bluuebunny/crossref_metadata_2025 huggingface dataset:
Enabling WITSML Stream Analytics Through Open Source Big Data Technologies
Authors: Pisauri Federico , Escudero Fernando , Rodriguez Pedro Emilio
Published: July 2020

This work presents a set of interconnected open source big data technologies through an example case to demonstrate the processes used to generate, process, store, and consume real-time wellsite information transfer standard markup language (WITSML) data from drilling and completions (D&C) operations. The new proposed approach to manage real-time data is based on the use of distributed storage and processing technologies to simultaneously analyze large volumes of information, previously considered only on an individual well basis. This new approach leverages the open source technology available in the market to target the gathering of the data, its secure database storage, and its future processing in a single workflow, to obtain the most value added from the oilfield-generated data during D&C operations. This work presents a set of big data tools and their application.

For this case study, a dynamic, open, easily configurable, and fully scalable work environment was obtained. Open source big data technologies prove to be different when handling operations data, as compared to traditional technologies. Traditional technologies typically require several manual inputs and configurations to enter the data. Data models for these technologies are usually closed or proprietary, and the provided visualizations are limited either to single well analysis or to basic analytical dashboards. The technologies used for this case fully enable data input and storage, as well as allow the generation and real-time deployment of machine learning and data science algorithms and models.

As a different approach, this paper introduces the use of big data architectures for the D&C business to obtain better results for gathering, storing, and analyzing real-time information than the business has traditionally achieved.
Importance of the Hygienic Measuring of Levels of Exposure to Benzene and Its Derivatives in Production Activities, Focused on Preventing Occupational Diseases
Authors: Gómez Real Carlos , Cárdenas Villalobos Oscar
Published: July 2020

Since exposure to Volatile Organic Vapors (Benzene, Toluene and Xylene - BTX) produces serious short- and long-term neurotoxic and hematological effects in individuals, this work focuses on reducing both the incidence and prevalence of occupational diseases associated with exposure to organic vapors by implementing prevention programs.

Hygienic measurements are made periodically, the results of which are essential for establishing guidelines for the different controls, thus eliminating or substantially reducing exposure. The NIOSH 1501 and OSHA 7 methods for measuring exposure to BTX were employed for collecting information at the worksites and its subsequent analysis. This study was conducted at different petroleum production fields in the Llanos Orientales basin in Colombia, based on a prior characterization of the crude (semi-heavy crude oil) and for certain positions determined according to the degree of exposure.

The comparison between permissible limits, the range of exposure and the periodic medical examinations of those exposed determine the measures to be taken to reduce the risk to employees. Personnel exposed to BTX organic vapors in the production areas, laboratories and crude loading racks are classified in a minimum exposure range.

During the 4 years of studies there have been no cases of incidence or prevalence of associated occupational disease, nor have case studies been detected in the annual occupational medical exams.

Implementing engineering measures in the workplaces has helped to maintain control of this danger and lessen the likelihood of worker exposure. This shows that the prior engineering designs and implementation of procedures supported with hygienic measurements are the best prevention tools for a major risk in oil production.
Data Boosted Stuck Pipe Prevention: Integrating Machine Learning Models into the Mud Plan Design Workflow
Authors: Berdugo Arias Carlos Andrés , León Torrado Angie Tatiana , Llano Carvajal Juan Sebastián
Published: July 2020

The main objective of this project is to develop a model that, based on the data of previously drilled wells, allows the user to evaluate the mud plan and identify the probability of a stuck pipe event occurrence. This is done, by using statistical predictive models, particularly in this case, neural network models.

The proposed model takes the input data from the Volve’s dataset. The process starts with the pre-processing of more than 24.000 rows of data from the daily drilling operation reports of 30 wells. The pre-processing of the data consists of identifying the cases where the operation ran across a section successfully or when it resulted in a stuck pipe event. Depending on whether there is or not a stuck pipe event, each row will be classified indicating the chance that a stuck pipe event occurs based on the geological and the operational conditions.

In order to ease the processing of the 24.000 rows, the project workflow implements a Natural Language Processing model, which, based on an initial dataset of 1.200 rows, reads the remaining 22.800 identifying whether the row content is relevant or not for stuck pipe identification. Once all the rows are processed, the rows which represent a stuck pipe event, and those who identify a clean operation run are selected and integrated into the final dataset.

Once the data is processed, the resulting dataset consists of around 600 rows. After some data transformation, this dataset will be the input for the neural network model in the training and validation phases. Once the model is built, the model is tested with the validation dataset in order to evaluate its accuracy.

