Preparation of Sodalite and Faujasite Clay Composite Membranes and Their Utilization in the Decontamination of Dye Effluents

The present work describes the deposition of two zeolite films, sodalite and faujasite, by the hydrothermal method to tune the mesopores of clay support, which are prepared from a widely available clay depot from the central region of Morocco (Midelt). The clay supports were prepared by a powder metallurgy method from different granulometries with activated carbon as a porosity agent, using uniaxial compression followed by a sintering process. The 160 µm ≤ Φ ≤ 250 µm support showed the highest water flux compared to the supports made from smaller granulometries with a minimum water flux of 1405 L.m−2·h−1 after a working time of 2 h and 90 min. This support was chosen for the deposition of sodalite (SOM) and faujasite (FAM) zeolite membranes. The X-ray diffraction of sodalite and faujasite showed that they were well crystallized, and the obtained spectra corresponded well with the sought phases. Such findings were confirmed by the SEM analysis, which showed that SOM was crystalized as fine particles while the FAM micrographs showed the existence of crystals with an average size ranging from 0.53 µm to 1.8 µm with a bipyramidal shape and a square or Cubo octahedral base. Nitrogen adsorption analysis showed that the pore sizes of the supports got narrowed to 2.28 nm after deposition of sodalite and faujasite. The efficiencies of SOM and FAM membranes were evaluated by filtration tests of solutions containing methyl orange (MO) using a flow loop, which were developed for dead-end filtration. The retention of methylene orange (MO) followed the order: SOM > FAM > 160 µm ≤ Φ ≤ 250 µm clay support with 55%, 48% and 35%, respectively. Size exclusion was the predominant mechanism of filtration of MO through SOM, FAM, and the support. However, the charge repulsion between the surface of the membrane and the negatively charged MO have not been ruled out. The point of zero charge (pzc) of the clay support, SOM and FAM membrane were pHpzc = 9.4, pHpzc = 10.6, and pHpzc = 11.4, respectively. Filtrations of MO were carried out between pH = 5.5 and pH = 6.5, which indicated that the surface of the membranes was positively charged while MO was negatively charged. The interaction of MO with the membranes might have happened through its vertical geometry.

Development of an Approach for Determining the Effectiveness of Inhibition of Paraffin Deposition on the Wax Flow Loop Laboratory Installation

The formation of wax deposits is a common phenomenon in the production and transportation of formation fluids. On the territory of the Perm Krai, this problem occurs in half of the mining funds. One of the most common and promising methods of dealing with these deposits is the use of inhibitor regents. The most popular technique for assessing the effectiveness of a wax inhibitor is the «Cold Finger», which has a number of significant drawbacks. This work presents a number of methods for assessing the effectiveness of inhibition of paraffin formation on the laboratory installation «WaxFlowLoop». A number of laboratory studies have been carried out to determine the effectiveness of a paraffin deposition inhibitor for inhibiting the paraffin formation process of four target fluids. Verification of the obtained values was carried out by comparing them with the field data. As a result of laboratory studies, it was found that the value of the inhibitor efficiency, determined by the «Cold Finger» method, differs from the field data by an average of 2 times. At the same time, the average deviation of the results determined at the «WaxFlowLoop» installation from the field data is 8.1%. The correct selection of a paraffin deposition inhibitor and its dosage can significantly increase the inter-treatment period of the well, thereby reducing its maintenance costs and increasing the efficiency of well operation.

Scaling Formulae for the Wellbore Hydraulics Similitude with Drill Pipe Rotation and Eccentricity

