bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Approach to Gathering Bottomhole Pressure and Temperature
Authors: Gosney Josh , Lassek John , Hartwell Mark
Published: January 2023

Bottomhole pressure (BHP) is a critical parameter to understand for hydraulic fracture diagnostics but is often difficult to measure due to increased complexity of execution needed for installation of gauges. Surface pressure is often used with a calculated friction and hydrostatic offsets, but these calculations can have significant error (Keck, et al 2000). Many authors of diagnostics such as step-down tests and diagnostic fracture injection tests (DFITs) clamor for the need of accurate, reliable BHP understanding (Cramer 2013, Mondal 2019, Hawkes 2018). A new technology has been developed to embed a pressure sensor in existing hardware that is used in standard fracturing operations. This reduces operational complexity and enables gathering of critical bottomhole measurements including pressure and temperature as a function of time.

This case study will address design and qualification of the technology, field deployment, operational considerations and compare results from the measurement compared to surface pressure derived calculations. It will be useful for completions and production engineers along with anyone who is involved in hydraulic fracture diagnostics.
Nitrogen Foam Fracturing in the Oil Window of the San Juan Basin: A Multi- Disciplined Approach Contributes to Significant Well Results
Authors: Li Ningning , Slowinski Matt , Koenig Don , Weaver Brian , Valenzuela Naomi , Searle Curtis , Reece Adrian , Sullivan Sabrina , Rosenthal Jack
Published: January 2023

The operator has successfully drilled and completed more than fifty horizontal oil wells in the subnormally pressured Gallup Sandstone (Mancos Formation) within the San Juan Basin, New Mexico. All the wells were fracture stimulated using 70% quality Nitrogen (N2) foam with 20/40 sand. N2 fracs are uncommon in modern completions but provide numerous benefits for operations in the San Juan Basin. Benefits of N2 foam fracs include reduced water usage, less proppant settling (improved carrying capacity of proppant), and less parent/child interference. The N2 fluid is high-viscosity and promotes higher height/length growth with improved fracture width relative to low viscosity completion fluids. These properties of N2 foam fluids help prevent damage to parent wells and result in an ideal fracture geometry.

This paper discusses methodologies employed by the operator resulting in significant improvements to well results. Methods include a) fracture design/modeling optimization with N2, b) parent and child well management, c) strategies for mitigating fracture-driven interactions, and d) a presentation of well results. The paper compares the completion parameters used in newly drilled wells versus legacy wells and contemporary offset completions to provide context to well results. Additionally, pressure management is utilized during flowback and production of both parent and child wells, resulting in improvements in oil productivity, load recovery, and minimal proppant returns during flowback. Pressure management incorporates both wellhead choke management and gas injection volume management as methods to maintain reservoir pressure in the short and long term.

The combination of N2 foam hydraulic fracs, pressure management during flowback, and production optimization has led to significant improvements in horizontal Gallup sandstone well production. Incremental improvements have been made to all aspects of the completion, flowback, and production processes. Nitrogen foam fracturing is an understudied completion design that has had limited deployment in oil reservoirs across the oil industry. Strong production results from Gallup Sandstone N2 completions suggest that the technology is worth further consideration and study. This methodology could provide insights for other operators with similar reservoir conditions.
Comprehensive Understanding of Proppant Transport for Slickwater Fracturing via CFD Modeling
Authors: Liu Xinghui , Chang Oliver , Wang Jiehao , Singh Amit , Rijken Margaretha , Reverol Richard , Lazo Antonio
Published: January 2023

Unlike high-viscosity fluids, proppant transport with slickwater inside fractures is complex, but most fracture models do not adequately describe it. These models solve proppant transport based on simplified continuity equations. They assume that the average proppant velocity is the same as the fluid velocity and proppant settling in the vertical direction is always incorporated using Stokes’ law or similar equations. Some models also include proppant bridging and trapping effects, and velocity slippage between proppant and fluid, using empirical correlations. None of these commercially available models consider proppant momentum and interactions of particles with other particles, fluids, and fracture walls. In addition, turbulent flow near wellbore is completely ignored in these models. Slot tests used for proppant transport in laboratory studies are too small and too simplified to upscale properly to realistic field conditions. CFD (computational fluid dynamics) modeling can bridge some of these gaps. The main objective of this study was to use CFD modeling for a comprehensive understanding of proppant transport with slickwater and improve proppant and fluid selections for unconventional fracturing.

Several lab-scale CFD models were constructed and calibrated using experimental proppant transport data from slot flow tests. Field-scale CFD simulations were performed to evaluate the impact of key parameters on proppant transport and placement, including pumping rate, fracture width, fluid viscosity, proppant size and density, fluid leakoff, fracture height growth, perforation orientation and size, multiple fractures near wellbore, and pre-existing dunes, etc. Field-scale CFD model results show that proppant with wider size distribution provided more favorable placement, as larger proppant particles settle quickly to create a proppant dune and generate sufficient fracture conductivity near the wellbore. Smaller proppant particles travel deep into the fracture to increase partially propped fracture surface area in the far-field. CFD model results further show that the distance that larger proppant could reach inside the fracture is small, especially in the vertical direction, and that proppant height coverage can be improved by dune formation.

