bluuebunny/crossref_metadata_2025 huggingface dataset:
A Numerical Model to Assist with the Selection of Non-Metallic Piping Materials for Offshore Developments
Authors: Alsaddah Abdullah , Almedallah Mohammed K. , Clark Stuart R. , Walsh Stuart D. C.
Published: January 2020

The oil and gas industry is moving towards the use of non-metallic pipeline material, such as reinforced thermoplastic and flexible piping, for applications in offshore fields. However, these materials have certain pressure and diameter constraints that require careful analysis prior to deciding on the appropriate piping material to be installed. The objective of this paper is to suggest an integrated approach that considers the reservoir properties, well path and the field pipeline network to determine the operating pressure and diameter that is ultimately used to select the appropriate pipeline material for offshore field developments.

The proposed integrated model uses a series of three optimization techniques to determine the optimum field development architecture, which includes the allocation of wells, pipeline network configuration and well path optimization. The model starts by applying a continuous optimization technique to find the optimum subsurface and surface network. It then uses a graph-theorical approach to find the optimum pipeline route based on an appropriate minimum radius of curvature while considering the presence of obstacles in the seabed. From the results of this optimization, a dynamic nodal analysis is applied to determine the optimum operating conditions of the field (e.g. pressure and well rate). Finally, mixed-integer linear programming (MILP) is used to optimize the pipeline diameter subject to constraints based on the maximum pressure and pipeline size of different non-metallic pipeline materials.

Analysis of the model results demonstrates that ignoring any of the reservoir, wellbore and surface facility components results in an underestimation or overestimation of the operating conditions of the field, which subsequently leads to incorrect selection of pipeline materials. Therefore, an integrated approach is necessary to evaluate the non-metallic piping applications in the oil and gas industry.
Fracturing in Coalbed Methane Formations in Ordos Basin: Observations, Simulation, and Improvement Plan
Authors: Han Jun , Liu Chuanqing , Wu Jianjun , Liu Yuan , Niu Li , Wang Weikan
Published: January 2020

Many operators are developing coalbed methane (CBM) reservoirs from Ordos basin on a regular basis, and fracturing is one of the key measures to increase production from this unconventional resource. Despite the long history and large volume for CBM fracturing stages in the past, the performance from the CBM reservoir is still often inconsistent and differs from expectations. It is necessary to have better understanding of the hydraulic fracturing dynamics in CBM to improve reservoir performance.

CBM reservoirs are well known to be different compared to the conventional formations, and so fracturing involves different considerations. Three key components are integrated in this study to better understand CBM fracturing. Fracturing data from multiple wells are integrated into one database to exhibit a certain pattern of where the better production would be. With the observation from previous microseismic and offset well response, it is confirmed that the fracture geometry has reached to certain length. Based on this observation and analysis, simulation for pressure match is completed to illustrate the hydraulic fracturing geometry and propped fracturing geometry, which leads to an improvement plan for future work.

The improvement plan for the fracturing in CBM is built upon the observation and analysis above. Unlike fracturing in conventional resources, onsite pressure observation and adjustment guidelines are suggested to achieve a better fracturing geometry in CBM because these have been shown to provide higher production over longer period of time.
Using Multicomponent 3D Seismic Data to Define Current Fluid Contacts in Stacked Limestone Reservoirs of a Partially-Depleted Oil Field
Authors: Al-Enazi Falah , Beck Byron
Published: January 2020

This paper describes the interpretation of compressional and shear wave seismic data, recorded in a multicomponent ocean-bottom cable seismic survey in the Arabian Gulf, to define individual present-day fluid contacts in stacked limestone reservoirs in a partially-depleted oil field.

KJO recorded a multicomponent 3D-4C seismic survey over a dormant, partially-depleted oil field using ocean-bottom cable technology in 2012. Processing of the P-wave, shear-wave and reservoir characterization volumes provided unprecedented resolution of the reservoir architecture, rock and fracture properties, and reservoir fluid distribution to assist in the field redevelopment plan. The reservoir characterization results provided a variety of porosity, fluid & lithology indicators. Vp/Vs ratio was identified as the most reliable fluid indicator. This is expected to be low above the oil-water contact (OWC) and high below the contact.

The field produced oil for many years from five limestone reservoirs. After a multi-year shut-in period, engineering assessment of fluid contacts concluded that the four upper limestone reservoirs, of late-to-middle Cretaceous age, are in vertical communication but also compartmentalized by faulting. Similarly the lower limestone reservoir (early Cretaceous) is also compartmentalized by faulting. Structural interpretation of the new data provided detailed depth maps of each reservoir top together with an updated pattern of axial and wrench faults. Reservoir characterization processing of the new multicomponent seismic data delivered a number of potential fluid indicator seismic attributes: Poisson's Ratio, Vp/Vs ratio and AVO gradient. After evaluation of 16 different seismic volumes, the Absolute Vp/Vs ratio from the PPPS Joint Inversion was selected as the most robust fluid indicator. Structure maps, overlain with the Vp/Vs ratio seismic attribute, showed amplitude shut-offs consistent with structural contours, varying from fault block to block. These maps were used to define present-day fluid distribution for each reservoir level. The results confirmed a) the presence of remaining hydrocarbons in most of the late Cretaceous reservoir compartments; b) middle Cretaceous limestones are largely depleted except for isolated attic volumes, and c) limited depletion in the early Cretaceous reservoir.