Equivalent circulation density of the fluid circulation system in drilling rigs is determined by the frictional pressure losses in the wellbore annulus. Flow loop experiments are commonly used to simulate the annular wellbore hydraulics in the laboratory. However, proper scaling of the experiment design parameters including the drill pipe rotation and eccentricity has been a weak link in the literature. Our study uses the similarity laws and dimensional analysis to obtain a complete set of scaling formulae that would relate the pressure loss gradients of annular flows at the laboratory and wellbore scales while considering the effects of inner pipe rotation and eccentricity. Dimensional analysis is conducted for commonly encountered types of drilling fluid rheology, namely, Newtonian, power-law, and yield power-law. Appropriate dimensionless groups of the involved variables are developed to characterize fluid flow in an eccentric annulus with a rotating inner pipe. Characteristic shear strain rate at the pipe walls is obtained from the characteristic velocity and length scale of the considered annular flow. The relation between lab-scale and wellbore scale variables are obtained by imposing the geometric, kinematic, and dynamic similarities between the laboratory flow loop and wellbore annular flows. The outcomes of the considered scaling scheme is expressed in terms of closed-form formulae that would determine the flow rate and inner pipe rotation speed of the laboratory experiments in terms of the wellbore flow rate and drill pipe rotation speed, as well as other parameters of the problem, in such a way that the resulting Fanning friction factors of the laboratory and wellbore-scale annular flows become identical. Findings suggest that the appropriate value for lab flow rate and pipe rotation speed are linearly related to those of the field condition for all fluid types. The length ratio, density ratio, consistency index ratio, and power index determine the proportionality constant. Attaining complete similarity between the similitude and wellbore-scale annular flow may require the fluid rheology of the lab experiments to be different from the drilling fluid. The expressions of lab flow rate and rotational speed for the yield power-law fluid are identical to those of the power-law fluid case, provided that the yield stress of the lab fluid is constrained to a proper value.

A Novel and Sustainable Generation of Advanced Mud Gas Logging System for Managed Pressure Drilling Applications: An Explorative Well Deployment from North Germany

Summary In the high risk Managed Pressure Drilling operations, increased certainty given by Mud Logging is a critical deliverable to guarantee a safe drilling environment even under challenging conditions and, to provide the first indications for reservoir evaluation. This paper describes a novel product application that successfully obtains advanced mud gas data from a Managed Pressure Drilling environment, proven in flow-loop and field applications (in Lower Saxony, Germany), by reducing service footprint as well as power consumption.

Development of a Methodology and Software Package for Predicting the Formation of Organic Deposits Based on the Results of Laboratory Studies

One of the main problems in the oil industry is the fallout of asphaltene–resin–paraffin deposits (ARPDs) during oil production and transportation. The formation of organic deposits leads to reduced equipment life and reduced production. Currently, there is no single methodology for the numerical simulation of the ARPD dropout process. The aim of our work was to obtain a correlation dependence characterizing the rate of wax growth over time for oils in the Perm Krai, depending on temperature, pressure, and speed conditions. Experimental data for 20 oil samples were obtained using a Wax Flow Loop installation that simulates fluid movement in tubing. The developed correlation was tested in 154 wells. The results of numerical modeling of the paraffin precipitation process made it possible to correct the inter-treatment period of scraping for 109 wells (71%), indicating the high accuracy of the developed approach.

Novel In-Line Inspection Tool for Deposit Characterization in Pipelines

Deposition formation inside pipelines is a major and growing problem in the oil and gas industry. The optimal use of prevention and remediation tools such as chemical inhibitors and cleaning processes could lead to major savings due to minimized production problems and optimized pipe cleaning costs. This requires characterization and quantification of the actual deposits inside pipelines and downholes. Recently, a novel deposition inline inspection sensor moving inside the pipeline has been proposed based on "inside-out" electrical tomography. In this sensor, the distribution of electrical properties between the sensor and the pipe wall are estimated based on measurements carried out using electrodes around the sensor. In this study, the next generation sensor moving inside the pipeline is described and a deep neural network based approach to deposit estimation is introduced. Test results from a 70 m long semi-industrial scale flow loop containing paraffin wax and calcium carbonate deposits of different thicknesses are shown. Challenges include the changing position and orientation of the sensor during the low. The results show that the sensor is able to measure both deposit thickness and type with good accuracy which indicates that the sensor is suitable for industrial use. Accurate knowledge about deposits allows future blockage prevention, detecting build-up locations in the early phase, increasing accuracy of multi-phase flow and deposition models, optimization of chemical use and validation of deposit cleaning tools before integrity campaigns leading to overall reduced pipeline operation costs.