The trained model shows high accuracy, higher than 84% on the test data. After the model is trained and validated, it’s implemented into a frontend which will serve as the front user interface where he can upload the mud plan parameters, and obtain a stuck pipe event chance evaluation. Having these results, the user can improve the mud plan in order to reduce the chance that an event of this type occurs.

The main advantage of this methodology is that it allows to include historical data from the other drilled wells, this way, boosting the mud plan design with real data and reducing the chances that a stuck pipe event, that account for a high percentage of NPT’s during drilling operations occur. Also, by the use of these statistical models, applied to a specific field, it will allow to intrinsically take into account variables such as geomechanics properties in the model.
Evaluation of the Performance of Thermal EOR Processes in Fractured Shale Oil Formations
Authors: Sarkar Prakhar , Moridis George J. , Blasingame Thomas A.
Published: July 2020

The objective of this study is to analyze and describe quantitatively the effectiveness of thermal EOR processes in increasing production from multi-fractured unconventional resources such as shale oil and tight sand reservoirs. The study evaluates the efficacy of circulation of hot fluids at different temperatures through dedicated unperforated wells in a process that involves direct heat injection without the concurrent injection of fluids that could cause problems of excessive pressures and adverse relative permeability regimes in these ultra-low-permeability (ULP) systems.

In this numerical simulation study, a modified version of the TOUGH+ compositional simulator is used to represent (a) the flow of heat by all possible transport mechanisms and (b) the flow of the three phases routinely involved in these ULP reservoirs. The simulation domain is a stencil, i.e., the minimum 3D repeatable element of a hydraulically-fractured unconventional reservoir, and is discretized using a high-definition (to a mm-scale) grid. The solutions associated with different thermal treatments are compared to a reference case that involves a simple, non-isothermal depressurization-induced production. The rate and composition of the production stream, as well as the spatial distributions of pressure, temperature, phase saturations, viscosities and relative permeabilities is continuously monitored during the simulation process.

This high-resolution 3D study simultaneously considers all thermophysical processes that are affected by the changes in pressure and temperature involved during these thermal EOR operations in ULP reservoirs, as well as their evolution over time: fluid flow, heat flow and transport by conduction and advection, phase density and viscosity, gas solubility in the liquid phases, phase changes and phase production rates. The study captures in detail phenomena that can be easily attenuated in coarser grids. An important contribution of this study is a detailed analysis of the various aspects of production affected by a thermal process as well as the quantification of mass and energy balance, as well as the associated losses. The results of the study indicate that thermal processes (even ones that involve long heating periods) lead to increases in hydrocarbon recovery that (a) are practically negligible to minor even under ideal conditions (under which heat losses are disregarded) and (b) cannot even begin to compensate for the significant energy needs of these methods. The major contribution of this study is that it provides documented evidence of, and sufficient quantitative information on, the ineffectiveness of thermal processes as possible EOR methods, thus reducing them in priority (if not eliminating them from further consideration altogether) as a viable EOR option.
Pressure Behavior During Injectivity Tests - A Composite Reservoir Approach
Authors: L. F. Bittencourt Neto Jessica , Vieira Bela Renan , Pesco Sinesio , Barreto Abelardo
Published: July 2020

Injectivity testing is a procedure used by the oil industry whose purpose, when injecting a fluid, is to obtain information about the characteristics of an oil reservoir. Such characteristics can be estimated from the pressure response obtained during the test. This work presents a solution to the well pressure during an injectivity test, considering a piston flow, using a radially composed reservoir model. It is considered that the reservoir may have a two-phase flow with two regions (water and oil) or three regions. In this case it is considered that the region near the well represents a damaged zone (skin zone). From the known analytical solution for pressure in the Laplace space, it is possible to use a matrix representation of the problem the well pressure calculation. With the aid of Stehfest algorithm, it is possible to perform the numerical inversion of the solution to the real field. From this problem, it was possible to develop a code that simulates the injectivity test and the pressure behavior over time.
Innovative Technologies Drive Benchmark Performance Drilling Challenging Caipipendi Block in Bolivia
Authors: Bertarelli Mario , Duran Romulo , Tocantins João Pedro , Mendoza Diego , Bijai Rahul , Trunk Philip , Villegas Cesar , Ramos Aldo
Published: July 2020

