Development of stress sensitive reservoirs, especially in challenging environment, is raising awareness that geomechanics is a vital aspect of reservoir management. Understanding reservoir geomechanical behavior becomes more and more important for petroleum industry. A significant changes in formation pressure caused by depletion will induce deformation and stress/strain changes in the reservoir and the surrounding formation, understanding in-situ stresses and how stress changes in and around the reservoir due to depletion is important in a multidisciplinary approach to reservoir characterization and management. These changes in stresses/strain affect the reservoir as well as the overburden and underburden formation, which directly affect drilling and stimulation operations strategies. Reservoir compaction, shear casing and well damage, cap-rock integrity, fault reactivation and sand production can occur during reservoir depletion. To address these issues, 3D geomechanical models have been developed (which describe the state of stresses in the reservoir and overburden).
The demand for unconventional gas is rapidly increasing to provide enough energy to maintain sustainable growth for industrial countries. Even oil producers can develop UG to be directed to internal industrial and power consumptions. As Unconventional gas reservoirs are located in deep high-stress formations, one of the critical challenges gas producers are facing is to develop a cost effective stimulation method that can reduce production cost to lower than Break-even.
In this paper a novel stimulation method, based on thermochemicals, is introduced. Thermochemicals when injected in tight reservoirs generate localized pressure-pulses, which result in creating microfractures, improve permeability and increase stimulated reservoir volume (SRV). Tight core samples were treated with thermochemicals and the impact on mechanical properties were studied. Generated localized pressure was clearly detected during Coreflood treatment. Microstructural and mineralogical properties were also investigated using microscopy and spectroscopy. CT-scan, micro CT-Scan, Young's modulus, Poisson's ratio and ultrasonic velocities were measured pre and post treatment. Results showed creation of fractures and microfractures, which resulted in improved rock conductivity.
Results show that, micro-factures are created inside the used sample due to the in-situ generation of heat and pressure. The density of those micro-factures is strong function of the chemical concentration and the injected volume. Creation of micro-factures leads to improve the formation conductivity and reduce the capillary forces, therefore, enhances the hydrocarbon recovery. The outcome of this study is to understand the impact of thermochemical treatment on rock integrity. The ultimate objective is to establish a relationship between the injected chemicals and the alterations of formation properties such as permeability and porosity. This work will serve as a baseline for designing and conducting thermochemical operations for hydrocarbon reservoirs.
In this study a novel stimulation technique to increase stimulated reservoir volume (SRV) is presented. In basins with excessive tectonic stresses, the current novel treatment can become an enabler to deeply stimulate well stages which otherwise left untreated. A new methodology is developed to lower fracturing cost and increase unconventional gas production. A better connectivity reduces the required number of hydraulic fracturing-stages.
Reservoir evaluation of source rock is still a challenge because the geochemical assessment of the kerogen content is complicated and time consuming. Existing traditional methods to characterize kerogen involves the removal of inorganic minerals which is a critical preliminary step. The incomplete isolation of kerogen may introduce some errors and uncertainties in kerogen content estimation. The alteration of kerogen microstructure during this process has also been documented. The current approach still requires input from geochemical measurement of total organic carbon (TOC) while the conversion of TOC to kerogen volume requires the precise value of a conversion factor and kerogen density. Overall, there is yet a standard lab or field scale approach to characterize kerogen content. These difficulties and uncertainties prompt the motivation to attempt a new methodology to quantify the kerogen content of unconventional shale from porosity measurements.
Porosity is the basic rock property that is related to the volumetric average of pore space. The distinction between the total and effective porosity is meaningless for shale and this characteristic property has enabled the preservation of its organic content. The recent popularity and growth of different measurement techniques is in part closely tied to the near zero porosity of shale. Two special cases of practical interest are NMR and density porosity measurements which can both be measured in the rock physics lab and well logs. NMR porosity is sensitive to 1H which is naturally enriched in kerogen whereas density porosity must be calibrated to the mineral matrix.