CFD model results confirm that proppant placement inside the fracture is significantly affected by pumping rate, fracture width, fluid viscosity, proppant size and density. CFD model results suggest that horizontal wells should always be landed close to the bottom section of the expected fracture where the proppant dune is located. Proppant with wider size distribution, for example 40/140- and 40/200-mesh sand, is expected to provide improved proppant placement.
Effect of Proppant Settling in the Wellbore on Proppant Distribution in Perforation Clusters
Authors: Aijaz Muhammad Jahanzaib , Sharma Mukul Mani
Published: January 2023

Our goal in this paper is to quantify the impact of proppant settling in the wellbore on the efficiency and distribution of proppant into perforation clusters. This phenomenon has been experimentally studied on the lab scale in the past but no field-scale simulations have been performed to quantify the amount of proppant settled in the wellbore and its impact on proppant placement.

Critical velocity correlations are used to estimate the velocity at which proppant settling can occur and incorporates them into a numerical simulator for simulating proppant transport in multiple perforation clusters. The proppant distribution in each perforation cluster and the amount of proppant settling in individual wellbore sections is computed. Comparisons made with cases where no settling is considered clearly show that the total proppant mass entering individual perforation clusters is impacted when proppant settling is considered. A parametric study is then conducted to determine which parameters (number of perforation clusters, flow rate, proppant size etc.) have the largest impact on proppant placement.

Our results show that proppant settling occurs primarily at the toe-side of the stage where the wellbore fluid velocity drops below the critical velocity. Wellbore settling occurs mainly near the last cluster as the fluid leaks off into all the heel-side perforations. Proppant wellbore settling cannot continue indefinitely because as proppant deposits in a wellbore section, the flow area is reduced and this in turn increases the flow velocity to above the resuspension velocity. The effect of proppant settling becomes more pronounced as the number of clusters in the stage increases. It is most pronounced in refracturing scenarios where a large number of perforations are open to flow. The settling progresses towards the upstream clusters as the toe side clusters are plugged and the critical velocity in that region drops below a threshold value. The injection rate, fluid viscosity, proppant diameter, proppant density and fluid density also have a significant impact on the total amount of proppant that settles.

This paper quantifies proppant placement in perforation clusters and proppant settling in wellbore sections during a fracturing stage. It provides a quantitative estimate and an explanation for the combined effects of proppant inertia, perforation bridging and proppant wellbore settling. The results suggest many ways to minimize the impact of proppant settling in the wellbore.
Investigation and Optimization of Pre-Loading Strategy in Parent Well for Fracture Driven Interaction Mitigation
Authors: Wu Ruiting , Ramsaran Keith , Cai Yuzhe , Madara Ben , Chen Yuguang , Singh Amit , Prouhet Jeremy , Banki Reza , Lannen Christopher , Rijken Peggy , Liang Baosheng
Published: January 2023

Inter-well Fracture Driven Interaction (FDI), aka Frac Hit, has gained visibility as more high intensity events (pressure increase in parent wells). Severe production performance impact (parent and child wells) are observed in depleted and tightly spaced wells in unconventional reservoirs. Various strategies, including water pre-loading in parent wells, adjusting well completion design of child wells, optimizing development plans, etc., have been tried in the industry to mitigate the negative impact of FDIs on production performance. However, mixed results have been observed in some pilot tests utilizing a water pre-loading mitigation strategy. Hence, it is critical to understand the driving mechanisms and key parameters impacting pre-loading performance in order to quantify the expected benefit of pre-loading in different well scenarios and optimize the pre-loading design.

A novel integrated and coupled geomechanics / fluid flow / fracturing propagation modeling workflow is applied to simulate the FDI (including pre-loading) on the pad scale. The workflow is capable of simulating the entire life cycle of the FDI interaction, (a) stimulation of parent wells, (b) production of parent well, (c) pre-loading of the parent well, (d) stimulation of the child wells, and (e) production forecasting of both parent and child wells. The workflow includes calibration with field observations of fracture geometry, production performance, pre-loading pressure behavior, etc. Geomechanics and reservoir simulation coupling captures the stress change due to the depletion at the parent well and re-pressurizing from pre-loading.