Application of Machine Learning Classification Algorithms for Two-Phase Gas-Liquid Flow Regime Identification

This research aims to identify the best machine learning (ML) classification techniques for classifying the flow regimes in vertical gas-liquid two-phase flow. Two-phase flow regime identification is crucial for many operations in the oil and gas industry. Processes such as flow assurance, well control, and production rely heavily on accurate identification of flow regimes for their respective systems' smooth functioning. The primary motivation for the proposed ML classification algorithm selection processes was drilling and well control applications in Deepwater wells. The process started with vertical two-phase flow data collection from literature and two different flow loops. One, a 140 ft. tall vertical flow loop with a centralized inner metal pipe and a larger outer acrylic pipe. Second, an 18-ft long flow loop, also with a centralized, inner metal drill pipe. After extensive experimental and historical data collection, supervised and unsupervised ML classification models such as Multi-class Support vector machine (MCSVM), K-Nearest Neighbor Classifier (KNN), K-means clustering, and hierarchical clustering were fit on the datasets to separate the different flow regions. The next step was fine-tuning the models' parameters and kernels. The last step was to compare the different combinations of models and refining techniques for the best prediction accuracy and the least variance. Among the different models and combinations with refining techniques, the 5- fold cross-validated KNN algorithm, with 37 neighbors, gave the optimal solution with a 98% classification accuracy on the test data. The KNN model distinguished five major, distinct flow regions for the dataset and a few minor regions. These five regions were bubbly flow, slug flow, churn flow, annular flow, and intermittent flow. The KNN-generated flow regime maps matched well with those presented by Hasan and Kabir (2018). The MCSVM model produced visually similar flow maps to KNN but significantly underperformed them in prediction accuracy. The MCSVM training errors ranged between 50% - 60% at normal parameter values and costs but went up to 99% at abnormally high values. However, their prediction accuracy was below 50% even at these highly overfitted conditions. In unsupervised models, both clustering techniques pointed to an optimal cluster number between 10 and 15, consistent with the 14 we have in the dataset. Within the context of gas kicks and well control, a well-trained, reliable two-phase flow region classification algorithm offers many advantages. When trained with well-specific data, it can act as a black box for flow regime identification and subsequent well-control measure decisions for the well. Further advancements with more robust statistical training techniques can render these algorithms as a basis for well-control measures in drilling automation software. On a broader scale, these classification techniques have many applications in flow assurance, production, and any other area with gas-liquid two-phase flow.

First Use of Novel High Temperature Water-Based Reservoir Drilling Fluid to Access Depleted Deepwater Reserves

A combination of divalent base brine and high wellbore temperature presents significant challenges for high density aqueous reservoir drilling fluids. Such systems traditionally use biopolymers as viscosifiers; however, they are subject to degradation at elevated temperatures. Non-aqueous drilling fluids are thermally stable but complete removal of the filtercake is challenging and this can lead to formation damage. This paper describes the qualification and first deepwater drilling application of a unique aqueous reservoir drilling fluid at temperatures above 320°F. A high-temperature divalent brine-based reservoir drilling fluid (HT-RDF) and a solids-free screen running fluid (SF-SRF) were designed, both utilizing the same novel synthetic polymer technology. Calcium bromide brine was selected for use to minimize the total amount of acid-soluble solids in the drilling fluid. A comprehensive qualification was undertaken examining parameters such as rheology performance across a range of temperatures, long-term stability, fluid loss under expected and stress conditions (16 hours at 356°F), production screen test (PST), and various fluid-fluid compatibility tests. Return permeability tests were conducted on the final formulations to validate their suitability for use. The synthetic polymer technology provided excellent rheology, suspension, and fluid loss control in the fluid systems designed in the laboratory. To prepare for field execution multiple yard mixes were performed to verify the laboratory results on a larger scale. Additionally, a flow loop system was utilized to evaluate fluid performance under simulated downhole temperature and pressure conditions before field deployment. The final high temperature drilling fluid as designed provided rheological properties that met the necessary equivalent circulating density (ECD) requirements while drilling the reservoir. The fluid loss remained extremely stable and there were no downhole losses despite the depleted nature of the wellbore. Production screens were run straight to total depth (TD) with no wellbore stability issues after a three-day logging campaign. High temperature aqueous reservoir drilling fluids have historically been limited by the lack of suitable viscosifiers and fluid loss control additives. This paper outlines the design, mixing and logistical considerations and field execution of a novel polymer-based reservoir drilling fluid.