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Results
Summary Rocks in earth’s crust usually contain both pores and cracks. Typical examples include tight sandstone and shale rocks that have low porosity but contain abundant microcracks. By extending the classic Biot’s poroelastic wave theory to include the effects of cracks, we obtain a unified elastic wave theory for porous rocks containing cracks, adding crack density and aspect ratio as two important parameters to the original theory. The new theory is applied to interpret acoustic velocity log data from tight sand and shale gas formations, whereas the classic Biot theory has difficulty explaining such data. Because the flat- or narrow-shaped cracks can easily deform under acoustic wave excitation, the acoustic property of a cracked porous rock is quite different for different saturation conditions. This allows the new theory to correctly predict the trend of velocity variation with gas saturation in low-porosity rocks, providing a useful interpretation tool for acoustic logging in tight formations.
- North America > United States > Texas > Haynesville Shale Formation (0.99)
- North America > United States > Louisiana > Haynesville Shale Formation (0.99)
- North America > United States > Arkansas > Haynesville Shale Formation (0.99)
SUMMARY New-generation electromagnetic (EM) and sonic logging tools are capable of measuring multi-frequency multi-component data at multiple depths of investigation. This allows us to image the formation around the borehole by using an inversion method. A method is developed for directly obtaining porosity and fluid saturation distributions by simultaneously inverting borehole EM and sonic measurements. This joint inversion reduces the nonuniqueness of determining porosity and fluid saturation distributions, which can not be achieved with either sonic or EM inversion only. We show that the inversion algorithm can accurately obtain porosity and water saturation distributions around the borehole including the zones invaded by the mud filtrate, oil-water contacts, and as well as the dipping structures.
- Geophysics > Electromagnetic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.68)
SUMMARY We present a quantitative approach for the joint interpretation of time-lapse crosswell electromagnetic, time-lapse crosswell seismic, and production data. Because the time-lapse electromagnetic data are sensitive to saturation changes and the time-lapse seismic data are sensitive to both saturation and pressure changes, conditioning the reservoir model to these data can impose additional constraints to the inverse problem, and the resulting reservoir model will honor the saturation and pressure changes due to the recovery process. The reservoir simulator is a key component of the workflow being used to model the recovery process and to compute the time-dependent production data for the wells as well as the temporal and spatial distributions of fluid properties such as saturation, salt concentration, phase density, and pore pressure in the reservoir. These fluid properties together with rock properties can be transformed into the electrical and acoustic properties using prescribed rock physics relations. Three-dimensional finite-difference electromagnetic solver and acoustic solver are then used to calculate electromagnetic and full-waveform seismic responses. We use a multiplicative-regularized Gauss-Newton algorithm to iteratively update the reservoir model to simultaneously minimize data misfits between observed and simulated time-lapse electromagnetic, seismic, and production data. A synthetic crosswell case is employed to demonstrate that the proposed approach can significantly improve the permeability estimation as well as the fluid-front movement monitoring.
- North America > United States (0.29)
- Europe > Norway (0.28)
- Asia > Middle East (0.28)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/7 > Snorre Field > Statfjord Group (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/7 > Snorre Field > Lunde Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/4 > Snorre Field > Statfjord Group (0.99)
- (11 more...)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- (2 more...)
Summary Porosity and pore aspect ratio are two important parameters for reservoir characterization of unconventional gas shales. Porosity estimation helps to determine gas capacity, as well as the bulk density of shales. The pore aspect ratio estimation helps to understand where the stiffest or softest intervals are, and along with density, more favorable for hydraulic fracturing. This work introduces an algorithm to estimate the porosity distribution and an algorithm to estimate the pore aspect ratio distribution of the Haynesville Shale. Both algorithms are based on the self-consistent model and a grid search method. For the porosity estimation, we first calibrated a specific self-consistent model that contains a representative composition assemblage and pore aspect ratio distribution. Then a grid search method was combined with this specific self-consistent model to generate a probabilistic estimation of porosity. The estimated porosity matched with the observed porosity. For the pore aspect ratio estimation, we first generated a group of self-consistent models that contained all plausible pore aspect ratios. Then a grid search based on P-impedance and porosity was applied to the self-consistent models and provided the matching pore aspect ratios. When seismic data from a 3D volume is involved, 3D distributions of porosity and pore aspect ratio can be characterized.