The workflow was applied to one pre-loading pilot test in the Permian Basin. The goal of the study is to identify the key parameters that contribute to the pre-loading success and optimize the pre-loading design. History match of parent and child wells production performance using the integrated and coupled geomechanics / fluid flow / fracturing propagation modeling workflow was conducted to calibrate and validate the model. Then, a sensitivity study was performed on various key parameters, including pre-loading volume and level of depletion at the parent well to understand its impact on the production performance at the parent and child wells. Learnings from this study provided guidance to the operation team in order to optimize FDI mitigation strategy.
One Shot Wonder XLE Design: A Continuous Improvement Case Study of Developing XLE Design in the Bakken
Authors: Lorwongngam Apiwat Ohm , McKimmy Michael , Oughton Evan , Cipolla Craig
Published: January 2023

Many operators have been working on optimizing stage spacing or clusters per stage to maximize production and reduce completion capital investment in unconventional wells. The operator has successfully proved that eXtreme Limited Entry (XLE) design works well in the Bakken. This paper uses a continuous improvement concept to improve on the paper presented in 2020 URTeC: 2796. The objective of this study is to push the boundary of perforation design that has been used as a standard design since 2020 to evaluate the optimum Shots Per Cluster (SPC), the minimum Rate Per Cluster (RPC), and the maximum Clusters Per Stage (CPS) that can still further maximize well production and provide optimum fracture cluster efficiency and Uniformity Index (UI). This paper will also address the comparison between XLE design and other diversion techniques.

Through the 3-year journey of understanding and optimizing XLE design, the operator had a total of 4 pads planned as a part of this study. The first 2 pads used to prove the XLE design concept utilized Radio Active (RA) tracer, deployable fiber optic, step down tests, downhole camera, perforation acoustic imaging tool, and production data. The other 2 pads are the observation lateral project [Cipolla et al. 2022] and a permanent fiber project; both projects include lateral bottom hole gauges, offset well fiber optic strain, and permanent fiber along the lateral. This paper uses part of the data from these projects to help validate fracture morphology, rate per cluster, and maximum clusters per stage. The operator uses the Lean continuous improvement and plan-do-check-adjust process to work from the planning to the standardization of the design.

RA tracer, step-down test, and deployable fiber optic results show that XLE with 1 Shot Per Foot (SPF) yields high production cluster efficiency of more than 90%, high uniformity index, and comparable production data to the non-XLE design while lowering the completions cost. From the permanent fiber optic data, the results show that the minimum rate per cluster to yield a uniformity index of more than 80% in the Bakken is ~ 5 BPM for 4-1/2" liner and ~6 BPM for 5-1/2" liner.

Using a continuous improvement process, the operator adopted the XLE design with 1 SPF as the current completion design standard. This design is proven to yield high productivity and increase asset value by lowering the cost of completions by more than 12%. In the high oil price environment, the XLE design can also be used to maximize asset value by increasing entry points in the well. This leads to an increase in short-term production. Throughout the data gathering and trial process, the operator also gathered novel pressure data allowing for direct measurement of perforation friction, and near-wellbore friction Limited Entry and Extreme Limited Entry Designs
Can You Feel the Pressure? Strain-Based Pressure Estimates
Authors: Haustveit Kyle , Haffener Jackson
Published: January 2023

Pressure measurements have long been vital to evaluating fracture interactions and well performance in both conventional and unconventional formations. Pressure responses during stimulation can be used to evaluate characteristics such as fracture geometry and net pressure. Dynamic pressure changes which occur during drawdown, both near wellbore and far-field, provide insight into the effective geometry being drained and how it evolves over time.

The combination of horizontal wells and hydraulic stimulation have been key in unlocking vast unconventional resources across North America and beyond, but there is still much left to understand regarding how the reservoir is drained across the miles of laterals accessing the resource. The density of pressure gauges required to accurately measure the drainage pattern from a horizontal multi-stage stimulation is currently not realistic economically or technologically. In this case study, the authors will describe a method of monitoring the drainage profile of a horizontal multi-stage stimulation using optical fiber.

Optical fiber was installed on an observation lateral in combination with six reservoir-sensing pressure gauges as part of the Hydraulic Fracture Test Site I, Phase 3 in the Eagle Ford, funded by the Department of Energy (DOE). The lateral observation well was positioned approximately 225 feet away from the nearest stimulated and producing horizontal well. Using Raleigh Frequency Shift Distributed Strain Sensing (RFS-DSS), the strain change was measured in the far-field as the offset well was stimulated and first produced. RFS-DSS provides a spatial resolution of 20 cm, allowing for the monitoring of strain changes much smaller than we can accurately sense with Low Frequency Distributed Acoustic Sensing (LF-DAS) (Ugento et al., 2019). The strain change measured during the offset fracturing strongly correlates to the strain change measured during the production period.

The combination of RFS-DSS and six externally sensing pressure gauges provided a strong correlation between the total strain change and total pressure drawdown, where gauges positioned in regions of large negative strain change interpreted as drawdown showed large pressure declines and gauges in areas of small strain change saw small pressure declines. The correlation was applied to the total length of strain change, including areas without pressure gauges, to generate an estimated pressure profile for the entire length of the optical fiber.

