A New Approach to Barrier Verification

Objectives/Scope Verification and testing of a wellbore barrier, in older assets has proven to be challenging. Even more so when the well has structural issues, indemnities or weak spots in the barrier envelope, that limits the possibility to get a positive pressure verification of the barrier with an applied surface pressure. The paper will air on the operational use of this novel test method and the tools used, to allow an in well verification of any type of barrier to secure the well for a repair or a upcoming P/A operation. A pilot job case history will be included to illustrate use of the principles. Methods, Procedures, Process Find a suitable location with necessary support and strength in the well. If installing a mechanical barrier by means of a bridge plug as the primary barrier, we will monitor the installation forces in the anchoring and sealing sequence. This individual signature will be verified towards a nominal base line signature towards a library of thousands of collected installation profiles. Any abnormality can trigger a release and possible relocating of the barrier. A second verification barrier will then be installed above the primary barrier. When both installation signatures are accounted for, we can pressure test the installed barriers. This is done with a pressure inflow tool, where we introduce a calculated predetermined pressure drop between the installed primary barrier and the verification barrier. By monitoring this pressure alteration vs. the pressure above the verification barrier, we can determine if we have a verified barrier. Results, Observations, Conclusions We now have the Primary Barrier verified in the direction of flow (negative pressure test). And verification barrier as the secondary barrier (verified with a positive pressure test). If a dual barrier is requested, you can leave the verification barrier as secondary barrier. Novel/Additional Information Pressure manipulation is done with existing and proven technology and is re-usable after re-setting at surface. By monitoring this pressure alteration, we can verify the installed primary and verification barrier in one run. This without any time-consuming pressure manipulating from surface.

Demonstration and Optimization of Floor Height of 220kV GIS Room in the Indoor Substation

With the development of cities, the construction of indoor substations and the use of gas insulated switchgear (GIS equipment) are becoming more and more widespread. In this paper, the height of 220kVGIS room in the indoor substation is demonstrated and optimized. On the basis of the collection and analysis of the basic data of each major equipment manufacturer, the height of GIS room is analysed from the expansion, maintenance needs and pressure test, which are two limiting factors. Finally, the optimal height of 220kVGIS room is determined.

Machine Learning for Formation Tightness Prediction and Mobility Prediction

From the perspective of wireline formation test (WFT), formation tightness reflects the "speed" of pressure buildup while the pressure test is being conducted. We usually define a pressure test point that has a very low pressure-buildup speed as a tight point. The mobility derived from this kind of pressure point is usually less than 0.01md/cP; otherwise, the pressure points will be defined as valid points with valid formation pressure and mobility. Formation tightness reflects the formation permeability information and can be an indicator to estimate the difficulty of the WFT pumping and sampling operation. Mobility, as compared to permeability, reflects the dynamic supply capacity of the formation. A rapid and good mobility prediction based on petrophysical logging can not only directly provide valid formation productivity but can also evaluate the feasibility of the WFT and doing optimization work in advance. Compared to a time-consuming and costly drillstem test (DST) operation, the WFT is the most efficient and cost-saving method to confirm hydrocarbon presence. However, the success rate of WFT sampling operations in the deep Kuqa formation is less than 50% overall, mostly due to the formation tightness exceeding the capability of the tools. Therefore, a rapid mobility evaluation is necessary to meet WFT feasibility analysis. As companion work to a previous WFT optimization study(SPE-195932-MS), we further studied and discuss the machine learning for mobility prediction. In the previous study, we formed a mobility prediction workflow by doing a statistical analysis of more than 1000 pressure test points with several statistical mathematic methods, such as univariate linear regression (ULR), multivariate linear regression (MLR), neural network regression analysis (NNA), and decision tree classification analysis (DTA) methods. In this paper, the methods and principles of machine learning are expounded. A series of machine learning methods were tested. The algorithms that are appropriate for these specific data set were selected. Includes DTA, discriminant analysis (DA), logistic regression, support vector machine (SVM), K-nearest neighbor (KNN) for formation tightness prediction and linear regression, DTA, SVM, Gaussian process regression SVM, random tree, neural network analysis for mobility prediction. Contrastive analysis reveals that: The SVM classifier has the best result over other methods for formation tightness probability prediction. Based on R squared and RMSE analysis, linear regression, GPR, and NNA delivered relatively good results compared with other mobility prediction methods. An optimized data processing workflow was proposed, and it delivered a better result than the workflow proposed in SPE-195932-MS under the same training and testing dataset condition. The comparison between measured mobility and predicted mobility results reveals that, in most situations, the predicted mobility and measured mobility matched very well with each other. WFT were conducted in newly drilled wells. Sampling success rate also achieved 100% in these wells by optimizing the WFT tool string and sampling stations selection in advance, and NPT is significantly reduced.