This was the first multicomponent reservoir characterization project carried out by KJO. The Vp/Vs ratio results confirmed the fluid distribution as determined by the engineering assessment; identified the sealing faults responsible for compartmentalization of the field, and supported the engineering assessment conclusion that the shallow reservoirs are in vertical communication.
A New Technique to Quantify the Productivity of Complex Wells Using Artificial Intelligence Tools
Authors: Hassan Amjed , Mahmoud Mohamed , Al-Majed Abdulaziz , Abdulraheem Abdulazeez
Published: January 2020

Nonconventional wells (NCWs) are applied to increase the well deliverability and access the difficult formations. The nonconventional wells have been used to refer for the advanced wells such as highly deviated, horizontal, fishbones or multilateral wells. These wells offer a great potential to maximize the hydrocarbon recovery, however, it is difficult to predict their performance. In the literature, numerous mathematical models were developed to predict the well-productivity. However, the available models have been developed by employing one or more simplifying assumption(s), which may lead to over or under estimate the hydrocarbon production. This paper presents an effective technique to estimate the productivity for nonconventional wells.

In this work, artificial intelligence (AI) technique was utilized to determine the well-productivity for wide range of conditions. The developed models can determine the well performance without introducing the complexity associated with the numerical approaches. Artificial neural network was utilized to estimate the hydrocarbon production for two types of nonconventional wells; fishbone multilateral and hydraulically fractured horizontal wells. Reliable models are presented to quantify the performance of nonconventional wells producing from heterogeneous and anisotropic formations. The developed models evaluate the importance of reservoir properties and well configuration on the well deliverability. Total of 850 data sets were utilized to construct the intelligence models and to validate the prediction performance. Moreover, mathematical equations were extracted utilizing the optimized ANN models. The extracted correlations showed acceptable prediction errors, the absolute error around 7.4% in average.

The novelty of this work is that effective models are proposed to quantify the productivity of nonconventional wells. The proposed models can be utilized to refine commercial software to narrow down the deviations between the actual measurements and simulation outputs. Also, this work can contribute to enhance our understanding of the oil-field management by improving the prediction of well deliverability. Consequently, this study can help in optimizing the well planning for complex wells such as hydraulically fractured horizontal and fishbone multilateral wells.
Wellbore Far-Field Imaging for High Resolution Reservoir Characterization
Authors: Denis P. Schmitt , Thierry-Laurent D. Tonellot
Published: January 2020

Depth images produced using sonic waveform data have the recognized potential to provide deep-look data applied to reservoir and fracture characterization. However, their usage is relatively sparse.

The geo-bodies that can be imaged with sonic logs do not need to intersect the wellbore and can be a fault, a fracture, a lithological boundary or a fluid contact, for example. The literature on near-wellbore imaging has been split in two camps for quite a while: P-wave versus S-wave imaging; the latter receiving lots of attention recently. In fact, one does not preclude the other.

The approach used in this work enables the nearly routine processing of all acquired acoustic data, irrespective of the wireline acoustic tool used, as well as the source (monopole or dipole), increasing the possibility of unveiling unsuspected and/or useful information from the reservoirs. We present several examples of images obtained from carbonate reservoirs in horizontal and slanted wells, including for runs of more than3000 feet. The imaging is performed using a proprietary reverse time migration implemented to run in parallel. In several instances, the image reached 200 feet from the wellbore and boundaries within a reservoir are delineated over several hundred/thousand feet within the formation at a distance from the wellbore varying from 180 feet to a few feet. An example shows the repeatability of the process and how structural images can be obtained at a sub-seismic scale. Besides being constrained by the formation properties, the distance reached during imaging is a function of the listening time. Pre-processing, such as the removal of the borehole modes is a critical step for detailed structural imaging. Its design can affect the final image, as illustrated in this paper.

As this technology becomes more mature, logging-based structural imaging away from the wellbore can be the missing scale between borehole wall images and borehole seismic such as VSP, enabling the estimation of more complete/detailed geological models helping the interpretation and the design of future well paths.
Improved Well-Control Management Through Progressive Optimization with Generalized Barycentric Coordinates and Manifold Mapping
Authors: Ciaurri David Echeverría , Beltrán Gustavo A. Moreno , Navarro Jhonatan Camacho , Mejía Jorge A. Prada
Published: January 2020

Well-control management is nowadays frequently approached by means of mathematical optimization. However, in many practical situations the optimization algorithms used are still computationally expensive. In this paper we present Progressive Optimization (PO), a simulator-nonintrusive four-stage methodology to accelerate optimal search substantially in well-control applications.

