A new azimuthal electromagnetic (EM) logging-while-drilling (LWD) tool has been developed with multiple tilted antennas to measure three-dimensional (3D) electromagnetic fields. Multiple field trials successfully demonstrated the ultradeep detection range of more than 200 ft (60 m) with various transmitter-to-receiver spacings and operating frequencies, providing valuable geomapping insight for large-scale reservoir development. Additionally, this paper reveals the tool's capabilities in different geosteering applications, requiring different depth of detection (DOD) ranges for landing a well, optimizing well placement in thin reservoirs, and eliminating the need for a pilot hole.
This paper discusses in detail a new 3D finite-difference (FD) method to simulate realistic and complicated formation structures in three dimensions, enabling accurate formation interpretations and inversion of reservoir geology. Solving the scattered potential boundary value problem with the 3DFD numerical algorithm simulates the EM signals in this new LWD ultradeep application, and the modeling accuracy was benchmarked alongside in-house modeling codes and 3D commercial software. To accelerate the computation in the 3D modeling, sliding window, multicore parallel cloud computing, and decoupling between model pixel grid and FD simulation grid have been implemented for practical applications. Additionally, 3D modeling is used in the inversion to provide more accurate and complex reservoir determinations.
In addition to inversion, the tool provides 3D azimuthal multispacing, multifrequency geosignal, and resistivity measurements. Using the inversions and the 3D azimuthal images of the geosignal and resistivities enable improved reservoir understanding and geosteering decisions for the three dimensions. This paper describes two field trials from relatively thin to thick reservoirs to establish great and flexible geosteering performance because of multispacing, multifrequency measurements, and a robust signal and inversion process to optimize wellbore placements in the reservoir.
Chen, Li (Schlumberger) | Winkelman, Ben (Talos Energy) | Wilkinson, Tim (Talos Energy) | Meyer, John (Deep Gulf Energy) | Mullins, Oliver C. (Schlumberger) | Forsythe, Julia C. (Schlumberger) | Hayden, Ron S. (Schlumberger) | Xu, Weixin (Schlumberger) | Shan, Dan (Schlumberger) | Canas, Jesus A. (Schlumberger) | Garcia, German (Schlumberger) | Zuo, Julian Y. (Schlumberger) | Gan, Yunyan (Schlumberger) | Chao, Jiun Chi | Hall, Donald L.
Fluid geodynamics processes can alter the hydrocarbon accumulation in the reservoir and complicate the fluid distribution. The processes can be one or combination of late gas charging, biodegradation, water washing, spill-fill charging etc. Fault block migration is another geological process can take place after fluid charging, which results in the fluid re-distribution and brings extra challenges for reservoir evaluation. The understanding and evolution of the fluid geodynamics and fault block migration processes become the key to reveal reservoir connectivity, reservoir charging and geological structural evolution.
This paper elaborates a case study from a Talos Energy's discovery in deep-water Gulf of Mexico, Tornado field from Pliocene formation, to illustrate the connectivity analysis cooperating fault block migration and fluid geodynamics. The high-quality seismic imaging delineated the sand bodies in the reservoir with a gross pay of 400 feet. The two wellbores in the main block A and one wellbore in adjacent block C all exhibit two primary stacked sands separated by an intervening shale break. The RFG (Reservoir Fluid Geodynamics) workflow was applied to this field for connectivity analysis, with integration of the advanced DFA (Downhole Fluid Analysis) data from wireline formation testing, advanced analytical and geochemical analysis of the oil, laboratory PVT and fluid inclusion testing data. The advanced DFA data includes fluid color (asphaltene), composition, Gas-Oil-Ratio (GOR), density, viscosity, and fluorescence yield to help assess connectivity in real-time and after laboratory analysis, which helped to optimize data acquisition and allow the early completion decisions. The DFA data was analyzed using the Flory-Huggins-Zuo Equation of State for asphaltene gradients and the Cubic Equation of State for GOR gradients. The resulting DFA-RFG analysis shows that in the main block A, the fluids in the upper and lower sands are separately equilibrated, in spite of the young age of the reservoir, indicating there is good lateral connectivity in each sand. The asphaltene content of the oil in the upper sand is slightly, yet significantly smaller, than that in the lower sand indicating that the intervening shale might be a laterally extensive baffle or possibly a barrier. Subtleties in the DFA data are more consistent with the shale being a baffle. Moreover, the biomarker analysis shows that all oils encountered are indistinguishable from a petroleum system perspective. This reinforces the DFA-RFG interpretation. However, seismic imaging shows that the intervening shale is not present at the half lower section of the reservoir. With guidance from RFG connectivity analysis, it is consistent with the geology understanding that the shale becomes thinner which beyond the seismic resolution. The paleo flow analysis based on high definition borehole images integrated with seismic interpretation confirmed that upper sand scoured away the intervening shale. The deposition modeling supports that the shale is a baffle.
