at different depths. The threshold for Poisson’s ratio is 0.34, Young’s modulus at 1.6 × 106 psi and the unconfined compressive strength at 2400 psi. The MPL and geomechanical models were generated to predict sanding incident. The results were subsequently validated with artificial neural network using MATLAB. Also, critical wellbore pressure is calculated and acts as a guide to operate outside the sand failure envelope. Thus, the prediction of the weak formation using geomechanical properties has been further established in this study.http://link.springer.com/article/10.1007/s13202-019-00784-5Weak sandMechanical properties logGeomechanical propertiesLogging dataMATLAB |
| spellingShingle | Aliyu Adebayo Sulaimon Lim Lee Teng Modified approach for identifying weak zones for effective sand management Journal of Petroleum Exploration and Production Technology Weak sand Mechanical properties log Geomechanical properties Logging data MATLAB |
| title | Modified approach for identifying weak zones for effective sand management |
| title_full | Modified approach for identifying weak zones for effective sand management |
| title_fullStr | Modified approach for identifying weak zones for effective sand management |
| title_full_unstemmed | Modified approach for identifying weak zones for effective sand management |
| title_short | Modified approach for identifying weak zones for effective sand management |
| title_sort | modified approach for identifying weak zones for effective sand management |
| topic | Weak sand Mechanical properties log Geomechanical properties Logging data MATLAB |
| url | http://link.springer.com/article/10.1007/s13202-019-00784-5 |
| work_keys_str_mv | AT aliyuadebayosulaimon modifiedapproachforidentifyingweakzonesforeffectivesandmanagement AT limleeteng modifiedapproachforidentifyingweakzonesforeffectivesandmanagement |