This is the first attempt known to the authors where RFS-DSS monitored during production in a far-field observation well was translated to an estimated pressure profile. The technique will continue to be evaluated, trialed, and improved upon as additional data is collected from the pilot.
A Bullhead Refrac Application - Using Active Acoustic Pulses to Measure Diverter Effectiveness
Authors: Bourgoyne Steven , Murray David
Published: January 2023

During a bullhead refrac treatment, an Eagle Ford operator utilized active acoustic pulses to measure diverter effectiveness while continuously pumping. The goal was to determine if the fluid point of entry along the lateral would change after the diverter material seated on the perforations.

The bullhead refrac treatment consisted of 52 sand ramps with planned diverter drops after each ramp. Active acoustic pulses were taken at the end of every sand ramp to identify if fluid point of entry was changing along the wellbore as a result of the diverter material. The acoustic pulses and return signals were captured with a hydrophone sensor for optimal signal quality. The return signal comes from the first encountered, lowest impedance point and represents fluid point of entry in the well. Subsequently, forward acoustic modeling was conducted to simulate acoustic responses from different fracture sizes and their corresponding acoustic signatures.

Over 300 acoustic pulses were taken throughout the refrac treatment. Analysis of all the acoustic return signals indicated that a dominant fracture system was created or previously existed around the heel segment of the lateral and the fluid point of entry did not change throughout the duration of the refrac, indicating diverter was not effective. This paper will show that the use of acoustics gives an operator real-time ground truth about the location of the fluid point of entry and will allow them to make changes to optimize the refrac operation during a stage.
Real-Time Monitoring of Fracture Dynamics with a Contrast Agent-Assisted Electromagnetic Method
Authors: Ahmadian Mohsen , Haddad Mahdi , Cui Liangze , Kleinhammes Alfred , Doyle Patrick , Chen Jeffrey , Pugh Trevor , Liu Qing Huo , Wu Yue , Mohajeri Darwin
Published: January 2023

In collaboration with the Advanced Energy Consortium, our team has previously demonstrated that the placement of electrically active proppants (EAPs) in a hydraulic fracture surveyed by electromagnetic (EM) methods can enhance the imaging of the stimulated reservoir volumes during hydraulic fracturing. That work culminated in constructing a well-characterized EAP-filled fracture anomaly at the Devine field pilot site (DFPS). In subsequent laboratory studies, we observed that the electrical conductivity of our EAP correlates with changes in pressure, salinity, and flow. Thus, we postulated that the EAP could be used as an in-situ sensor for the remote monitoring of these changes in previously EAP-filled fractures. This paper presents our latest field data from the DFPS to demonstrate such correlations at an intermediate pilot scale.

We conducted surface-based EM surveys during freshwater (200 ppm) and saltwater (2,500 ppm) slug injections while running surfaced-based EM surveys. Simultaneously, we measured the following: 1) bottomhole pressure and salinity in five monitoring wells; 2) injection rate using high-precision data loggers; 3) distributed acoustic sensors in four monitoring wells; and 4) tiltmeter data on the survey area.

We demonstrated that injections into an EAP-filled fracture could be successfully coupled with real-time electric field measurements on the surface, leading to remote monitoring of dynamic changes within the EAP-filled fracture. Furthermore, by comparing the electrical field traces with the bottomhole pressure, flow rate, and salinity, we concluded that the observed electric field in our study is influenced by fracture dilation and flow rate. Salinity effect was observed when saltwater was injected. EM simulations solely based on assumptions of fracture conductivity changes during injection did not reproduce all of the measured electric field magnitudes. Preliminary estimates showed that including streaming potential in our geophysical model may be needed to reduce the simulation mismatch.

The methods developed and demonstrated during this study will lead to a better understanding of the extent of fracture networks, formation stress states, fluid leakoff and invasion, characterizations of engineered fracture systems, and other applications where monitoring subsurface flow tracking is deemed important.
Field Applications of Quantitative Fracture Diagnostic From Distributed Temperature Warmback Analysis
Authors: Mao Yilin , Godefroy Caroline , Gysen Michel
Published: January 2023

Fracture diagnostic on a cluster scale of multi-stage hydraulic fracturing wells remains challenging but essential to determine the quality of the stimulation operation and the completion strategies for future wells. Since the stimulation fluid is injected at a different temperature compared to the original geothermal, the considerably modified and highly heterogeneous thermal profile after stimulation presents significant potential to serve for fracture diagnostic purposes. In this work, a model to analyze the temperature signal associated with the shut-in period after hydraulic fracturing is presented, along with the pilot testing of two datasets.