The sands from the well in the adjacent block C show a vertical shift of asphaltene distribution from block A. The extent of the 360feet vertical offset matches the fault throw from seismic imaging and from log correlation. The fluid properties including asphaltene content, API gravity, methane carbon isotope, GOR, density, are all consistent with the fault block migration scenario. A further complexity is that the upper fault block received a subsequent charge of primary biogenic gas after fault throw. This innovated approach provides guidelines for geophysical and geological interpretation regarding fault block migration and the hydrocarbon charging sequence. The field connectivity conclusions have been confirmed by over 1-year of production history to date.
Accurate determination of the dew point pressure of gas condensates in nano-porous ultra-low permeability reservoirs is crucial to prevent liquid dropout inside the formation. This paper presents a proof of concept experimental data and procedure to explain the effect of the pore size distribution on the degree and direction of the shift in the saturation pressure of gas mixtures under confinement compared to the bulk behavior.
We built a packed bed of BaTiO3 nanoparticles, providing a homogenous porous medium with pores of 5 to 50 nm, providing a volume more than 1000 times larger than typical nano channels. We designed an isochoric apparatus to monitor pressure for a fixed volume of fluid under confinement and bulk conditions simultaneously. A binary mixture of ethane-pentane undergoes an isochoric process with pressures of 10 to 1500 psi and temperatures of 290 to 425 K. The result is a set of Isochoric lines for the bulk and confined sample, plotted on the phase envelope to demonstrate the change in saturation pressure.
Many attempts in explaining the shift in saturation pressures of the reservoir fluid confined in the narrow pores of unconventional reservoirs compared to those of the bulk can be found in the literature. However, there are some contradiction between the predicted behavior using different mathematical approaches. Experimental data could be substantially helpful in both validating models and improving the understanding of the fluid behavior in these formations. Contrary to what many published models predict, our results show that confinement effects shift the dew point pressure towards higher values compared to the bulk for a fixed temperature in the retrograde region. In the non-retrograde region, however, this shift is towards lower dew point pressure values for the confined fluid compared to the bulk. Capillary condensation is assumed to be the main source of the deviations observed in the behavior of fluids inside nanopores. We evaluate published models, including those based on EOS modifications, by comparing it to experimental results to provide a quantification of their accuracy in predicting saturation pressure values for confined mixture.
This paper provides an alternative approach to examine the effect of pore size on phase behavior over a decent and practical range of pressures and temperatures. The synthesized porous medium is very helpful in uncoupling the effect of pore size from the effect of mineralogy on the observed deviations in behavior. Experimental findings are valuable for validating existing theories and can be used to adjust proposed mathematical approaches towards better predictions of saturation pressures for other systems.
Present day innovations in seismic acquisition tools and techniques have enabled the acquisition of detailed seismic datasets, which in many cases are extremely large (on the order of terabytes to petabytes). However, data analysis tools for extracting information on critical subsurface features such as fractures are still evolving. Traditional methods rely on time-consuming iterative workflows, which involve computing seismic attributes, de-noising and expert interpretation. Additionally, with the increasingly widespread acquisition of time-lapse seismic surveys (4D), there is a heightened demand for reliable automated workflows to assist feature interpretation from seismic data.