The first stage of PO consists in a global exploration of the search space using design of experiments. Thereafter, in the second stage, a fast-to-evaluate proxy model is constructed with the points considered in the experimental design. This proxy is based on Generalized Barycentric Coordinates (GBCs), a generalization of the concept of barycentric coordinates used within a triangle. GBCs can be especially suited to problems where nonlinearities are not strong, as is the case often for well-control optimization. This fact is supported by the good performance in this type of optimization problems of techniques that rely strongly on linearity assumptions, such as Trajectory Piecewise Linearization, a procedure that is not always applicable due to its simulator-intrusive nature. In the third stage, the precision of the proxy model is iteratively improved and the enhanced surrogate model is re-optimized via Manifold Mapping (MM), a method that combines models with different levels of accuracy. MM has solid theoretical foundations and leads to efficient optimization schemes in multiple engineering disciplines. The final and fourth stage aims at additional improvement resorting to direct optimization of the best solution from the previous stages. Nonlinear (operational) constraints are handled in PO with the filter method. The optimal search may be finalized earlier than at the fourth stage whenever the solution obtained is of satisfactory quality.

PO is tested on two waterflooding problems built upon a synthetic model previously studied in well-control optimization literature. In these problems, which have 120 and 40 well controls and include nonlinear constraints, we observe for PO reductions in computational cost (for solutions of comparable quality) of around 30% and 50% with respect to Hooke-Jeeves Direct Search (HJDS), which, in turn, outperforms Particle Swarm Optimization (PSO). HJDS and PSO are simulator-nonintrusive algorithms that usually perform well in optimization for oil-field operations.

The novel concepts of Generalized Barycentric Coordinates and Manifold Mapping within the framework of the Progressive Optimization paradigm can be extremely helpful for practitioners to efficiently deal with optimized well-control management. Savings of 50% in computing cost may be translated in practice into days of computations for just a single field and optimization run.
Enhancing Oilfield Water Injection Distribution and Energy Efficiency through Surface Network Optimizations
Authors: White Ramsey , Fischbuch Darryl , Bahattab Mohammad
Published: January 2020

Objectives/Scope: A Saudi Aramco facility is forecasted to process crude from an adjacent oil field. Additionally, the forecasted produced water rates and injection pressure are anticipated to increase. This requires pump upgrades thatincrease power consumption. Moreover, the produced water, normally reinjected into the reservoir, needs to be redistributed through upgraded headers to align with the overall reservoir management strategy. A hydraulic assessment was conducted to determine the ideal balance through optimization of capital expenditures and forecasted operating expenses.

Methods, Procedures, Process: The study was conducted using a hydraulic model of the pipeline network and produced water pumping system. Several scenarios of pump stages and disposal header configurations were simulated. Pump discharge pressure can be manipulated by increasing the number of stages. Alternatively, the existing disposal water injection network can be upgraded by replacing with larger lines, looping and or rerouting of injection headers. Based on the scope of each upgrade, capital costs and forecasted operating expenditures were quantified.

Results, Observations, Conclusions: Technical solutions through a hydraulic assessment was developed to achieve the ideal balance through optimization of capital expenditures and operating expenses. A 15% reduction in forecasted energy consumption was achieved by reducing the required discharge pressure from the salt water injection pumps. A major capital cost avoidance was also accomplished because of the proposed modification. Moreover, additional operational flexibility is provided, allowing for the facility to inject into other flanks as required, to reduce injection header pressure and fulfill reservoir management strategy. Further optimization will be explored in the future, as water injection redistribution to other flanks are introduced.

Novel/Additive Information: This study was conducted using detailed hydraulic assessmenttools that were used to determine the optimum facility designrequired to achieve the overall water injection strategy for the field. It includes hydralic modeling with Geographic Information System(GIS) capabilities, which considers the impact of the elevation profile on the hydraulics.
Innovative High Efficiency Oil Burner Proves to Solve Many Environmental Challenges in Well Test Applications
Authors: Wakabayashi Dalmo , McGouldrick Mark
Published: January 2020