Based on porosity measurements, the emerging aproach is that the kerogen volume fraction is the contrast between NMR and density porosity. Although, the theoretical basis of this approach is not satisfactory, it is straightforward and far less complicated than the existing approaches to quantify kerogen content. We investigate this concept further based on laboratory measurement. We conducted laboratory measurements of NMR porosity, bulk density, grain density and TOC on Qusaiba shale to characterize its kerogen content. In our approach, we conducted the NMR experiment on the shale samples in the dry state without fluid saturation.
Applications of oil-in-water emulsion (O/W) emulsification technology in enhanced recovery and pipeline transportation of heavy oil can be limited by several factors including salinity of the reservoir or process water, process temperature, and water cut. In this investigation, laminar flow of O/W was simulated in a pipeline to investigate the effect of salinity of aqueous phase (NaCl) and water cut on flow characteristics of the fluid. The case was simplified by considering the O/W as a stable, pseudo-homogeneous, single-phase fluid within the conditions operated. Pertinent to the objective of the study, at flow reference temperature, Tref 30oC, the pressure drop at 30% water cut was 931Pa compared to 84.6 Pa at water cut of 50% (reference working fluid without NaCl). In contrast, the pressure drop was 239Pa, 142Pa, 124Pa, and 82.9Pa at 70000ppm, 40000ppm, 20000ppm, and 10000ppm salinity in the aqueous phase, respectively. In addition, the maximum dynamic viscosity imposed by the fluid, was 81000cP at 30% water cut compared to 14000cP from the reference fluid. The dynamic viscosity obtained from 70000ppm salinity content was 34000cP. Moreover, the results confirm facile application of emulsification technology for pipeline transportation of bitumen from large reduction in pressure drop (99%) regardless of the water cut and salinity.
During waterflooding, pore-throat structure of the porous media in the reservoir changes continually, which causes the great challenge in reservoir modeling and simulation. However, through the evolution mechanism of pore-throat characteristics for the reservoir during waterflooding has been intensively investigated in the past several decades, the essential controls on pore-throat structure evolution of reservoir rocks are not studied much. It is of theoretical and practical significance to use analytical methods to study the evolution of pore-throat characteristics of porous media during waterflooding. However, because of the disordered and extremely complicated microstructures of porous media, the theoretical model for stress sensitivity is scarce. The objective of this work is to establish a novel and reasonable quantitative model to determine the essential controls on pore-throat structure evolution of reservoir rocks. The theoretical model is derived from the fractal geometry. The predictions from the proposed model agree well with the available experimental data presented in the literature, which verified the novel quantitative model. There is no empirical constant and every parameter in the model has specific physical significance. In addition, the evolution rule for the pore-throat structure parameters has been obtained. The results show that the pore-throat structure of porous media becomes more complex and more heterogeneous after waterflooding. The pore-throat parameters (e.g. porosity, permeability, the maximum pore-throat radius, average pore-throat radius and sorting coefficient, etc.) will change during waterflooding. This work presents accurate and fast analytical models to perform the evolution rule of pore-throat characteristics of porous media during waterflooding. The proposed models can reveal more mechanisms that affect the coupled flow deformation behavior in porous media.
A detailed study comparing various properties and attributes of local Saudi Arabian sand (processed and unprocessed) and high-strength proppant (HSP) for hydraulic fracturing applications is discussed. Further, quartz grain crystallinity, texture, quality, and mechanical durability (strength) are described and an insight into the prospects of sand application viability during hydraulic fracturing is provided.
An in-depth comparison of processed sand, unprocessed sand, and readily available HSP widely used in the industry was performed. It is well known that the Middle East region, particularly Saudi Arabia, has an abundance of sandstone formations ranging from the Cambrian to Quaternary age; outcrops of these formations extend from northern to southern parts of Saudi. These formations have varying grain sizes and other physical attributes that must be studied to grade their possible performance as hydraulic fracturing proppants. Unprocessed sand samples were collected from various central and southern Saudi sandstone formations. Petrographic analysis, including thin section and scanning electronic microscopy (SEM), was conducted on sand samples to quantify the percentage of polycrystalline quartz grains and define their surface features. Crush-resistance testing was performed on the samples to compare the mechanical durability of the sands and HSP.