As part of an exploration campaign in the Sub Andean region in Bolivia, Repsol faced a unique challenge to reduce well construction costs while drilling through harsh and abrasive Caipipendi Block formations. The Caipipendi Block poses several drilling challenges that often lead to premature bit and underreamer cutting structure damage. Two main points were targeted as fundamental to accomplish this objective: reduce the number of runs to drill the Carboniferous section and improve borehole enlargement efficiency. A multidisciplinary group comprising a service company and Repsol team members conducted a detailed and thorough investigation of previous failure modes to identify an integrated approach to improve the performance. Along with offset history, the team was able to identify lithology characteristics to accurately diagnose the underlying root causes. To tackle the hard and abrasive Upper Carboniferous section, a customized polycrystalline diamond compact (PDC) drill bit was equipped with 3-D cutter (3DC) technology and powered by a combination of an enhanced power section and a robust rotary steerable system (RSS) tool with a new specific steering pad feature. A new reamer concept was also applied in this well to mitigate the anticipated drilling shock and vibration associated with underreaming through the challenging strata—without compromising drilling efficiency. To achieve the desired performance goals, 3DC elements were applied to the drill bit, along with a robust RSS designed with a pioneering steering pad developed to sustain performance in high levels of formation abrasiveness. To increase borehole enlargement efficiency in the Devonian section, a new cutter block was designed. An advanced 4D transient drillstring dynamics modeling package was used to analyze failure modes, design the reamer and drill bit cutting structures, predict the drilling dynamics of drill bit and reamer, and recommend drilling parameters for the run. The objective was successfully achieved where Repsol was able to set a new benchmark for the block, drilling the programmed depth of the well in 350 days, 17% less than AFE curve and 25% less compared with the best result in the block even with a significant change in lithology sequence from the program. The innovative 3DC technology boosted overall drilling performance. The new PowerDrive* rotary steerable system pads enabled the customized drill bit to drill farther and avoid unexpected bottomhole assembly (BHA) trips. The use of a new cutter block equipped with 3DC technology enhanced stability and reduced lateral displacement and vibration.
Establishing Limits for Brine Discharge Dispersion in Offshore Operation
Authors: Mota Pedro Henrique , Damasceno Marcelo Maia , Da Silveira Neto Aristeu , Vedovoto João Marcelo , Marinho Leonardo , Pamphili Cristiano , Samsoni Umberto , Waldmann Alex , Martins André Leibsohn
Published: July 2020

A study of saline fluids discharge from offshore activities was performed through the modeling and numerical simulation of the advective and diffusive transport of discharged brines. In order to solve the fluid dynamic equations, the turbulence closure model used was the dynamic subgrid-scale (SGS) model of Germano, a Large Eddy Simulation (LES) method, implemented in the MFSim software. In addition, the scalar transport equation was considered to obtain a spatial and temporal distribution of salinity in the ocean after brine discharge. Furthermore, the adaptive mesh refinement (AMR) method was considered to refine regions of interest and, consequently, reduce numerical costs. The effects of brine discharge were evaluated considering the brine content, discharge flow rate and different scenarios of ocean currents. The methodology assisted in achieving precise results of the advective and diffusive transport of the plume under different operating conditions and observing detailed aspects of this phenomenon. The results were analyzed considering restrictions imposed by environmental protection agencies. As a result, the importance of evaluating operating conditions was observed in order to control environmental impacts since different operating conditions could lead to different fluid dynamic characteristics at farther distance from the discharge point.
Low Salinity Water Injection Optimization in the Namorado Field Using Compositional Simulation and Artificial Intelligence
Authors: Mercado Sierra Diana , Alvarez Rojas Argenis , Salazar Araque Victor
Published: July 2020

This work aims to optimize the development plan involving Low Salinity Water Injection – LSWI for the Namorado Field (located in the Campos basin in Brazil). Multiple mechanisms have been proposed in the literature to represent LSWI, mechanisms that we are going to discuss in this paper. Additionally, it will be studied the impact to evaluate multiple geostatistical realizations at the same time with multiple development scenarios (Robust Optimization) to select the optimal Net Present Value (NPV) of the project considering the reservoir uncertainties.

This methodology combines compositional simulation and a mathematical optimization tool that uses artificial intelligence to maximize the NPV of the project under evaluation. Considering that LSWI alters the initial chemical equilibrium in the reservoir and induces changes in the system, a geochemical model is included with aqueous reactions, dissolution / precipitation mineral reaction and ion exchange. The optimization project was carried out in three stages, first a multiple assisted history match, followed by a probabilistic forecast and finally, a robust optimization.

As a result, an optimum operational strategy of LSWI was obtained in which the impact of changing the type, location and number of producer and injector wells as well as the volume of injected water (High Salinity Water Injection (HSWI) vs. LSWI) are considered. On average, the optimal scenario for LSWI obtained a recovery factor of 41%, compared to 34% if only conventional water is injected. The selection and optimization of the recovery strategy considered multiple geological realizations and multiple history matched models in the field development plan, this considers the uncertainty associated with the porosity, permeability and net to gross distribution, with the objective of increasing the accuracy and reliability of the results obtained for the recovery factor and the NPV. For the optimal LSWI case and considering five different selected geological scenarios (P10 to P90), the recovery factor obtained was between 37.89% (P10) and 42.21% (P90) and the project NPV between 807 MMUSD (P10) and 3315 MMUSD (P90).