The model extends the scope of traditional thermal injection profiling algorithm with fracture diagnostic functions. During the development process, we incorporate the existing warmback model of conventional wells in analyzing shut-in temperature data with a newly developed stimulated region thermal model. Two main outputs of the model, the injection fluid intake and the fracture propagation extent, are estimated and tested. The model is then automated and thoroughly implemented in the software package.

The primary applications of this work are injection fluid intake and fracture propagation extent of each perforation cluster in fractured wells. The spatial resolution of the injection profiling and fracture growth can reach the sub-meter scale (same as the distributed temperature sensing spatial resolution). Compared to the conventional radial warmback model, the temperature signals from the fractured well show a much faster warming trend while taking relatively larger amounts of injection fluid. This behavior can be attributed to the additional heat loss to the unstimulated region and larger contact area between clusters. On the other hand, leak-off fluids create a cooler stimulated region around the fracture plane, which makes the warmback trend slower compared to the linear flow regime model. The model developed in this study considers both behaviors to simulate the actual datasets.

The inverse model estimates the fracture propagation extent in both the stimulated region as well as the fracture plane. Both estimations can jointly infer the leak-off extent of an individual cluster. As a pilot project, this model is tested on warmback temperature data from two datasets. The injection profiling results using the model are consistent with profiles obtained from other data sources, while the estimated fracture propagation extents of individual clusters present different types of fracture geometry (symmetrical, asymmetrical, double peaks, etc.).

Quantitative injection profiling and fracture propagation extent estimations of an individual cluster using warmback analysis have been proven viable and reliable in this field study. It could be the first quantitative warmback analysis applied to fracture wells in the industry.
CO2 Injection in a Depleted Gas Field
Authors: Lüftenegger Markus , Rath Alexander , Smith Michael , Danilko Alexey
Published: January 2023

A compositional dynamic simulation model is fully implicitly integrated with a gas injection surface network model, to study the effects of CO2 injection into a depleted gas field. Multiple prediction scenarios are evaluated, under uncertainty, to reduce risk and improve decision making. We propose a workflow, composed of a geological sensitivity clustering step followed by a dynamic calibration step. The aim of this workflow is to decrease the objective function and improve the reliability of a probabilistic forecast, to model the CO2 storage potential of an onshore depleted gas field. Each run, containing all parameters and its objective function was exported and introduced into an inhouse R Script. Within this script we train a random forest tree to predict the objective function for various parameter combinations. This random forest is then used to generate 1 million models with the initial distribution from the simulation runs and will predict their objective function. The idea here is to get to a posterior distribution that can be used in the second simulation iteration. This method achieves a better history match within the ensemble, in a vastly reduced timeframe. History matched models were taken forward to predict CO2 injectivity. Injection variables, facilities and well completions for several wells have been included in the analysis, and numerical reservoir simulation models have been integrated with a surface network.
A Data Driven P-V-T Model to Predict the Oil Formation Volume Factor, Solution GOR and Bubble Point Pressure for Characterizing an Oil Reservoir
Authors: Kumar Saket , Gautam Sandarbh , Thakur Nitu Kumari , Khan Murtaza Ahmed , Kumar Sikandar
Published: January 2023

Characterizing an oil reservoir requires one to understand the Pressure- Volume-Temperature (PVT) properties of reservoir fluids, especially bubble point pressure, solution gas oil ratio and oil formation volume factor because of its more often utilization in reservoir engineering studies. The current correlations are restricted by the use of sample from a particular field. As the physical properties and the composition of the crude oil varies the results becomes erroneous after a specific range. This correlation will give results only over a specific range of properties like specific gravity, viscosity, composition etc. The challenge is to develop a new approach which overcomes the current shortcomings. In this paper a new machine learning based model has been developed using Interactive Multivariate Linear Regression (I-MLR) method by integrating a large number of datasets to predict above mentioned properties. It overcomes the restriction of the previous correlations as it does not use data from any particular field. As such it is applicable over wide range of physical properties and composition. This model does not require any laboratory studies which makes it more economical. The validation of the model is done after detailed comparative study done with various commercially used empirical correlations.
An Effective Approach to Modeling Hydraulic Fracture in a Coarse Scale Simulation Model
Authors: Tello Gomez Adan Hanniel , Fekkane Abdelhafidh , Oluwa Jubril Babajide , Al-Qahtani Adel
Published: January 2023

The use of hydraulic fracturing to improve well productivity in tight reservoirs and connecting unconsolidated quality reservoirs via hydraulic fracturing is very well practiced in the oil industry. Currently to model hydraulic fracture in order to fully assess its effect in the well and its interaction with the formation (or different layers) requires upscaling methods to reach higher resolution (refinement) in order to reach certain accuracy in simulations like sector-based or local grid refinement techniques around well-reservoir modeling. However, modeling hydraulic fracturing in a large full-field reservoir simulation model with hundreds of wells and millions of cells is computationally very expensive. The aim of this proposal is to provide an alternative modeling of hydraulic fracturing at any size-based cell without the need of refinement saving computational cost.