The results of this study confirmed that polycrystalline quartz grains are more abundant in coarse-grained sandstones than those fine-grained. Mechanical durability decreased with an increased percentage of polycrystalline quartz grains, strained grains (with undulose extinction), and surface features. The metamorphic nature of the quartz grain source rock and intense chemical weathering along the quartz grain surface reduce its strength. HSP demonstrates greater mechanical durability compared to processed and unprocessed sand, keeping in mind, the processed sand was from a specific sandstone formation.
The suitability of Saudi sandstones for the petroleum industry's use is dependent on the mechanical durability of quartz grains, which, in turn, depends on the source and chemical weathering of those grains. Comparatively, HSP is more durable and mechanically strong; however, processed sand has an edge over unprocessed sand.
The purpose of the paper is to present the results of using local sand resources in Saudi Arabia for the manufacture of resin coated proppant as a ceramic proppant alternative for deep conventional gas development. Crushed Miocene sandstone, old river sand and dune sand has been tested for a source to manufacture resin coated sand proppant. Compared to Northern White Sand in USA, each sand source has its own set of limitations such as angularity, low aspect ratio, clay, carbonate scale or iron oxide coating, and/or micro-fracture damage. Complete resin bonding to the particle surface required clean quartz surface free of sharp edges and no dust contamination. Conductivity testing of the resin coated sand at reservoir pressure and temperature reveals that over 95 wt% of the mesh sized sand particles should pass the room temperature crush test before coating.
A major challenge in carbonate reservoirs is the highly-fractured nature of the rock. The flow rate may be high or low depending on the targeted fracture clusters. In addition, it is possible that flow rates vary from one region of the reservoir to another. Smart wells furnished with smart completion strategy presents great prospects to produce such reservoirs intelligently, thereby, helping to deal with heterogeneities rather smartly. It is established that early water break-through occurs when multi-lateral wells are completed with constant choke settings, and therefore one way to mitigate this problem is using smart completions that manage the unexpected production through fractures, thereby increasing ultimate recovery. The early water breakthrough is obvious because if a lateral section intersects a clusters of fracture zone, there is a possibility that these fractures may connect with the water zone that may trigger the breakthrough. This can be managed by preferentially regulating production from manifold laterals.
The evident communication among the various laterals of the mother bore raises difficulty in optimizing the production from the variable productivity intervals. In theory, the optimization scheme of smart completion involves different constraints, nevertheless, the settings of the smart inflow control valve (ICV) is the single most important parameter that may prove to be the differentiating factor between a high producing well to a poorly producing one. This study engrosses its effort on the reservoir engineering characteristics of finding the optimum choke setting that would lead to maximum recovery.
Computational Intelligence through Particle Swarm Optimization (PSO) is utilized as the integral algorithm to determine the optimal ICV configuration for a fishbone well in a naturally fractured carbonate reservoir. A commercial black oil simulator was used to determine the objective function; whose role here is to evaluate the fitness of a configuration of the choke; this was carried out under a workflow programmed in the MATLAB programming language that coupled the optimization algorithm with the numerical simulator. A single fishbone well, having 15 laterals was studied in order to see the effect of the fracture network on the water breakthrough and consequent impact on recovery.
Three different scenarios are developed to see the impact of optimization; a base case employing only multilateral well technology without the smart well completion, a smart well completion scheme with no optimization and finally the optimized smart well completion. The results very sequentially clarify the need for not only optimization but also highlights the role of intelligent completions for wells in the reservoir being studied. It is evident that without using smart wells, the water breakthrough is relatively earlier and produces less hydrocarbons, but as the use of smart wells is incorporated, the results start improving and for complete optimization scheme of the ICVs, it is observed that the recovery has increased by almost 80% from 21% to 38%. Moreover, the time to water breakthrough and eventually the cumulative water cut has also been managed quiet significantly.