This adapted methodology allowed to obtain the optimal development plan considering the uncertainty associated in the reservoir, using multiple geostatistical realizations and multiple history matched models at the same time (usually just one history match is considered).
Coupled Flow-Geomechanics Simulation of Fracturing-to-Production in Unconventional Reservoirs
Authors: Rodriguez Adolfo A. , Monteagudo Jorge E. , Nieto Nathalie E. , Primera Alejandro
Published: July 2020

We have developed a computational platform that allows the simulation of coupled flow-geomechanics-fracturing in a seamless manner. This allows consistent simulation of water flow back, proppant placement and production. The simulation process starts with the hydraulic fracturing process which is implemented by solving the fully coupled flow-geomechanics problem. Next, a critical stress intensity factor is computed which rules the fracture propagation process. For the results presented in this paper, we consider the simultaneous propagation of all the fractures belonging to a single stage. After the fractures have been successfully created, injection is stopped for a given number of days after which oil production starts. We showed a set of synthetic results that illustrate the stress and pressure changes that occur during fracturing and production of unconventional wells.
Laplace Domain Pressure Behavior Solution for Multilayered Composite Reservoirs
Authors: L. F. Bittencourt Neto Jessica , Vieira Bela Renan , Pesco Sinesio , Barreto Abelardo
Published: July 2020

This work proposes an analytical model to compute the pressure response for radially heterogeneous multilayer reservoirs. The analytical model proposed in this work was developed based on equations that model pressure behavior during multilayer conventional production tests. A system of linear equations in Laplace domain is built, representing all differential equations, boundary and coupling conditions. The solution of this linear system in Laplace domain is inverted to real domain through Stehfest’s Algorithm. Layer properties such as permeability, oil viscosity, and porosity may be different for each layer. The computed pressure may be used to determine the main properties of an equivalent single-layered radial composite system that responds in the same manner as the heterogeneous one.
A Novel Solid Lubricant Uses the Principles of Tribology to Reduce the Coefficient of Friction COF in Oil- Based Muds OBM for Extended Reach Drilling Applications
Authors: Ramirez Mario A , Pritchard Ryan
Published: July 2020

Extended reach horizontal wells face significant challenges in drilling longer laterals with oil-base mud (OBM). A novel solid-state lubricant was developed to close the gap in limitations of liquid lubricants and OBM with respect to lubricity in long extended lateral sections. The novel solid lubricant reduces the surface contact area between the asperities (deformations) by rolling and provides a chemically bonded film on the contact areas to reduce the amount of shear stress between the surfaces.

There is limited understanding of the complex mechanisms affecting the coefficient of friction (COF). The principles of Tribology (the science of friction, lubrication and wear) were used to develop the solid-state lubricant. The Stribeck Curve describes the regimes while using a lubricant, including boundaries mixing elasto-hydrodynamic and hydrodynamic lubrication. Liquid lubricants are limited at controlling boundary conditions where the COF is ruled by asperities in contact between the surfaces. The novel solid-state lubricant works on the asperities of both the wellbore and bit/BHA. In addition, the COF is improved in the mixed and elasto-hydrodynamic lubrication regimes.

Several oil-based mud field samples were tested for lubricity using different methods including the EP Lubricity Meter and Dynamic Lubricity Evaluation Monitor (LEM). The novel solid-state lubricant was also tested using a Tribometer to produce a continuous Stribeck curve that enables evaluation of the lubricant in the entire lubricity regime. The results of the COF using EP Lubricity Meter were transformed calculating the Stribeck number to build the curve. The potential benefits of the solid lubricant were discussed using a model developed by the Stick Slip vibrations with Stribeck curves. A reduction of COF in the boundary lubrication region occurs when the asperities of the wellbore and the bit/BHA are in contact. This is explained by the adsorption and absorption of the novel solid-state lubricant onto the asperities, providing a smooth surface. The novel solid-state lubricant has a wide particle distribution (PSD) to cover different size and height of asperities. The Stribeck curves of the novel solid-state lubricant show that the lubricant can reduce COF in the boundary lubrication region where friction forces are highest, compared with a base fluid and other liquid lubricants.
Real Time Measurement of Resistivity at the Bit Allows Optimal Casing Point in JSO Sands
Authors: Cruz Nancy , Luna Mabel , Reyes Carlos
Published: July 2020

In Mexico, the development fields of the northeastern marine region have complex geological structures, which have formations with thicknesses that limit well directional operations, especially those related to the construction of high-angle curves in the reservoir.