We present a novel data-driven tool for fast fracture identification in BIG post-stack seismic datasets, motivated by techniques developed for real-time face detection. The proposed algorithm computes spatiotemporal amplitude statistics using Haar-like bases, in order to characterize the seismic amplitude properties that correspond to fracture occurrence in a unit window or voxel. Under this approach, the amplitude data is decomposed into a collection of simple-to-calculate "mini-attributes", which carry information on the amplitude gradient and curvature characteristics at varying locations and scales. These features then serve as inputs to a cascade of boosted classification tree models, which select and combine the most discriminative features to develop a probabilistic binary classification model. This overall approach helps to eliminate the computationally-intensive and subjective use of ad-hoc seismic attributes in existing approaches.
We first demonstrate the viability of the proposed methodology for identifying discrete macro-fractures in a 2D synthetic seismic dataset. Next, we validate the approach using 3D post-stack seismic data from the Niobrara Shale interval within the Teapot Dome field. We show the applicability of the proposed framework for identifying sub-seismic fractures, by considering the amplitude profile adjacent to interpreted fullbore microimage (FMI) well log data. The upscaled spatial distribution of the predicted fractures shows agreement with existing geological studies and align with interpreted large-scale faults within the interval of interest.
Recently, there has been a drive towards a risk-based approach to plug & abandonment (P&A) design. To apply a risk-based approach for decision-making, i.e. to decide if a P&A design is acceptable or not, risk acceptance criteria have to be established and be approved by authorities. This paper presents the core of a risk-based approach, and then present three alternative risk acceptance criteria based on leakage risk of permanently plugged and abandoned wells.
The core elements of the risk-based approach for evaluation of the containment performance in permanently plugged and abandoned wells consist of estimating probability of leakage and associated leakage rates for any proposed P&A design. These will then have to be used to evaluate the acceptability of the design, by comparing them to some defined acceptance criteria. Different principles can be followed to define such criteria, such as being consistent by accepting risk levels which have been considered acceptable in other situations, environmental survivability or considering the cost-benefit to optimize the allocation of funds.
The approach and principles used are described and applied in the context of P&A design. Based on the specification of an actual gas producing well that was permanently plugged and abandoned on the Norwegian Continental Shelf (NCS), a synthetic case study is established. Simulations are carried out to provide estimations of the core elements of the risk-based approach, i.e. leakage rate and probability of the leakage, for the synthetic case. Three examples of risk acceptance criteria are then presented and discussed. The estimations derived from simulations for the synthetic case study are used to exemplify the strengths and weaknesses of the three acceptance criteria.
Pressure-and rate-time data at wells producing the Wolfcamp shale are evaluated by a model based on a framework using subdiffusive concepts. Quantitative measures to estimate heterogeneities in the fractureand matrix-systems are provided. Multiple transfer mechanisms and complex structures govern the dynamic performance of the reservoir. Long-term depletion is governed by the matrix system; our evaluations indicate that excellent coverage is obtained in draining the lateral extents of the reservoir rock. As a physics-based model is used to evaluate responses, the suggested procedures are both extendable and scalable.
A method is presented to identify intervals in shale oil reservoirs that contain moveable hydrocarbons with a novel geochemical productivity index,
Shale oil is both source and reservoir rock. Hence, it is critical to know both its organic matter maturity and oil/water flow capacity. The introduced
Use of the
The key novelty of the paper is that it develops a continuous curve of an index that is easy-to-use and is powerful for identifying intervals with moveable hydrocarbon potential. This is true even in those intervals without laboratory data due to the continuity of the
Modeling shale gas relative permeability,
Since early 2016, commodity prices have been gradually increasing, and the Permian Basin has become the most active basin for unconventional horizontal well development. As the plays in the basin are developed, new infill wells are drilled near pre-existing wells (known as "parent wells"). The impact of pressure depletion caused by adjacent existing producers may have a larger role in the performance of these new infill wells. How the various well spacing impact with the degree of reservoir pressure depletion from parent well is more important than ever for operators to optimize the completion design. Through data analytics and comprehensive fracture/reservoir modeling this paper studies how changes in well spacing and proppant volume in the Spraberry, a main formation in the Permian Basin, will impact new infill well performance. The studies in this paper are focused on the Midland Basin.
