Numerical RTA in Tight Unconventionals

2021 ◽  
Author(s):  
Mathias Lia Carlsen ◽  
Braden Bowie ◽  
Mohamad Majzoub Dahouk ◽  
Stian Mydland ◽  
Curtis Hays Whitson ◽  
...  
Keyword(s):  
Multiphase Flow ◽  
Water Saturation ◽  
Saturation Pressure ◽  
Element Model ◽  
Production Performance ◽  
Symmetry Element ◽  
Analytical Models ◽  
Finite Conductivity ◽  
Gas Oil ◽  
Water Cut

Abstract We extend the numerically-assisted RTA workflow proposed by Bowie and Ewert (2020) to (a) all fluid systems and (b) finite conductivity fractures. The simple, fully-penetrating planar fracture model proposed is a useful numerical symmetry element model that provides the basis for the work presented in this paper. Results are given for simulated and field data. The linear flow parameter (LFP) is modified to include porosity (LFPꞌ=LFP√φ). The original (surface) oil in place (OOIP) is generalized to represent both reservoir oil and reservoir gas condensate systems, using a consistent initial total formation volume factor definition (Bti) representing the ratio of a reservoir HCPV containing surface oil in a reservoir oil phase, a reservoir gas phase, or both phases. With known (a) well geometry, (b) fluid initialization (PVT and water saturation), (c) relative permeability relations, and (d) bottomhole pressure (BHP) time variation (above and below saturation pressure), three fundamental relationships exist in terms of LFPꞌ and OOIP. Numerical reservoir simulation is used to define these relationships, providing the foundation for numerical RTA, namely that wells: (1) with the same value of LFPꞌ, the gas, oil and water surface rates will be identical during infinite-acting (IA) behavior; (2) with the same ratio LFPꞌ/OOIP, producing GOR and water cut behavior will be identical for all times, IA and boundary dominated (BD); and (3) with the same values of LFPꞌ and OOIP, rate performance of gas, oil, and water be identical for all times, IA and BD. These observations lead to an efficient, semi-automated process to perform rigorous RTA, assisted by a symmetry element numerical model. The numerical RTA workflow proposed by Bowie and Ewert solves the inherent problems associated with complex superposition and multiphase flow effects involving time and spatial changes in pressure, compositions and PVT properties, saturations, and complex phase mobilities. The numerical RTA workflow decouples multiphase flow data (PVT, initial saturations and relative permeabilities) from well geometry and petrophysical properties (L, xf, h, nf, φ, k), providing a rigorous yet efficient and semi-automated approach to define production performance for many wells. Contributions include a technical framework to perform numerical RTA for unconventional wells, irrespective of fluid type. A suite of key diagnostic plots associated with the workflow is provided, with synthetic and field examples used to illustrate the application of numerical simulation to perform rigorous RTA. Semi-analytical models, time, and spatial superposition (convolution), pseudopressure and pseudotime transforms are not required.

Autonomous Inflow Control Valve Multiphase Flow Performance for Light Oil

2021 ◽  
Author(s):  
Soheila Taghavi ◽  
Einar Gisholt ◽  
Haavard Aakre ◽  
Stian Håland ◽  
Kåre Langaas
Keyword(s):  
Multiphase Flow ◽  
Single Phase ◽  
Control Valve ◽  
Oil Reservoirs ◽  
Test Results ◽  
Gas Oil ◽  
Flow Loop ◽  
Light Oil ◽  
Water Cut ◽  
Oil Rim

Abstract Early water and/or gas breakthrough is one of the main challenges in oil production which results in inefficient oil recovery. Existing mature wells must stop the production and shut down due to high gas oil ratio (GOR) and/or water cut (WC) although considerable amounts of oil still present along the reservoir. It is important to develop technologies that can increase oil production and recovery for marginal, mature, and challenging oil reservoirs. In most fields the drainage mechanism is pressure support from gas and/or water and the multiphase flow performance is particularly important. Autonomous Inflow Control Valve (AICV) can delay the onset of breakthrough by balancing the inflow along the horizontal section and control or shut off completely the unwanted fluid production when the breakthrough occurs. The AICV was tested in a world-leading full-scale multiphase flow loop located in Porsgrunn, Norway. Tests were performed with realistic reservoir conditions, i.e. reservoir pressure and temperature, crude oil, formation water and hydrocarbon gas at various gas oil ratio and water cut in addition to single phase performances. A summary of the flow loop, test conditions, the operating procedures, and test results are presented. In addition, how to represent the well with AICVs in a standard reservoir simulation model are discussed. The AICV flow performance curves for both single phase and multiphase flow are presented, discussed, and compared to conventional Inflow Control Device (ICD) performance. The test results demonstrate that the AICV flow performance is significantly better than conventional ICD. The AICV impact on a simplified model of a thin oil rim reservoir is shown and modelling limitations are discussed. The simulation results along with the experimental results demonstrated considerable benefit of deploying AICV in this thin oil rim reservoir. Furthermore, this paper describes a novel approach towards the application of testing the AICV for use within light oil completion designs and how the AICV flow performance results can be utilized in marginal, mature, and other challenging oil reservoirs.