This paper presents a novel/cost-effective hydrophobic material based 9-octadecenoic acid grafted graphene (POG) for oil/water separation. Graphene derived from graphite was modified with 9-octadecenoic acid to obtain 9-octadecenoic acid grafted graphene (OG). Then, emulsion polymerization of styrene was performed on OG to produce polystyrene branches on 9-octadecenoic acid grafted graphene (POG). Three different composites were prepared by varying the amount of 9-octadecenoic acid grafted graphene used as follows: POG25, POG50, and POG75. The three materials were characterized by using N2-physisorption and Fourier transform Infra-red (FTIR). The BET surface area of POG75 was 288 m2/g while POG50 was 225 m2/g and POG25 was 79 m2/g. These materials were evaluated for their oil/water separation efficiency using model mixture. The results showed that the higher the ratio of the 9-octadecenoic acid grafted graphene, the higher the oil removal efficiency of the material and the faster the rate of the adsorption. The materials showed not only high efficiency but also fast uptake of the certain quantity of the oil just within 1 minute. This can be explained by the high hydrophobicity nature of the materials which repel the water as confirmed by the contact angle of approximately 150°. POG75 showed promising results to be a good candidate adsorbent materials for oil removal from produced water where it displays the highest adsorption capability to organic compounds and the highest BET surface area. POG75 was regenerated and its performance was tested again. This material showed a slightly reduced adsorption rate in the first cycle compared to the fresh material. However, the adsorption rate was constant for the next several cycles. POG75 has the potential to be utilized to remove oil contaminants from produced water.
The drilling engineers are overmild with huge amount of data-points, argue the need to develop Artificial Intelligent (AI) and Machine Learning (ML) models to crunch these huge amount of data generating decision-like information. There are a lot of challenges developing such approach, varying from computational power, lack of subject matter experts, and develop the optimum algorithm. But the main bottleneck is the quality of the data. Regardless of how advance AI/ML model, if the data is bad, the model will generate bad result; garbage-in garbage-out. The scope of this paper is to use metaheuristics models to improve the data quality. The process start by extracting Hook-Load drilling real-time data. And explore the raw data quality using visualization and statistical methods. Then apply several Metaheuristics models to generate functional approximation equation that identify/ follow the trend of the good-quality data. This will be by employ multiple scenarios with different degree of randomness that lead to the highest matching which generate the high quality level. The process will cover different technique including Greedy, Hill-Climbing, Random Search, and Simulated Annealing. During this process hundreds of thousands of scenarios will be conducted to simulate the Hook-Load data, to identify the optimum functional approximation equation that match the best data quality. Which can then safely integrated into the advance Artificial Intelligent and Machine Learning models. Running such process require an expensive computational cost, since it includes huge amount of real-time data need to be process under complex advance models. Moreover it require a deep understanding of the internal process of each models to ensure finest manipulating them to get the optimum data quality result. Running these scenarios, lead successfully to functional approximation that spill the data behavior, with Mean Absolute Error (MAE) equal to 10.5. It is worth height that functional approximation is very expensive in term of time and complexity, but it generate the highest quality result, leading to better AI/ML model. Moreover it is the most dynamic approach allowing it to be applied in other drilling real-time parameters as well. Utilizing Metaheuristics approach to improve the data quality is new to the upstream domain in general, with almost no application in drilling in specific. The novelty is to introduce this advance technique into the drilling real-time data domain, it will sharply improve the data quality leading to higher Artificial Intelligent and Machine Learning prediction/ analytical models. It worth mentioning that such approach will run all those simulation/ scenarios and adjust itself automatically with almost no manual interference. Leading to self-data-driven data-quality model.