The paper discusses how a new burner can solve environmental challenges in well test applications by reducing the quantity of fallout, providing better control of the burning operation, and allowing operators to adjust to changes in the well/weather conditions. In order to conduct successful well tests, substantial amounts of oil must be brought to the surface, and in most instances, the safest and least expensive method of disposal is to burn the produced oil. A quality smoke-free burn and drip-free operation is enabled through an innovative advanced nozzle design installed in this new oil burner. The nozzle can precisely control the flow of oil and air through the burner allowing, for the first time, closure with no unburned fuel escaping. The nozzles are operated remotely and powered by an integrated pneumatic system using the combustion air supply. The system permits control over each individual nozzle, enabling operators to adapt to varying flow conditions to maintain efficient and flawless performance. A wide range of tests were conducted, including combustion zone gas sampling and fallout testing. Over a three week testing period, the new burner flawlessly executed full-scale burns and provided on-the-fly nozzle control, burner head rotation, and instant drip-free shutdowns. The new burner demonstrated its capability to shut down all ten nozzles from their full capacity in three tenths of a second with no visible unburned hydrocarbons or drips. The new burner achieved a 99.99952% fallout efficiency; this is 14.58 times more efficient than any other current oil burner product offering. In addition to the exceptional fallout efficiency, it also delivers 99.4% combustion efficiency and 99.5% destruction efficiency allowing the calculation of CO2 emission rates, which during testing was found to be 41Lbs/MMBtu. The first operation was conducted offshore in Brazil where this new burner demonstrated the capability to control, monitor, and react to changing well conditions for approximately three days without issue. It flowed in excess of 6,700 bbls, preventing a minimum of 69.48 liters of fallout from entering the sea. A total of 32 jobs were performed with the new burner system from December 2014 to January of 2018 with a 100% success rate without contamination/fallouts. The totally eliminated fallout volume, compared with the second most efficient burner system available in the market, is 2653.22 liters after burning a total of 257,490 bbl of hydrocarbons. In 60% of the field jobs, the burner was rotated to accommodate wind direction or to improve burning efficiency. If a different burner system had been used, the burner efficiency would have lessened or, in a worst case scenario, the operation could have been delayed and the well shut in until wind direction changed sufficiently to allow the burning operation.
Applying Lean Methodology to Improve the Operational Efficiency of a Well Stimulation Vessel
Authors: Gondalia Ravi Ramniklal , Narayan Shashank , Sharma Sigra , Diwakar Harish , Patil Ravindra Madav , Palli Venkata Ramanamurthy
Published: January 2020

Western offshore fields in the South and East Asia region are depleted and require frequent stimulation. To efficiently deliver stimulation treatments, a supply vessel has been converted into a well stimulation vessel with limited well flowback capability. This is one of only a few vessels in the world that has a zero-discharge flowback facility with certification by industry-recognized external organizations. Developing the vessel and operations plans required a systematic approach to continuous improvement.

The process involved identifying the criteria for efficiency and effectiveness for an offshore stimulation vessel and building in continuous improvement methodology with a focus on visual order, organization, safety, and standardization of operations. A lean management methodology was applied to systematically analyze and improve operational process efficiency in relation to organization, orderliness, cleanliness, adherence, and self-discipline. A series of checklists were introduced to enable procedural adherence with monthly self-evaluations to identify areas of improvement and develop remedial work plans.

This paper describes the vessel conversion and installation process as well as the lean approach and health, safety, and the environment (HSE) requirements. The vessel has been used for a variety of stimulation jobs such as proppant fracturing, sand control pumping, matrix stimulation, nitrogen pumping, and limited flowback. These stimulation jobs have been achieved with no recordable injuries and zero nonproductive time by introducing operating procedures, training crew members in those procedures, and monitoring adherence. Systematic efficiency improvements related to materials and procedures led to a 23% reduction in onboard crew size, thereby reducing the risk exposure to personnel. Vessel repair and refabricating expenditures have been reduced by 53%. This vessel has delivered an average of 40 jobs per month, achieving a peak job frequency of 64 jobs per month and treating more than 1,000 wells to date.

This paper provides an overview of the practices developed and lessons learned for operating an offshore stimulation vessel, including process flow charts with trackers and checklists designed to improve operational efficiency.
Development and Field Testing of a Novel Multifunctional Drilling Enhancement Tool in a Middle East Field
Authors: Abdel-Aal Mohamed Ahmed , Mohamed Fahd Mohamed , Abdelkader Ahmed Galal , AbdulLatif Mohammed AbdulHamid , Koulidis Alexis , Ahmed Shehab
Published: January 2020

Well drilling and wellbore conditioning typically involve multiple specialized drilling tools. Systematic application of such tools can be a challenge from a logistics and maintenance perspective, which eventually has an impact on the efficiency of the drilling process as well as the resulting wellbore condition. This paper presents a new multifunctional drilling tool developed to address such operational challenges. The tool’s effect on the drilling and logging process is illustrated through a field case study.

The CRS is a multifunctional drilling tool able to Cut, Ream and Stabilize when installing in a BHA. It is envisioned as an integral bottom hole assembly (BHA) component replacing the uppermost stabilizer while selectively acting as a fixed blade cutter, roller-reamer, lateral vibration damper, friction reducer, stabilizer and/or key-seat wiper. The specific function is dependent on wellbore conditions and is passively activated or engaged during operation. The CRS was successfully field-tested in a middle east field late 2018. Offset well data were used to validate the effectiveness of the tool and provide recommendations for future development.