A New Methodology of Production Performance Prediction for Strong Edge-Water Reservoir

2020 ◽  
Vol 143 (8) ◽  
Author(s):  
Angang Zhang ◽  
Zifei Fan ◽  
Lun Zhao ◽  
Jincai Wang ◽  
Heng Song
Keyword(s):  
Performance Prediction ◽  
Water Saturation ◽  
Water Injection ◽  
Material Balance ◽  
Water Reservoir ◽  
Production Performance ◽  
Water Flooding ◽  
Gas Oil ◽  
Permeability Model ◽  
Water Influx

Abstract Material balance is a basic principle in reservoir engineering, which is still used as a quick and easy analytical tool for reservoir evaluation. In this article, a new methodology of production performance prediction for water-flooding reservoir was proposed based on the material balance principle, which considers the water saturation change caused by water injection and natural water influx, and its effect on transient gas–oil ratio. Among them, the cumulative water production was calculated based on Tong’s water-driver performance curve; the cumulative water influx was obtained by the Fetkovitch method; the transient gas–oil ratio can be acquired by Darcy’s law and Baker’s relative permeability model. Comparisons have been made between the new methodology and commercial reservoir simulator for two different reservoirs. The results show that there is good similarity between these two tools, which verifies the correctness of the new methodology.

scholarly journals Structural and Acoustic Responses of a Submerged Stiffened Conical Shell

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Meixia Chen ◽  
Cong Zhang ◽  
Xiangfan Tao ◽  
Naiqi Deng
Keyword(s):  
Conical Shell ◽  
Element Model ◽  
Analytical Models ◽  
Superposition Method ◽  
Far Field ◽  
Fluid Loading ◽  
Low Frequencies ◽  
Structural Responses ◽  
The Individual ◽  
Field Sound

This paper studies the vibrational behavior and far-field sound radiation of a submerged stiffened conical shell at low frequencies. The solution for the dynamic response of the conical shell is presented in the form of a power series. A smeared approach is used to model the ring stiffeners. Fluid loading is taken into account by dividing the conical shell into narrow strips which are considered to be local cylindrical shells. The far-field sound pressure is solved by the Element Radiation Superposition Method. Excitations in two directions are considered to simulate the loading on the surface of the conical shell. These excitations are applied along the generator and normal to the surface of the conical shell. The contributions from the individual circumferential modes on the structural responses of the conical shell are studied. The effects of the external fluid loading and stiffeners are discussed. The results from the analytical models are validated by numerical results from a fully coupled finite element/boundary element model.

A Unified Parameter to Represent Reservoir Heterogeneity

2021 ◽  
Author(s):  
Nandana Ramabhadra Agastya
Keyword(s):  
Water Saturation ◽  
Pressure Ratio ◽  
Universal Method ◽  
Permeability Ratio ◽  
Initial Water ◽  
Vertical Permeability ◽  
Radar Chart ◽  
Horizontal Permeability ◽  
Water Cut ◽  
Thief Zone

Abstract We aim to find a universal method and/or parameter to quantify impact of overall heterogeneity on waterflood performance. For this purpose, we combined the Lorenz coefficient, horizontal permeability to vertical permeability ratio, and thief zone permeability to average permeability ratio, with a radar chart. The area of the radar chart serves as a single parameter to rank reservoirs according to heterogeneity, and correlates to waterflood performance. The parameters investigated are vertical and horizontal permeability. Average porosity, initial water saturation, and initial diagonal pressure ratio are kept constant. Computer based experiments are used over the course of this entire research. We conducted permeability studies that demonstrate the effects of thief zones and crossflow. After normalizing these parameters into a number between 0 and 1, we then plot them on a radar chart. A reservoir's overall degree of heterogeneity can be inferred using the radar chart area procedure discussed in this study. In general, our simulations illustrate that the larger the radar chart area, the more heterogenous the reservoir is, which in turn yields higher water cut trends and lower recovery factors. Computer simulations done during this study also show that the higher the Lorenz coefficient, the higher the probability of a thief zone to exist. Simulations done to study crossflow also show certain trends with respect to under tonguing and radar chart area.