Derived from the current challenges and demands in well drilling, the requirement of a greater area of ​​contact in the reservoir to increase the oil production, causing the drilling of wells in a high angle and forcing the use of various technologies to minimize drilling risks, turning them into methods for optimization.

This technical document shows the application of resistivity technology close to the bit, providing added value to geological control and monitoring during drilling, allowing the collection of information as a key point for critical casing points.

When drilling of a horizontal well, the problem of performing high angle curves in formations with risk of generating non-productive times is addressed, as well as the reduced thickness in certain areas of the reservoir are limiting for the construction of the horizontal section. Performing the correct casing point at the top of the reservoir allows the anhydrite zone to be isolated, which represents a potential risk during drilling.

As a result of real-time monitoring of the resistivity at the bit and the interpretation of structural geological information from correlation wells, minimization of the uncertainty to casing point in the desired formation was achieved, providing a wide vertical thickness margin, to achieve planned trajectory and position the well within the desired rock unit.
Benchmarking Drilling Performance of PDC and Hybrid Bits in an Offshore Interbedded Environment, Based on Bit Design and Features
Authors: Serrano Ralph Adeleke , Roy Chowdhury Ashabikash , Schoen William , Samuel Ronald
Published: July 2020

Interbedded formations are challenging to drill due to its potential to trigger torsional instability issues while drilling at low depth-of-cut (DOC), which could damage the bit due to impact and result in low penetration rate or an undesired trip. Wells drilled in the Guyana-Suriname Basin face a similar challenge as the wells penetrate interbedded shale and carbonates, causing conventional polycrystalline diamond compact (PDC) bits to lose their cutting efficiency due to impact damage while drilling the hard, interbedded formation.

Using a detailed bench-marking methodology, offset drilling data was analyzed and the results were utilized to optimize bit design to meet these challenges. Mechanical specific energy (MSE), which quantifies drilling efficiency, indicates formation changes and signals the advanced dull condition or damage. When coupled with dull bit forensics, MSE provides insight for iterative bit design optimization to mitigate drilling challenges.

The outcome of a detailed benchmarking process led to the selection and deployment of a 12¼-in. hybrid bit to drill directionally through interbedded formation, which significantly improved drilling performance and bit durability. The hybrid bit combined PDC and tungsten carbide insert (TCI) rolling cutting elements and delivered balanced aggressiveness to improve torisonal stability. Post-well analysis showed rolling DOC control offered by the hybrid bit delivered higher penetration rate. The comparison of the drilling mechanics of the hybrid versus PDC highlighted limited drilling efficiency of PDC bits in interbedded formation. The hybrid bit drilled 54% more carbonates than the best PDC offset run. Drilling dynamics data also highlighted lower levels of vibrations with the hybrid bit. In addition, the hybrid dull condition was better than the PDC bits, suggesting improved durability compared to the previously-used PDC bits.

This paper demonstrates time and depth based surface and downhole drilling data, when supplemented with rock strength analysis using a suitable benchmarking process, can provide insight about drilling mechanics. When matched with an application specific bit, it leads to sustained drilling performance improvement.
Non-Intrusive Parametric Model Order Reduction with Error Correction Modeling for Changing Well Locations Using a Machine Learning Framework
Authors: Zalavadia Hardikkumar , Gildin Eduardo
Published: July 2020

The objective of this paper is to develop a non-intrusive Parametric Model Order Reduction (PMOR) methodology for the problem of changing well locations that can eventually be used for well placement optimization, to gain significant computational savings. In the past, model order reduction strategies developed for the case of changing infill well locations are limited to the scale of application, with majority of focus laid on development of MOR for changing controls of the wells for well control optimization. In this work, we propose a proper orthogonal decomposition (POD) based PMOR strategy that is non-intrusive to the simulator source code, as opposed to the convention of using POD as a simulator intrusive procedure, and hence extends its applicability to any commercial simulator. The non-intrusiveness of the proposed technique stems from formulating a novel Machine Learning (ML) based framework used with POD. The features of ML model (Random Forest used here) are designed such that they take into consideration the temporal evolution of the state solutions and thereby avoiding simulator access for time dependency of the solutions. The proposed PMOR method is global in the sense that a single reduced order model can be used for all the well locations of interest in the reservoir. We address a major challenge of explicit representation of the well location change as a parameter by introducing geometry-based features and flow diagnostics inspired physics-based features. An error correction model based on reduced model solutions is formulated later to correct for discrepancies in the state solutions at well gridblocks.