An offset well was used as a benchmark for comparison to characterize CRS performance. The CRS replaced the stabilizer directly above the measurement while drilling (MWD) tools as part of the BHA used for drilling the interval from 1800 to 2520 meters. When compared to the offset well, the tool had no negative effect on trajectory or dogleg severity. Tight spots required significant back-reaming in the offset well during pull-out-of-hole (POOH). Using the CRS saved 63 hours of rig time when POOH due to the tool’s effective tight spot cutting capability. High torque fluctuations ranging between 2 to 13 klbs-ft were observed in the offset well while drilling formations mainly composed of sticky claystone and limestone. The resulting poor wellbore quality rendered significant logging challenges. The CRS’s ability to damp lateral vibration while engaging in its reaming function resulted in the mitigation of these challenges. Another innovative feature of the CRS’s reaming function is the complete elimination of cutter loss risk. The CRS body is, by far, the industry’s largest area bearing mounted reaming structure and its concentric design eliminates the possibility of it being lost in the hole. The CRS body rotates in response to lateral vibration and drill string whirl when in a vertical or deviated wellbore, effectively contributing to the damping of both vibration modes. The body acts as friction reducer at high deviations. The rotating body also translates on the tool mandrel when faced with a tight spot or pack-off. This translation is opposed by a unique spring assembly that can deliver full top drive torque to the body to cut through the formation.
Synthetic Well-Log Generation: New Approach to Predict Formation Bulk Density While Drilling Using Neural Networks and Fuzzy Logic
Authors: Gowida Ahmed , Elkatatny Salaheldin , Abdulraheem Abdulazeez , Shehri Dhafer Al
Published: January 2020

Synthetic well-log generation using artificial intelligence tools is presented as a robust solution when the logging data are not available or partially lost. Formation bulk density (RHOB) logging data greatly assist in identifying downhole formations. It is measured in the field using density log tool either while drilling by logging while drilling technique (LWD) or mostly by wireline logging after the formations are drilled because of the operational limitations during the drilling process.

Therefore the objective of this study is to develop a predictive tool for estimating RHOB while drilling using artificial neural networks (ANN) and Adaptive network-based fuzzy interference systems (ANFIS). The proposed models used the drilling mechanical parameters as feeding inputs and the conventional RHOB log-data as an output. These drilling mechanical parameters including the rate of penetration (ROP), weight on bit (WOB), torque (T), stand-pipe pressure (SPP) and rotating speed (RPM), are usually measured while drilling and their responses vary with different formations.

A dataset of 2400 actual data points obtained from horizontal well in the Middle East is used for building the proposed models. The obtained dataset is divided into 70/30 ratios for training and testing the model respectively. The optimized ANN-based model outperformed the ANFIS-based model with correlation coefficient (R) of 0.95 and average absolute percentage error (AAPE) of 0.72 % between the predicted and the measured RHOB compared to R of 0.93 and AAPE of 0.81 % for the ANFIS-based model. These results demonstrated the reliability of the developed ANN model to predict the RHOB while drilling based on the drilling mechanical parameters. Afterwards, the ANN-based model is validated using unseen data from another well within the same field. The validation process yielded AAPE of 0.5 % between the predicted and the actual RHOB values which confirmed the robustness of the developed model as an effective predictive tool.
New Acid Fracturing Model on Reservoir-Centric Platform for Carbonate Formations
Authors: Kuznetsov Dmitry , Emelyanov Denis , Romanovskii Rostislav , Khudorozhkova Aleksandra , Oussoltsev Dmitri , Nakamura Fabio
Published: January 2020

Acid fracturing is a widely accepted method for stimulation of carbonate reservoirs. A new high-resolution fracture hydrodynamics and in-situ kinetics model integrated on a reservoir-centric exploration and production platform improves acid fracturing simulation accuracy and performance for completion, stimulation, and reservoir engineering groups. This paper describes key features of the new acid fracturing model and the workflows that have been enabled on the E&P platform.

We demonstrate that the new acid fracturing model can simulate the key effects of acid fracturing at a new level of fidelity and quality. For example, it reproduces viscous fingering effects that occur naturally when alternating fluid systems of different viscosities are pumped into the fracture. The model simulates diverting agents that reduce leakoff in the fracture area and their effects on fracture geometry. Combining the 3D earth model in the E&P platform and high-resolution simulator allows the modeling of small-scale heterogeneities that affect fracture conductivity with a high level of accuracy. The model is also capable of simulating hybrid acid-proppant treatments. Finally, a fluid and materials database is incorporated to capture the impact of modern acid systems and diversion agents. The new model was validated against the results of laboratory experiments and published data. The first results of the platform stimulation-to-production workflow implementation are presented for a formation with high calcite content. The new approach enables engineers to evaluate completion and stimulation designs directly by quantifying the impact on hydrocarbon production and seamlessly integrates carbonates completion design and reservoir engineering disciplines.