Even though computational capacity has increase exponentially in the last decade, the complexity and resolution of simulation models does overwhelm conventional computational processing leaving high resolutions models to corporations and companies with major resources in computing as the only capable to ensure an effective simulation of stimulation in wells modeling interaction with full field reservoir models. The search of alternatives to simplify and propose representative models of hydraulic fracture is part of needed applications to provide tools in field development and reservoir management scenarios, specially if a sizable data base with good quality surveying and compensated with production and performance data can represent key cornerstones to create meaningful characteristic variables in order to apply in modeling and forecast activities as history matching.

This paper proposes a new approach to model the hydraulic fracturing (HF) effect based on a volumetric relation between created fracture and influenced volume in a designated reservoir/productive formation to be use specially in coarse simulation models to simulate the enhancement of the hydraulic fracture effects in production and history matching modeling. The use of field data and pressure matched properties based on stimulation parameters is the foundation to rely on. The new approach helped developing a fracture factor used to model permeability interaction between formation and stimulated volume designated by cell size and position. The proposed approach guaranties no change on regional nor alteration of static model properties maintaining the geological concept intact and providing a more realistic approach in order to simulate effectively stimulation in modeled wells in any type of grid or geometry of cells.
Evaluation of NMR Derived Capillary Pressure Curves Against Porous Plate Data for a Sandstone Reservoir
Authors: Sharma Sharanya , Duhe Craig , Gao Bo
Published: January 2023

NMR assisted capillary pressure and water saturation measurements have proven to be significantly faster than traditional porous plate and centrifuge methods. The NMR directly measures water saturation along the length of the core and associated capillary pressure generated at a given centrifuge speed. It overcomes limitations of requiring lengthy equilibration times, tedious material balance, and approximate solutions. However, limited data is available with respect to actual application and operating range of the technology in reservoir cores. The objective of this study is to evaluate data quality, identify best practices, and any limitations in utilizing the faster NMR derived capillary pressure curves when compared against the gold standard porous plate method.

Core samples from a sandstone reservoir were selected to test a permeability range between 400mD – 1600mD. Representative synthetic reservoir brine was used in the tests. All plugs selected for the NMR capillary pressure study had associated porous plate data available. NMR capillary pressure curve was generated using the GIT-CAP patented methodology for three, four, and eight centrifuge speeds to understand the impact of test speed on capillary pressure curve resolution. The tests were performed at net confining stress and at ambient conditions to evaluate if large differences were observed in results. Gravimetric measurements were simultaneously obtained to ensure data quality. Two different available imaging pulse sequences – SE-SPI and the SPRITE method were also evaluated for the different samples in generating the NMR assisted capillary pressure curves. This work contributes to outlining parameters for workflow optimization when adopting this methodology in real field applications.
Evaluating Complex Lacustrine Carbonate Reservoir by Integrating Advanced Logging Techniques and Core Measurements-A Case Study in Qiadam Basin
Authors: Chen Wen An , Yu Dai Guo , Liu Guo Liang , Li Qing Bo , Zhang Di , Zhao Meng , Wu Fang fang , Cai Liang , Zhao Xian Ran , Li Shen zhuan , Wu Jin Long
Published: January 2023

A complex and tight lacustrine carbonate reservoir is the main target reservoir in Qaidam Basin. The diagenesis of shallow-shore lake deposition has created a highly heterogeneous reservoir in both vertical and horizontal directions in terms of lithologies, pore structures, and permeability. The core analysis shows a wide variety of lithologies that include terrigenous clastics (quartz, orthoclase, and plagioclase), carbonate (calcite, dolomite, and ankerite), and evaporite minerals such as anhydrite, etc. Electron microscope analysis shows mainly intercrystallite pores with dolomite, dissolved pores, and microfractures. Associated with the complex lithology and pore structure, reservoir permeability is varied and is mostly less than 0.02mD. Evaluating and characterizing this complex reservoir to find a better pay zone was the objective of this study.

To evaluate the lithologies, pore structures, porosities, and permeability in quantities accurately, the advanced gamma-ray spectroscopy logs, nuclear magnetic resonance (NMR) logs, and high-resolution micro-resistivity borehole image logs were acquired in some key wells. Integrated with core data such as X-ray diffraction (XRD), mercury injection capillary (MICP), the lithofacies, texture facies, and pore facies were classified based on the minerals from gamma-ray spectroscopy, the textures from borehole image, and the pore sizes from NMR. The combination of these three facies represents the reservoir quality.