Experimental Characterization of a Flexible Two-Link Manipulator Arm

1993 ◽  
Author(s):  
Randall L. Mayes ◽  
G. Richard Eisler
Keyword(s):  
Element Model ◽  
Input Voltage ◽  
Analytical Models ◽  
Experimental Characterization ◽  
Frequency Range ◽  
Flexible Links ◽  
Beam Elements ◽  
Output Torque ◽  
Manipulator Arm

Abstract Experiments were performed to verify the analytical models for a robotic manipulator with two flexible links. A finite element model (FEM) employing two-dimensional beam elements was used to model the structure. A proportional model relating input voltage to output torque was used for both hub and elbow joint motors. With some minor adjustments to the link stiffness, the FEM modal frequencies matched the experimentally extracted frequencies within 1.5%. However the voltage-torque relationship for the hub motor was found to exhibit dynamics in the frequency range of interest.

Real-Time EM Look-Ahead Resistivity for Mapping of Oil/Water Contact While Drilling at Low Deviated Well, New Perspective for Mature Oil Fields Development: A Case Study Of Umm Gudair Field, Kuwait

2021 ◽  
Author(s):  
Nasser Faisal Al-Khalifa ◽  
Mohammed Farouk Hassan ◽  
Deepak Joshi ◽  
Asheshwar Tiwary ◽  
Ihsan Taufik Pasaribu ◽  
...  
Keyword(s):  
Water Saturation ◽  
High Water ◽  
Carbonate Reservoir ◽  
Water Contact ◽  
Saturation Zone ◽  
Look Ahead ◽  
Production History ◽  
Oil Water ◽  
High Water Cut ◽  
Water Cut

Abstract The Umm Gudair (UG) Field is a carbonate reservoir of West Kuwait with more than 57 years of production history. The average water cut of the field reached closed to 60 percent due to a long history of production and regulating drawdown in a different part of the field, consequentially undulating the current oil/water contact (COWC). As a result, there is high uncertainty of the current oil/water contact (COWC) that impacts the drilling strategy in the field. The typical approach used to develop the field in the lower part of carbonate is to drill deviated wells to original oil/water contact (OOWC) to know the saturation profile and later cement back up to above the high-water saturation zone and then perforate with standoff. This method has not shown encouraging results, and a high water cut presence remains. An innovative solution is required with a technology that can give a proactive approach while drilling to indicate approaching current oil/water contact and geo-stop drilling to give optimal standoff between the bit and the detected water contact (COWC). Recent development of electromagnetic (EM) look-ahead resistivity technology was considered and first implemented in the Umm Gudair (UG) Field. It is an electromagnetic-based signal that can detect the resistivity features ahead of the bit while drilling and enables proactive decisions to reduce drilling and geological or reservoir risks related to the well placement challenges.

Machine Learning and Artificial Intelligence Provides Wolfcamp Completion Design Insight

2021 ◽  
Author(s):  
Robert Shelley ◽  
Oladapo Oduba ◽  
Howard Melcher
Keyword(s):  
Machine Learning ◽  
Water Saturation ◽  
Saturation Pressure ◽  
Ann Model ◽  
Permian Basin ◽  
Treatment Rate ◽  
Feed Forward Neural Network ◽  
Well Production ◽  
Reservoir Type ◽  
The Impact

Abstract The subject of this paper is the application of a unique machine learning approach to the evaluation of Wolfcamp B completions. A database consisting of Reservoir, Completion, Frac and Production information from 301 Multi-Fractured Horizontal Wolfcamp B Completions was assembled. These completions were from a 10-County area located in the Texas portion of the Permian Basin. Within this database there is a wide variation in completion design from many operators; lateral lengths ranging from a low of about 4,000 ft to a high of almost 15,000 ft, proppant intensities from 500 to 4,000 lb/ft and frac stage spacing from 59 to 769 ft. Two independent self-organizing data mappings (SOM) were performed; the first on completion and frac stage parameters, the second on reservoir and geology. Characteristics for wells assigned to each SOM bin were determined. These two mappings were then combined into a reservoir type vs completion type matrix. This type of approach is intended to remove systemactic errors in measuement, bias and inconsistencies in the database so that more realistic assessments about well performance can be made. Production for completion and reservoir type combinations were determined. As a final step, a feed forward neural network (ANN) model was developed from the mapped data. This model was used to estimate Wolfcamp B production and economics for completion and frac designs. In the performance of this project, it became apparent that the incorporation of reservoir data was essential to understanding the impact of completion and frac design on multi-fractured horizontal Wolfcamp B well production and economic performance. As we would expect, wells with the most permeability, higher pore pressure, effective porosity and lower water saturation have the greatest potential for hydrocarbon production. The most effective completion types have an optimum combination of proppant intensity, fluid intensity, treatment rate, frac stage spacing and perforation clustering. This paper will be of interest to anyone optimizing hydraulically fractured Wolfcamp B completion design or evaluating Permian Basin prospects. Also, of interest is the impact of reservoir and completion characteristics such as permeability, porosity, water saturation, pressure, offset well production, proppant intensity, fluid intensity, frac stage spacing and lateral length on well production and economics. The methodology used to evaluate the impact of reservoir and completion parameters for this Wolfcamp project is unique and novel. In addition, compared to other methodologies, it is low cost and fast. And though the focus of this paper is on the Wolfcamp B Formation in the Midland Basin, this approach and workflow can be applied to any formation in any Basin, provided sufficient data is available.