The novel high-fidelity approach to acid leakoff, diversion systems, and rheology of different fluid mixtures significantly extends the design and evaluation tools for acid fracturing treatments in carbonate formations. Integrating the acid fracture model and E&P platform enables simulation of multiple acid treatments all the way to production evaluation and opens the path towards optimal design of single- and multiple-well treatments.
Application of Statistical Analysis to Optimize Rate of Penetration
Authors: Abbas Ahmed K. , Alqatrani Ghassan , Al Saba Mortadha , Mohammed Haider Q. , Al-Bazzaz Waleed
Published: January 2020

Drilling optimization consists of selecting operational parameters that maximize a desirable rate of penetration (ROP). There are many factors, which determine the ROP. Typical factors include rig- and bit-related parameters, formation properties, and drilling fluid properties. To be able to maximize ROP successfully, it is critical to develop a deep understanding of the relationship between controllable drilling parameters and ROP. To this end, ROP model was developed based on statistical analysis method using the key parameters that can be modified quickly to adjust the ROP.

This study describes a statistical evaluation of wells drilled in Southern Iraq. The analysis attempted to discover the key operational drilling parameters that drive well-optimizing drilling operations. Some key questions to be addressed include: What is the wellbore trajectory (azimuth (AZI) and inclination (INC)) that could result in better drilling performance? What is the effect of total flow area (TFA) on drilling performance? What is the effect of the rig- and bit-related parameters on drilling performance? Is there a relationship between marsh funnel viscosity (MFV), plastic viscosity (PV), yield point (YP), and drilling performance? These and more questions were addressed in this study. This study supplies knowledge that can be used to conduct drilling optimization study and determine the optimum controllable drilling parameters that maximize ROP and economic objectives.
A Stochastic Approach to Economic Modeling of Unconventional Resource Play
Authors: Abdulazeez Mehaboob , Rabines Jaime , Siddiqui Ammar , Bukhamsin Khadija , Asiri Rawan
Published: January 2020

In unconventional reservoirs, not only do we have to concern ourselves with having a sufficient hydrocarbon volume to justify development (Resource Fairway), but also whether producibility characteristics, especially the ability to effectively fracture stimulate, are favorable (commercially). While volumetric characteristics tend to be regionally variable resulting in changes in hydrocarbon fluid types, reservoir pressures, thickness, porosity, saturation, etc., at the basin scale, producibility characteristics tend to be more locally variable resulting in changes in natural fracturing, subsurface stresses, permeability, effectiveness of fracture stimulation barriers, etc., at the field scale. A stochastic approach encompasses both these trend variations (regional and local) while assessing the commerciality of the play.

This paper will explain the workflow involved in creating a probabilistic model using a commercial tool for engineers to understand the mechanics of the model, quality-check the input distributions, compare the model results to those from other sources (such as empirical, analytical, or numerical models). This workflow also will help in seamlessly modifying the input parameters to generate "what-if" scenarios and stress test the base case of development projects.

Due to the capital-intensive nature of Unconventional projects, it is important to economically model a series of staged-investments. The purpose of the staging is to responsibly expose incremental capital and identify course corrections. Several factors and combination of inputs affect the commerciality of unconventional developments. These inputs will then be sampled using Monte Carlo simulation to generate a multitude of trials and their summary statistics. The recoverable resources, costs, and economics can also be exported for any given trial, and the ranges of input parameters sampled to generate a given trial can also be extracted

Five critical parameters and their ranges were identified for developing a stochastic Before Tax (BTAX) economic output reflecting the full range of outcomes. Well type curves and select components of Capex and Opex were identified as the primary drivers. Associated products, such as condensate, NGLs, ethane, sulfur and water, were modeled as a function of the primary product using dependent ratios. Variability in cycle time was added to account for delays in implementation and acceleration as learnings are applied.

This paper will present how technological integration between legacy in-house developed tools and stochastic analysis engines, as the centerpiece, can provide management the required level of visibility on project economics and evaluation ranges. With the considerable time spared in carrying out economic assessments due to this workflow, engineers are able to spend more time in developing case scenarios, run sensitivities, and analyze outcomes and results to make informed portfolio management decisions.
Modeling and Prediction of Resistivity, Capillary Pressure and Relative Permeability Using Artificial Neural Network
Authors: Ba alawi Mustafa , Gharbi Salem , Mahmoud Mohamed
Published: January 2020

Capillary pressure and relative permeability are essential measurements that are directly affecting multi-phase fluid flow in porous media. The difficulty of calculating them rises being constrained to core analysis in the laboratory with many challenges of mimicking reservoir conditions. This makes capillary pressure measurement process to be both time consuming and expensive. However, as resistivity is conveniently obtainable, it can be used to predict both capillary pressure and relative permeability given all relation to wetting phase saturation.