The Anti-Arthritic Efficacy of Khellin Loaded in Ascorbyl Decanoate Nanovesicles after an Intra-Articular Administration

Osteoarthritis is the most widespread joint-affecting disease. The management of persistent pain remains inadequate and demands new therapeutic strategies. In this study, we explored the pain relieving and protective properties of a single intra-articular (i.a.) injection of khellin loaded in nanovesicles (K-Ves) based on ascorbyl decanoate plus phosphatidylcholine in a rat model of osteoarthritis (OA) induced by monosodium iodoacetate (MIA) treatment. The developed nanovesicles (approximately 136 nm) had a narrow size distribution (PdI 0.26), a good recovery (about 80%) and a worthy encapsulation efficiency (about 70%) with a ζ-potential of about −40 mV. The stability of K-Ves was assessed in simulated synovial fluid. Seven days after the articular damage with MIA, both K-Ves and a suspension of khellin (K, 50 μL) were i.a. injected. K-Ves significantly counteracted MIA-induced hypersensitivity to mechanical noxious (paw pressure test) and non-noxious stimuli (von Frey test) and significantly reduced the postural unbalance related to spontaneous pain (incapacitance test) and the motor alterations (beam balance test) 7 and 14 days after the i.a. injection. K was partially active only on day 7 after the treatment. The histology emphasized the improvement of several morphological factors in MIA plus K-Ves-treated animals. In conclusion, K-Ves could be successfully used for the local treatment of osteoarthritis.

Effects of diaphragmatic control on multiparametric analysis of the sniff nasal inspiratory pressure test and inspiratory muscle activity in healthy subjects

Background We investigated the influence of diaphragmatic activation control (diaphC) on the relaxation rate, contractile properties and electrical activity of the inspiratory muscles of healthy subjects. Assessments were performed non-invasively using the sniff inspiratory pressure test (SNIP) and surface electromyography, respectively. Methods Twenty-two subjects (10 men and 12 women) performed 10 sniff maneuvers in two different days: with and without diaphC instructions. For the SNIP test with diaphC, the subjects were instructed to perform intense activation of the diaphragm. The tests with the best SNIP values were used for analysis. Results The maneuver with diaphC when compared to the maneuver without diaphC exhibited significant lower values for: SNIP (p <0.01), maximum relaxation rate (MRR) (p <0.01), maximum rate of pressure development (MRPD) (p <0.01), contraction times (CT) (p = 0.02) and electrical activity of the sternocleidomastoid (SCM) (p <0.01), scalene (SCL) (p = 0.01) and intercostal (CI) (p = 0.03) muscles. In addition, the decay constant (tau, τ) and relaxation time (½ RT) did not present any changes. Conclusion The diaphragmatic control performed during the SNIP test influences the inspiratory pressure and the contractile properties of inspiratory muscles. This occurs due to changes in the pattern of muscle recruitment, which change force velocity characteristics of the test. Thus, instruction on diaphC should be encouraged for better performance of the SNIP test and for evaluation targeting the diaphragm muscle activity.

Inspection Method of Finned Tube and Finned Heat Exchanger

The finned tube heat exchanger is one of the earliest and most successful discoveries in the process of improving tube heat exchange. This method is still the most widely used of all kinds of tube heat transfer surface enhancement heat transfer methods. It is not only suitable for single-fin tube heat exchangers, which are widely used in power, chemical, petrochemical, air-conditioning engineering and refrigeration engineering. Conventional heat exchanger with smooth tubes can be inspected through the pressure test during the manufacturing process. Finned tubes and finned heat exchangers with inner thread structure have some difficult to pass the water pressure test. The same situation exists in regular inspections. Due to structural reasons, it is difficult to carry out regular surface inspections[1]. For these two situations, two different testing methods are required to ensure quality. This article introduces in detail the methods of inspecting finned tubes and finned heat exchangers. Hierarchical comparison of alternatives in hydrostatic testing project, and the eddy current detection technology of the finned tube under the condition of in-service air cooling. The far-field eddy current method is chosen for inspection. And by comparing the standard sample tube, it is mainly used to adjust the sensitivity of the eddy current detector and ensure the accuracy of the test results[2]. The results show that the eddy current detection technology can be more accurate and reliable. The corrosion of the finned tube under service air cooling is detected, and a reliable basis is provided for judging the use of the finned tube and finned heat exchanger[3].