Accurate Evaluation of Bolt and Clamped Members Stiffnesses Of Bolted Joints

2021 ◽  
Author(s):  
Rashique Iftekhar Rousseau ◽  
Abdel-Hakim Bouzid ◽  
Zijian Zhao
Keyword(s):  
Finite Element ◽  
Joint Stiffness ◽  
Element Model ◽  
Fe Analysis ◽  
Bolted Joints ◽  
Analytical Models ◽  
Fe Modeling ◽  
Bolted Joint ◽  
A New Technique ◽  
External Loads

Abstract The axial stiffnesses of the bolt and clamped members of bolted joints are of great importance when considering their integrity and capacity to withstand external loads and resist relaxation due to creep. There are many techniques to calculate the stiffnesses of the joint elements using finite element (FE) modeling, but most of them are based on the displacement of nodes that are selected arbitrarily; therefore, leading to inaccurate values of joint stiffness. This work suggests a new method to estimate the stiffnesses of the bolt and clamped members using FE analysis and compares the results with the FE methods developed earlier and also with the existing analytical models. A new methodology including an axisymmetric finite element model of the bolted joint is proposed in which the bolts of different sizes ranging from M6 to M36 are considered for the analysis to generalize the proposed approach. The equivalent bolt length that includes the contribution of the thickness of the bolt head and the bolt nominal diameter to the bolt stiffness is carefully investigated. An equivalent bolt length that accounts for the flexibility of the bolt head is proposed in the calculation of the bolt stiffness and a new technique to accurately determine the stiffness of clamped members are detailed.

A Cognitive Data-Driven Single-Well Modeling Workflow for Reservoir Deliverability Predictions – Expanding the Wireline Formation Tester Application Envelope

2021 ◽  
Author(s):  
Abdul Bari ◽  
Mohammad Rasheed Khan ◽  
M. Sohaib Tanveer ◽  
Muhammad Hammad ◽  
Asad Mumtaz Adhami ◽  
...  
Keyword(s):  
Reservoir Characterization ◽  
Production Performance ◽  
Data Driven ◽  
Analytical Models ◽  
Production Model ◽  
Reservoir Evaluation ◽  
Fluid Properties ◽  
Petrophysical Model ◽  
Single Well ◽  
Data Driven Approach

Abstract In today's dynamically challenging E&P industry, exploration activities demand for out-of-the-box measures to make the most out of the data available at hand. Instead of relying on time consuming and cost-intensive deliverability testing, there is a strong push to extract maximum possible information from time- and cost-efficient wireline formation testers in combination with other openhole logs to get critical reservoir insight. Consequently, driving efficiency in the appraisal process by reducing redundant expenditures linked with reservoir evaluation. Employing a data-driven approach, this paper addresses the need to build single-well analytical models that combines knowledge of core data, petrophysical evaluation and reservoir fluid properties. Resultantly, predictive analysis using cognitive processes to determine multilayer productivity for an exploratory well is achieved. Single Well Predictive Modeling (SWPM) workflow is developed for this case which utilizes plethora of formation evaluation information which traditionally resides across siloed disciplines. A tailor-made workflow has been implemented which goes beyond the conventional formation tester deliverables while incorporating PVT and numerical simulation methodologies. Stage one involved reservoir characterization utilizing Interval Pressure Transient Testing (IPTT) done through the mini-DST operation on wireline formation tester. Stage two concerns the use of analytical modeling to yield exact solution to an approximate problem whose end-product is an estimate of the Absolute Open Flow Potential (AOFP). Stage three involves utilizing fluid properties from downhole fluid samples and integrating with core, OH logs, and IPTT answer products to yield a calibrated SWPM model, which includes development of a 1D petrophysical model. Additionally, this stage produces a 3D simulation model to yield a reservoir production performance deliverable which considers variable rock typing through neural network analysis. Ultimately, stage four combines the preceding analysis to develop a wellbore production model which aids in optimizing completion strategies. The application of this data-driven and cognitive technique has helped the operator in evaluating the potential of the reservoir early-on to aid in the decision-making process for further investments. An exhaustive workflow is in place that can be adopted for informed reservoir deliverability modeling in case of early well-life evaluations.

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