Artificial intelligence methods have achieved promising results in modeling extremely complicated phenomena in oil and gas industry. This study aims to find a relation between all of resistivity, capillary pressure and relative permeability. Ultimately, we are going to generate a model by utilizing Artificial Neural Network (ANN) technique to predict both capillary pressure and relative permeability from resistivity. In addition, the implemented technique will be used to improve the data quality and to extend its resolution to thousands of data points. After that, as countless artificial neural network architectures can be created, the most efficient one will be evaluated given its performance and accuracy results.

This paper presents the use of artificial neural network technique to both model and predict capillary pressure and relative permeability from resistivity attained from core analysis, and define core samples pore distribution systems. It was found artificial neural network architecture captures the complexity of the physics of the problem. Thus, it successfully fulfilled the required prediction objective. Additionally, compared to the traditional methods, this is proved to be accurate, fast, and significantly cost effective. Consequently, this process could replace the current traditional approaches. Finally, as artificial intelligence techniques are improving exponentially over time nowadays, this will increase the accuracy of the model predictability majorly.
Predictive Maintenance for Gas Turbines
Authors: Bangert Patrick
Published: January 2020

Gas turbines age and sometimes have problems that may lead to a trip or failure event. This paper describes how one can reliably forecast such problems at a future date so that the problem can be dealt with in the present. These methods are data-driven by relying on machine learning to develop the mathematical description for the gas turbine. First, all instrumentation is combined in a state of the turbine that is forecasted into the future using a long short-term memory (LSTM) network. Second, this forecast is analyzed by a neural network trained to recognize normal healthy behavior in order to identify problem. Third, problems can be diagnosed in some special circumstances by recognizing their fingerprint using past examples of the same failure mode; this is particularly relevant to vibration data.
Detecting Porous Gas Accumulations through Seismic Amplitude Analysis in Paleo-Zoic Siliciclastic Reservoir, Saudi Arabia
Authors: Alwusaibie Abdullah , Mahozi Ali
Published: January 2020

A siliciclastic gas reservoir is analyzed through two seismic attributes, root mean square (RMS) ampli-tude and reservoir to shadow mono frequency (RSMF) to detect and quantify porosity and gas accumu-lation. The objectives are to apply forward modeling to design the interval for amplitude mapping to de-lineate porosity; to analyze the amplitude of the frequency to generate the RSMF map; and to validate the RMS amplitude map with porosity, and the RSMF map with gas test results.

One well was modeled for two cases, a tight and porous reservoir, to establish an appropriate RMS amplitude extraction window for reservoir porosity. The amplitude around the reservoir was extracted and validated by wells. The seismic volume is decomposed in the frequency domain for the gas detec-tion technique. This technique measures the amplitude attenuation in the dominant frequency between the reservoir level and the zone just beneath it to produce the RSMF map, with the assumption that the frequency amplitude attenuation increases while passing through the gas reservoir. The RSMF map was validated by the normalized gas test results of several wells.

The forward modeling indicates that up to 20 ms below the reservoir is an optimum window to corre-late the targeted reservoir with the RMS amplitude. The RMS amplitude was found to be directly pro-portional to porosity, with the modeled tight reservoir case having lower RMS amplitude than the porous reservoir case within the optimum window. The RMS amplitude response for the modeled tight reservoir case almost matches the in-situ case. There is a correlation coefficient of approximately 70% between the average reservoir porosity of the wells and the RMS amplitude map extracted from the seismic volume within the optimum window. At the dominant frequency of 20 Hz, a correlation coeffi-cient of around 82% is observed between the gas test results and amplitude attenuation. The RMS and RSMF attributes are affected by seismic amplitude preservation as well as signal-to-noise ratio, which can impact the level of uncertainty between these two attributes and the extracted maps.

The integration of RMS amplitude and RSMF attributes complemented the characterization of the si-liciclastic gas reservoir for detecting high porosity zones with gas accumulations. Zones with high RMS amplitude and attenuation were highlighted to be targeted for well placement.
The Use Of Aerated Drilling Fluid Technique Through Top Fractured Formations In A Deep Gas Field - A Case History
Authors: Javay Alexandre , Nafi Mohamed Khalil , Mathur Anil , Alvidrez Levario Jesus
Published: January 2020

The aerated drilling fluid technique was introduced to a deep gas well drilling project as a solution to overcome the challenges posed by top fractured formations and highly water-sensitive shales. The top holes were originally drilled with a diesel oil-emulsion drilling fluid which was later changed to a high-bentonite content drilling fluid system. The aerated drilling fluid aimed at improving the overall drilling performance and addressing top hole geological complications.