The proposed methodology is applied to a heterogeneous channelized reservoir using a section of SPE10 model, to analyze and validate the proposed idea. It was observed that the global PMOR could predict the overall trend in the pressure and saturation solutions at the well blocks but some bias was observed that resulted in discrepancies in prediction of quantities of interest (QoI) like oil production rates and water cut. Thus, the error correction model proposed using Artificial Neural Networks (ANN) that considers the physics based reduced model solutions as features, proved to reduce the error in QoI significantly. Speed-ups of about 50x-100x were observed for different cases considered when running the test scenarios. The proposed workflow for reduced order modeling is "non-intrusive" and hence can increase its applicability to any simulator used. Also, the method is formulated such that all the simulation time steps are independent and hence can make use of parallel resources very efficiently and also avoid stability issues that can result from error accumulation over timesteps.
Assessing Well Integrity During Its Life Cycle Due to Primary Cementing
Authors: Miura Kazuo , Anunciação Jaculli Marcelo , Pelaquim Mendes José Ricardo , da Mata Cristian Roberto , Colombo Danilo
Published: July 2020

Primary cementing during well drilling operations aims, among other objectives, to provide structural stability by transferring well loads to surface formations, as well as being a safety barrier between casing and formation in order to prevent undesirable flow from permeable zones along the formation. The present work discusses whether permeable zones should be cemented along with impermeable zones, as degradation of cement quality has been observed in permeable zones due to, for example, circulation losses.

According to API (2010), between 1960 and 1996, 6.5% of all primary barrier losses were related to problems with cementing. Thus, in this work we evaluate the quality of well primary cementing based on the hydraulic power developed during the cementing job, in order to discuss better cementing practices. In order to perform this analysis, data is collected from Santos basin in Brazil regarding cementing of production casings and liners in pre-salt wells, with 3 or 4 phases.

Results show data collected from the drilling and cementing projects for selected wells, such as cement and cementing properties (density, volume, flow rate), casing properties (depth of casing shoes, diameter, weight), cement logging (expected vs. measured cement height, adherence quality of casing-cement and cement-formation), and drilling history (related operational problems). This data is then used to calculate the hydraulic power developed and to compare the quality of primary cementing between a 3-phase well, in which cementing is performed simultaneously in the impermeable (cap rock) and permeable (reservoir) zones, and a 4-phase well, in which the impermeable and permeable zones are cemented separately. Comparison between different wells allows us to verify our concerns regarding the quality of primary cementing in permeable zones, and to attest the quality of primary cementing as a barrier during the well life cycle.

Usage of the developed hydraulic power to attest the quality of primary cementing based on field data is a novel approach as a quantitative methodology for assessing well integrity and safety, becoming a tool that aids decision-making during well design, such as in selecting the number of phases or choosing appropriate cementing procedures.
Combining Machine Learning with Traditional Reservoir Physics for Predictive Modeling and Optimization of a Large Mature Waterflood Project in the Gulf of San Jorge Basin in Argentina
Authors: Calad Carlos , Gutierrez Fernando , Pastor Paola , Sarma Pallav
Published: July 2020

A novel technology that combines the benefits of speed of data sciences with the predictivity capabilities of traditional simulation is being applied to model two blocks of a large waterflood project in the Gulf of San Jorge basin in southern Argentina. The tool is being used to provide a prescription of injection water redistribution that optimizes production and reserves development and reduces injection cost.

The technology used is called DataPhysics* and combines the robustness of reservoir physics with the speed of data sciences techniques. The process solves a limited number of unknowns in a continuous scale making it several orders of magnitude faster than traditional numeric simulation. The reservoir model is created from raw (uninterpreted) data and is updated continuously allowing for close loop reservoir optimization in real time. Long term predictivity is enabled by the fact that the tool honors the reservoir physics.

At the time of writing this paper the recommendations of the predictive model have been implemented in the pilot sector of the field and early positive results have been observed.
One of the Deepest Wells Drilled in Bolivia: High Pressure and Temperature in more than 9 Months of Drilling, No Casing Wear Detected
Authors: Mertens Russell , Garcia Jesus , Bertarelli Valcárcel Mario Alberto , Duran Camargo Romulo
Published: July 2020

Casing wear caused by rotating drill strings can lead to reduced well integrity or increased well maintenance. Furthermore, excessive casing wear can lead to remedial actions, expensive non-productive time, failed casing, or safety hazards. Mechanical casing wear is a function of drill pipe contact pressure, drill pipe revolutions, and wear factor. Casing wear can be an issue anywhere in the world, but this paper examines these challenges in a particular well in the Bolivia's sub-Andean region. The historically low rate of penetration (ROP) of 1.3m/hr caused nine months of drilling operations inside the production casing. As a result, the production casing was exposed to 11.3 million drill pipe rotations. The operator with extensive experience drilling wells in this region identified the critical importance to mitigate casing wear. The strategy was to implement the use of Non-Rotating Protectors (NRPs) after the production casing was set in the hole to drill the last two hole sections. While casing wear reached 13.2%, an analysis indicates the wear would have reached 80% had NRPs not been used.