A public database was used to identify the number of parent and child wells in the Midland basin. Data analysis of production normalized by total proppant and lateral length shows that parent wells outperform infill, or child, wells. To further understand the relationship between parent and child wells, a reservoir dataset for the Spraberry formation was used to build a hydraulic fracture and reservoir simulation model for both the parent well and a two-well infill pad. After production history matching a P50 type well as the parent well, three periods of production depletion were modeled (6 months, 3 years and 5 years) to understand the timing impact on the infill well production. A geomechanical finite-element model (FEM) was then used to quantify the changes to the magnitude and azimuth of the in-situ stresses from the various reservoir depletion scenarios. A two-well infill pad was then simulated into the altered stress field next to the parent well at various spacings between the parent and child wells. A sensitivity was then performed with different stimulation job sizes to understand the volume impact on created complex fracture propagation and total system recovery.
This study can help operators understand how well spacing, reservoir depletion, and completion job size impact the infill well performance so they can optimize their infill well completion strategy.
Pemper, Richard (Weatherford International) | Pereira, Alex (Weatherford International) | Hou, Guojing (Weatherford International) | Dolliver, Darrell (Weatherford International) | Tudge, Joanne (Weatherford International) | Kharrazi, Jennifer (Weatherford International) | Chok, Hamed (Weatherford International) | Schmid, Gregory (Weatherford International) | Mekic, Natasa (Weatherford International) | Blankinship, Tom (Weatherford International) | Epstein, Robert (Weatherford International) | Cave, Tim (Weatherford International) | MacPherson, Adam (Weatherford International)
A new geochemical logging tool has been designed and developed for the precise determination of formation chemistry, mineralogy, and lithology, as well as the identification of total organic carbon (TOC). The primary elements identified by the system include aluminum, calcium, carbon, chlorine, hydrogen, iron, magnesium, oxygen, potassium, silicon, sulfur, thorium, titanium, and uranium. These elements are utilized to identify the minerals present in both conventional and unconventional formations.
Tool operation begins by emitting high energy 14 MeV neutrons into the formation from a pulsed neutron generator, and the resulting gamma rays are intercepted by a high resolution, state of the art, LaBr3(Ce) detector. In order to exclude background gamma rays and provide a clean capture spectrum, a boron coating has been placed on the housing. The 3.25-inch tool diameter makes the system easier to operate in small boreholes as well as in horizontal wells.
The extensive set of detected elements is made possible by the PNG, where high speed electronics are incorporated to accrue both capture and inelastic energy spectra. A Levenberg-Marquardt matrix inversion algorithm is employed to separate the spectra into their fundamental elemental components. Characterization of the system has been achieved through numerous measurements in more than 30 formations from a newly constructed Rock Formation Laboratory in Fort Worth, Texas as well as at the Callisto Facility in the United Kingdom. A significant number of core samples were obtained from these formations and analyzed for elemental and mineralogical composition. Extensive use of MCNP modeling was exploited for the design and characterization of the system.
The final lithological and mineralogical interpretation is guided by the elemental concentrations of the various elements, as well as the computation of intrinsic sigma. Magnesium is used to differentiate between calcite and dolomite in carbonate formations. Aluminum, iron, and potassium, in addition to silicon, provide the information required to distinguish the various clays in sand/shale formations. Sulfur is vital for the identification of both pyrite and anhydrite. Ternary plots are generated to aid in the final interpretation. To demonstrate the effectiveness of this work, log examples from the field are provided.