In the study area, the lithofacies were classified into four types, which are high carbonate content facies, middle carbonate content facies, high clay content facies, and high clastic content facies. The texture facies were classified into four types, which are massive texture, layered texture, dissolved texture, and algal texture. The pore structure facies were classified into four types, which are macro facies, meso facies, meso-micro facies, and microfacies. The better pay zone is the combination of high carbonate content facies, algal texture, and macro facies. The pay zone of the reservoir was well defined and mapped with the combination facies vertically and horizontally in the whole study area.

The integrated solution described in this study leverages the advantages of advanced gamma-ray spectroscopy, NMR, borehole images, and core measurements. It develops a comprehensive understanding of the complex carbonate reservoir and provides the solution to pinpoint the sweet spots and place the horizontal well.
Application of Machine Learning for Estimating Petrophysical Properties of Carbonate Rocks Using NMR Core Measurements
Authors: Farmanov Ravan , Feldmann Felix , Mathew Eric Sonny , Tembely Moussa , Al-Shalabi Emad W. , AlAmeri Waleed , Masalmeh Shehadeh , AlSumaiti Ali
Published: January 2023

Evaluation of petrophysical properties such as porosity, permeability, and irreducible water saturation is crucial for reservoir characterization to determine the hydrocarbon initially in place and further optimize hydrocarbon production. However, estimation of these parameters is challenging for carbonate rocks due to their heterogeneity. One of the ways to determine petrophysical properties is the use of nuclear magnetic resonance (NMR), which involves applying a magnetic field to the formation and detecting signals emitted from pore spaces. The main objective of this study is to develop an empirical correlation for porosity, permeability, and irreducible water saturation by comparing NMR and laboratory measurements for carbonate rocks in the Middle East. Furthermore, machine learning (ML) approach was applied to predict these petrophysical parameters utilizing NMR data. Different ML algorithms such as tree-based and neural networks were trained to estimate these petrophysical properties of carbonate rocks. The obtained results from ML algorithms were further compared with core measurements to ensure their accuracy.

The results showed that the use of T2 spectrum as an input provided more accurate results than NMR features. It can be proven by observing the performance of deep neural networks algorithm, where the models showed R2 values of 0.87 and 0.74 for porosity prediction using T2 and features extraction approaches, respectively. The same behavior was followed for the permeability estimations as deep neural networks model scored R2 = 0.81 (T2 approach) and R2 = 0.74 (features extraction approach). Similarly, determination of irreducible water saturation was more accurate using T2 approach (R2 = 0.87), whereas features extraction technique also exhibited a decent performance (R2 = 0.71). Also, T2 approach is more convenient since it is more straightforward to generate T2 spectrum from NMR measurements and use it for the ML models. Furthermore, based on the machine learning approach, gradient boosting and deep neural networks models performed with higher accuracy than other algorithms. This can be attributed to their strong configuration, which is able to find patterns between input and output parameters. This study provides more insight into petrophysical properties determined from NMR measurements in carbonates using ML techniques. This is useful in better characterizing carbonate reservoirs in the Middle East through accurate estimations of hydrocarbon resources and related reserves.
Abandoned Exploration and Appraisal Wells Turned into Long-Term Monitoring Wells for Enhanced Far-Field Reservoir Characterization: Lessons Learned from a Frontier Deepwater Installation
Authors: Mimoun Jordan G , Gagnon Jeffrey Paul , Zeilinger Sabine C , Fabuel-Perez Ivan , Horsfall Donald Isaac
Published: January 2023

This paper discusses benefits, caveats, and lessons learned of wireless pressure monitoring systems in abandoned exploration and appraisal wells to gain insight into reservoir properties that extend beyond the scope of standard well testing.

Appraising large offshore deepwater discoveries requires drilling and evaluating several wells across a field to increase subsurface understanding and reduce development uncertainties. The recent technological advancement of wireless pressure monitoring systems, which utilize electromagnetic telemetry, has enabled operators to capitalize on previously untapped value from exploration and appraisal wells by turning them into long-term observation wells, without compromising abandonment compliance. Even if not tested, these penetrations can provide valuable dynamic data for enhanced reservoir characterization early in the appraisal life cycle and at little incremental cost.

Such a system was installed in a deepwater well in Cyprus to further understand potential compartmentalization risks. A nearby well test, executed 3 years after system installation, was successfully monitored by the abandoned penetration. The interference test helped shed light on far-field connectivity, inter-well reservoir properties, and connected volume. This information will improve the fidelity of the geological and reservoir simulation models utilized to inform depletion planning and support field development and commercial decisions.