Additional challenges were expected due to high temperature and pressure in the lower sections. By using tools suited for these extreme conditions, one of the deepest wells in Bolivia was successfully drilled.
Early Engagement Collaboration to Evaluate Business Opportunities in Crude Trading Industry
Authors: Torres Montiel Adelfo , Ramirez Lopez Christian Alan
Published: July 2020

The objective of this paper is to present a comprehensive methodology to perform an initial evaluation of market size and potential value of a new hydrocarbon's transportation and commercialization network in Mexico.

The methodology is based in an integrated multi-domain evaluation from geoscience and reservoir engineering to facilities design and economics; covering four main aspects: 1) Confirmation of reserves and estimated resources, 2)Generation of production forecasts, 3) Pipeline network design for two sales terminals and 4) design plot of sales terminals with processing facilities to handle expected production. The four aspects are supported by an economic evaluation with multiple tariff scenarios for varied break-even and profitability targets.

The initial confirmation of reserves and resources for more than 70 fields spanning greenfields and brownfields alongside with exploration areas yielded the basis for the analysis which was supported on statistical analysis of analogue fields combined with a geological interpretation of the target basins. Production forecasts from multiple scenarios grouped by region and nationwide confirmed expected production input into the newly proposed transportation network which was compared against forecast from some of the operators with a reasonable match. Pipeline network design for heavy and light crude with flow assurance considerations provided the pipelines diameters and length to consider for the economic case and the inlet pressure for two terminals. Finally, the design plot of the facilities required at the terminals allowed to size land and infrastructure requirements at a pre-Front End Engineering Design (FEED) level. The economics showed feasibility of the production input scenarios at different tariff for the trading company considering the initial investments required to build the new transportation and commercialization network.

A novel integrated engineering solution combining domain expertise with processing and facilities design covering reserves and resources confirmation for more than 70 fields, production forecasts for all fields and aggregated to regional level, general assessment on infrastructure required to build a new transportation network and finally the infrastructure pre-design for two processing and commercialization terminals.
Fracture Face Damage: Diagnosis, Modeling, Solutions, and Study Cases in Ecuador
Authors: Izurieta Alvaro , Sierra Leopoldo
Published: July 2020

Underperforming fractured wells are often represented by fracture face damage or choked fracture models. This study shows a different pressure behavior identified from various historical cases in which mixed low- and high-mobility regions are present after hydraulic fracturing. Using available technology and processes to optimize the hydrocarbon production from wells in mature fields, this paper presents the data analyses and methodology used to analyze and discretize the induced damage after the stimulation process.

Production performance and pressure buildup data showed anomalous behavior in hydraulically fractured wells. To define this problem, an additional detailed reservoir simulation was performed to reproduce the damage mechanism that was not initially well identified by the pressure/derivative analysis. Various cases were examined to define the damage type, extent, and mobility changes present around the fractured area. Results from these simulations were used in pressure transient analysis software to generate analytical models that mimic the pressure behavior. The analytical models were compared with downhole data registered during well evaluation for validation.

Numerical models demonstrated that a low-mobility region was present around the fracture face and more consistent productivity results can be achieved by avoiding the creation of this region during fracture jobs by combining different breakers (delayed, temperature-activated, and fast reaction).

Pressure buildup data registered from different wells confirmed that the low-mobility region was not present.
Six Years Operating a Real Time Drilling Problem Detection Software in Deepwater Environments: Results and Challenges
Authors: Rodrigues G. da Silva Fabio , de Souza Cruz Marcelo , Barduchi Bruno , Bellumat Ernanda , Vieira dos Santos Maycon , Barroso de Matos Vinicius , Gandelman Roni Abensur , Leibsohn Martins André
Published: July 2020

Given the complexity and high costs associated to ultra deepwater drilling, any effort to avoid unforeseen situations is beneficial. Initiatives to optimize the drilling process in real-time are extremely important. This article details the experience of 6 year operating a real-time software with the focus of anticipating the detection of potential drilling problems in challenging scenarios.

Based on transient numerical simulation (hydraulics, cutting transport, torque and drag, etc.), the software automatically identifies operational problems in real-time, providing to the rig crew anticipated information, so that, corrective and/or preventive actions can be taken. The software incorporate relevant experimental and theoretical research developed in multiple Brazilian universities and R&D Centers. It receives surface and downhole data in real-time, as well as, simulates comprehensive models (which considers real data, fluid properties, well and drilling column geometry as inputs) in order to analyze the current drilling status, by comparing real and calculated (expected) data, with quantitative criteria. Dedicated decision trees, validated by a representative group of senior drillers, provide reliable indication for problem alerts.