The main objectives behind the introduction of aerated drilling were the mitigation of mud losses in Wasia and Shu’aiba formations and improvement of the penetration rate across the lowermost abrasive Biyadh interval. The aerated drilling fluid technique was successively implemented in four wells in different areas of the field. The system was a mixture of air and polymer-based fluid pumped inside a closed circulation system with the use of a rotating circulating head. The system provided the necessary viscosity to entrap the air downhole while allowing it to easily break out at surface in the separation equipment.

The technique proved to be an excellent solution for drilling through lost circulation zones across the Wasia and Shu’aiba fractured limestone formations. Equally important, this technique delivered much higher penetration rates while drilling across the Biyadh interval.

An effective oil-emulsion system used to be run to lighten the fluid column to prevent losses but was replaced by a high-bentonite drilling fluid for environmental reasons. The latter system was believed to seal the formation fractures due to its high gelation characteristics, thereby preventing losses. Despite being effective at preventing losses, this drilling fluid returned poor performance while drilling compacted clay intervals toward the end of the section. As a result, the casing point had to be set shallower thus complicating achieving the objectives of the subsequent hole section.

The results of implementation exceeded expectations both in terms of ROP improvement and control of downhole losses, reducing the section drilling times by more than two in comparison to the high-bentonite content drilling fluid and up to 35% over the oil-emulsion drilling fluid. This technique was also remarkable in reaching the designed casing point in all sections drilled.

This paper will describe in length the performance of the trial jobs, present the lessons learned from the implementation of this innovative drilling fluid technique and highlight the best practices utilized to make it a cost-effective solution.
Coiled Tubing Gas Lift: An Innovative Solution for Reviving Dead Wells in Southern Pakistan
Authors: Khalid Aizaz , Molero Nestor , Hassan Ghassan , Lovie Eric , Khan Rao Shafin Ali
Published: January 2020

In southern Pakistan, most wells in mature fields do not flow naturally and require delivery of supplemental energy into the wellbore through an artificial lift system. The existing portfolio of techniques, however, faces technical and economic challenges. Operators have tried numerous methods of deliquification such as soap injection, jet pumps, electrical submersible pumps, and conventional gas lift (GL). Those solutions differ in methodology and efficiency, but they unfortunately have failed either technically or economically in Pakistan.

Because reviving dead wells is key to maximizing production with the most efficient and cost-effective method in Pakistan, a detailed screening of candidate wells was carried out to identify innovative artificial lift solutions. The deployment of GL valves using coiled tubing (CT) soon emerged as the best option, because it offered the highest returns in a cost-benefit analysis. Coiled tubing gas lift (CTGL) is a rigless solution that enables setting GL valves at the required depth, during any stage of a well life. It allows gas to be injected through CT with production through the CT-to-tubing annulus. This technology is also retrievable and replaceable when needed.

Two pilot wells, that had been shut in since 2015, were selected from four shortlisted candidates through nodal analysis. Each system consisted of one CT string with multiple stations of unloading and orifice valves, spaced out at depths engineered to maximize each well’s productivity. In addition to a GL valve, each station included two CT external connectors and one self-aligning connector, which enabled efficient and safe connection between both CT ends during the deployment of the CTGL station.

Additionally, specific CT pressure control equipment and wellhead adapters were used to secure and hang the CT string in the production tree and provide connection with the gas injection facilities at the surface. The first installation was conducted in a vertical well originally completed 4 1/2-in. monobore, deploying 1 1/2-in. CT string with four CTGL stations. The second installation was performed with 1 1/4-in. CT and five CTGL stations in a well originally completed with 7-in. liner and 2 7/8-in. production tubing. The wells were commissioned using existing surface infrastructure and were unloaded smoothly until the production stabilized at optimum rates near 420 B/D and 325 B/D respectively.

This innovative artificial lift technique represents an effective and economical solution to restart production in mature fields where conventional artificial lift methods challenge well economics. This approach greatly rests on a thorough candidate selection process. The design and installation of two new CTGL systems was a first in the Middle East region and helped identify numerous best practices and lessons learned, which will speed up implementation of the methodology in other parts of the world.
Preventing Slugging by Tuning Choke through Machine Learning
Authors: Bangert Patrick
Published: January 2020

A gas-lift well sometimes suffers from slugging. As slugs reduce production volumes and cause other issues on the surface, we would like to mitigate or avoid them. The production choke and gas injection choke are two points at which the operator may influence the slug. For this to work, the operator must know that a slug is going to occur in advance so that avoidance actions can be implemented. The operator also needs to know by how much to change each choke. We find that a slug can be forecast successfully five hours in advance given typical field instrumentation of the well. This is based on an LSTM machine learning approach given historical data only.