This paper presents novel findings to help ensure data quality and representativeness from such systems, focusing on the overprint of the wellbore environment on the reservoir signal. Specifically, the deployment in a cased wellbore left with drilling fluid revealed lengthier and more complex swap-out dynamics with reservoir fluid than anticipated. As with most new technologies, subsequent installations benefited from these valuable lessons learned, resulting in more robust and reliable implementation practices.
Numerical Simulation Modelling of Well Tests for a Frac-Pack Completion Well in a Shallow Sand Reservoir
Authors: Mousavi Mirkalaei Seyed Mousa , Motaei Eghbal , Husen Akbar Ali Anwar
Published: January 2023

Understanding the flow behaviour of fractured wells is crucial to operators and service companies in evaluating the effectiveness of stimulation work performed on the well. New insights in modelling of well transient pressure tests in hydraulic fractured unconsolidated sand is presented in this paper by utilizing 3-D numerical black oil simulation in single and two layered sand reservoirs with a thin shale layer in between. The upper layer perforated and fractured to treat the sand production as frack-pack technique and the well test has been conducted only on the upper layer. Porosity and permeability heterogeneities are classically evaluated from petrophysic well log measurements and through geological description of the reservoir, then possibly refined by simulation and history matching. The pressure measured in the well test in four cycles of drawdown and build up. The well bottom hole pressure (BHP) behaviour cannot be adequately described with conventional well tests analysis for the upper sand without including the flow from the lower sand.

Different scenario of production from upper with adding hydraulic fractured examined to match the oil/gas production and bottom hole pressure. A range of factors are examined that may impact the introduced fracture flow behaviour based on actual fractured well flow. The main fracture and reservoir parameters investigated include absolute permeability of upper layer, gas oil contact (GOC), relative permeability endpoints to oil and gas, hydraulic fracture properties (permeability, width) and extension and finally the skin factor.

The results of dynamic simulation model show that the model is very sensitive to the amount of gas production and hydraulic fracture vertical extension. We highlight through this example and sensitivity simulations that the GOC should be very close to the well preformation or else the pressure could not be matched. Hydraulic fracture vertical extension is required for matching of BHP and gas rate, without it, the gas rate will be very high in all of the simulation cases. The fracture connecting the upper layer to lower layer with only upper layer perforated. Absolute permeability from log cannot represent to the real permeably measured from well test. To match all historical data absolute permeability, need to be reduce by one order of magnitude. Finally, the model is sensitive to the skin factor for matching of pressure build up.

The main business questions were answered through integrated analysis of the analytical well model and dynamic simulation of single model to identify the source of excess gas and understand the well performance to reduce the uncertainty in production forecast. Fast approach in the single well modeling and efficient approach in the integration in the workflow is described in detail in the paper.
Prototype Inversion of Multi-Probe Chemical Sensing Data to Estimate Inter-Well Distributions
Authors: Chen Hsieh , Poitzsch Martin E
Published: January 2023

For several years, there has been an interest in responsive "NanoProbes," which, when injected along with waterflooding could sense reservoir properties locally along the trajectories they follow from injector to producer wells, giving a low-cost and very deep formation evaluation upon being collected, evaluated, and interpreted with respect to injection point, arrival point, and timings. Here, we introduce these novel "dual-mode" NanoProbe tracers, which can undergo chemical transformations when encountering target analytes within the reservoirs.

We first built the dual-mode chemical sensing tracer functionality into our reservoir simulator and performed forward simulations to acquire model transformed and untransformed tracer breakthroughs. Specifically, the original tracer chemical (denoted tracer-1) can transform into a different chemical (denoted tracer-2) when encountering specific analytes of interest within the reservoir; and the ratio of tracer-1 and tracer-2 from injector-producer pairs provides information about the inter-well analyte distributions. Furthermore, we developed a history matching algorithm based on the iterative ensemble smoother with a rectifier linear unit transformation (ES-MDA-ReLU) that can successfully interpret the inter-well analyte distributions from the chemical sensing tracer data.

We found that traditional ES-MDA algorithm is ineffective for the history matching of the inter-well analyte distributions form the chemical sensing tracer data if the inter-well analyte distributions are discrete; nevertheless, applying a ReLU filter to the analyte distributions combining with ES-MDA algorithm results in greatly improved history matching results. We also studied the spatial and temporal resolution of the inter-well analyte distributions inverted from the barcoded chemical sensing tracer data, whereby we found that the spatial resolution is sensitive to well spacing as well as the tracer travel paths; and the temporal resolution is sensitive to the shapes of the tracer breakthrough curves (notably, good history matching can already be achieved if the early parts of the breakthrough curves are collected from all producers). Finally, we compared the application of chemical sensing tracers on synthetic reservoir models with homogeneous or heterogeneous permeability fields and found that better history matching can be achieved on heterogeneous fields due to the more diverse travel paths of the chemical sensing tracers.

Even though the responsive NanoProbes concept has been found promising, the details of the NanoProbes’ working principles and data processing have yet to be fully developed. We believe this work will bridge these gaps and begin to demonstrate the NanoProbes’ potential as novel formation evaluation tools with direct-sensing, low-cost, and very deep reservoir characterization capabilities.