The present paper aims to detail the successes and the difficulties of detecting typical drilling problems in Campos and Santos basins (offshore Brazil). The process of algorithm development, validation and field implementation is detailed.

In July 2014, after almost 10 years of development, the use of the application started as a service conducted by a drilling engineering team, on a 24x7 service in Petrobras Real Time Support Center. Since then, it monitored every Petrobras offshore well. According to estimates, the economy by using this real-time program reached almost 150 rig days, which is equivalent to approximately US$ 130 MM. In 2016, The iniciative was granted the Technological Innovation ANP (Brazilian National Petroleum Agency) Award as recognition by its relevant results. This software is in a continuous development process, aiming to acquire new analyses in order to increasingly help the Petrobras drilling operations.

The novelty is the usage of numerical simulation in order to withdraw the subjectivity of a qualitative data analysis, avoiding the misinterpretation of a possible operational event. Present challenges include the proposal of hybrid solutions (modeling + machine learning) to tackle the identification of complex problems (such as false kicks, stuck pipe in salt drilling and circulation loss prediction).
A Review on Fluids Technology for Near-Wellbore Remediation
Authors: Quintero Lirio
Published: July 2020

In the last two decades, the oil industry has dedicated considerable resources and efforts to developing chemical treatments to remove near-wellbore damage. The two main lines of work include formulations with multiple components (either solvent-based or water-based) and multifunctional microemulsion technologies that combine solvent-based and water-based treatments in a single-phase fluid.

Microemulsion technology has been applied in onshore and offshore wells, open-hole and cased-hole wells, newly drilled wells, and mature fields with issues of declining production. Various formulations are currently used for near-wellbore remediation in the oil industry.

This paper reviews publications relevant to near-wellbore remediation, in particular those that discuss microemulsion treatments. The review covers types of near-wellbore damage (emulsions, drilling fluids damage, sludge, scales, wettability alteration, paraffins and asphaltenes deposits) and the results of microemulsion evaluation and near-wellbore damage treatments.

The paper also presents a suite of laboratory tests for microemulsion evaluation and selection for near-wellbore remediation.
Machine Learning Applied to SRV Modeling, Fracture Characterization, Well Interference and Production Forecasting in Low Permeability Reservoirs
Authors: Urban-Rascon Edgar , Aguilera Roberto
Published: July 2020

The objective of this paper is to develop predictive models to optimize the (1) characterization of the stimulated reservoir volume (SRV), (2) discretization of the fracture network, and (3) hydraulic fracturing modeling, by combining machine learning (ML) algorithms and reservoir engineering in low permeability reservoirs.

An unsupervised learning algorithm is implemented to characterize the fracture network developed by micro-seismic observations during hydraulic fracturing. A Self Organizing Map (SOM) and Multi-Attribute Analysis are performed on the available seismic data to map the extension of the hydraulic fracturing stages and the fracture network complexity in a low permeability reservoir.

To correlate the mapped fracture network and discretized SRV, a 3D Finite Element Model (FEM) is developed to estimate fracture behavior, stress response, and hydraulic fracture propagation, on the predicted and forecasted multi-attribute map of the reservoir.

A 3D hydraulic fracture propagation model (HFPM) is introduced, to delimit the fracture geometry and remove data outliers in the SOM algorithm. Unsupervised algorithms rely on data quality. The efficiency of hydraulic fracturing modeling is improved with a machine learning approach by refining the certainty and quality of the data. An Artificial Neural Network (ANN) model helps to select the most significant parameters related to fracture modeling and simulation in the field. This approach allows us to recreate and forecast complex fracture networks in low permeability reservoirs, based on the learned geostatistical maps and hydraulic fracturing parameters, particularly where the microseismicity is limited or unavailable.

To validate the implementation of the 3D-HFPM in the field, an earthquake model is compared with statistically significant microseismic events obtained by the unsupervised iso-cluster algorithm. The relationship showed a good agreement, which suggests the HFPM agrees with seismic observations in the field.

The machine learning application to fracture network modeling provides the capability to identify susceptible areas to well interference and possible frac hits with higher certainty. This is so because the approach improves the selection of seismic data and hydraulic fracturing parameters, employed to develop the complex fracture network in numerical commercial reservoir simulators. This helps to determinate the reservoir interconnectivity and flow patterns in the fracture network.

This approach presents a robust manner for characterizing the SRV using a relative fast methodology, based on the combination of geostatistical and unsupervised learning modeling. The seismicity and hydraulic fracturing are connected using a multi-attribute and multi-disciplinary interpretation. It is a powerful tool for characterizing problematic fracture networks in unconventional reservoirs.