- North America > United States > Texas (1.00)
- North America > United States > Louisiana (0.74)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Processing (0.70)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.30)
- North America > United States > Texas > Haynesville Shale Formation (0.99)
- North America > United States > Louisiana > Haynesville Shale Formation (0.99)
- North America > United States > Arkansas > Haynesville Shale Formation (0.99)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
SUMMARY Shear-wave velocity is an indication of the shear strength of the ground since the velocity is related to the shear modulus. Therefore, monitoring the velocities is useful for site characterization and disaster prevention. We estimate the time-lapse change in shear-wave velocity as well as shear-wave splitting in the shallow subsurface throughout Japan by applying seismic interferometry to the data recorded with KiK-net, a strong-motion network in Japan. Each KiK-net station has two receivers; one is on the surface and the other is in a borehole. Using seismic interferometry, we extract the shear wave that propagates between these two receivers. Because KiK-net has continuously recorded strong motion seismograms since the end of 1990s, the data are available for time lapse measurements. After the Tohoku-Oki earthquake, the shear-wave velocity decreases about 5% in a region 1200 km wide and anisotropy increases more than 10%. From seasonal averages, we find the velocity and precipitation have a negative correlation.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (1.00)
ABSTRACT Modeling the stress conditions inside hydrocarbon and geothermal reservoirs is important to predict fracture behavior during injection of fluids. We analyze the influence of elastic heterogeneity on stress and fracture strength distribution in rocks. Therefore, we simulate the distribution of elastic modules inside a reservoir rock as a 3D fractal random medium according to parameters obtained from sonic well logging data. Using an ABAQUS finite element stress analysis model we determine the stress field inside the rock volume. By applying geo-mechanical considerations we then compute the fracture strength distribution and analyze relations between elastic modules stress state and fracture strength. The stress modeling analysis performed in this paper suggests that the stress state in elastically heterogeneous rocks can be highly heterogeneous. Our modeling study according to elastic heterogeneity derived from sonic well log data along the continental deep drilling (KTB) main hole results in a broadly distributed fracture strength between -10 to 20 MPa. We find strong relations between elasticmodules, stress state and fracture strength, which can be applied to predict the stress distribution in hydrocarbon and geothermal reservoirs and the occurrence probability of fluid injection induced seismicity.
- Geophysics > Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Well Drilling > Wellbore Design > Wellbore integrity (1.00)
- Well Drilling > Pressure Management > Well control (1.00)
- Well Completion > Hydraulic Fracturing (1.00)
- (3 more...)
Summary We present elastic finite-difference modeling results over a geologically realistic 2D representation of the Halfmile Lake volcanic-hosted massive sulfide deposit, New Brunswick, Canada. The model is constrained by geological information from surface mapping and boreholes whereas petrophysical properties are provided by wireline logging data acquired in two boreholes intersecting different parts of the deposit. We analyzed the P-P, P-S, S-P, and S-S responses of the Lower and Deep mineralized zones and assessed some compositional effects by substituting massive sulfides with gabbro properties in the model. Finite-difference modeling results predict complex scattering including P-P, P-S, S-P, and S-S waves generally having strongest amplitudes in the stratigraphy down-dip direction. The P-S, S-P, and S-S scattered waves, if properly recorded on multi-component data, represent useful signal that could help the targeting of deep sulfide mineralization. Finite-difference simulations further reveal phase-reversals on P-P wavefields scattered at the massive sulfide zones. The phase reversals are not observed for gabbro inclusions, suggesting that this signature could be used to discriminate gabbro units from sulfide mineralization. The FD simulation successfully reproduces many events of the VSP data, in particular P-S and S-S events on the radial component and P-P and S-P events on the vertical component.
- Geology > Mineral > Sulfide (1.00)
- Geology > Geological Subdiscipline (1.00)
ABSTRACT We advance a theoretical model for mudstones and carbonates enriched with solid organic matter – kerogen. The model on the scale smaller than the sonic log wavelength (<0.5 m) is based on the summation of the compliance contributions of the mineral matrix, non-kerogen porosity, kerogen with nanoporosity, and mostly bedding-controlled microcracks. The resultant bedding-normal elastic stiffnesses can be viewed as air-dry moduli and their transformation into fluid-saturated ones is achieved by Gassmann’s equation. Hence, we make an assumption that the majority of mature organic shales are subject to relaxed undrained response during seismic/sonic wave propagation. This assumption is validated using the relaxed-to-unrelaxed transition frequency equation proposed by Gueguen et al. We find a good agreement between our model predictions and field observations, such as sonic logs and VSP.
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.80)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling (0.38)
Summary A recent advance in single-well reflection imaging is the utilization of a dipole acoustic system in a borehole to radiate and receive elastic waves to and from a remote geological reflector in formation. This paper substantiates this dipole-acoustic imaging technology by numerically simulating the radiation and reflection of the wavefield generated by the borehole dipole source and analyzing the receiving sensitivity of the dipole system to the incoming reflection waves. The analyses show that a borehole dipole source can radiate a compressional wave (P wave) and two types of shear waves (i.e., SV and SH waves) into the formation. The SH wave has wide radiation coverage and the best receiving sensitivity, and is most suitable for dipole-shear imaging. In an acoustically slow formation, the dipole-generated P wave has strong receiving sensitivity and can also be utilized for reflection imaging. An important feature of dipole imaging is its sensitivity to reflector azimuth, which results from the directivity of the dipole source. By using a four-component data acquisition method to record the dipole-generated reflection signal, the reflector azimuth can be determined. The numerical simulation results provide a solid foundation for the dipole acoustic imaging technology.
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
Summary Predicting missing logs is an essential tool for geophysicists especially in mature oilfields. The limited budget in acquiring P-wave or S-wave logs forces geophysicists to work with data constraints and come up with methods to predict the missing logs. Although basic neural network for log prediction is included in many rock physics software, yet it is not possible to fully customize the parameters to build the network structure, making the method less appealing to users. This study reveals what is inside the black box and improves the capabilities of the predictions. The enhancement is achieved by (1) changing the algorithm from conventional to Bayesian regularization neural network, (2) using stratigraphic constraints, and (3) allowing neural nodes to vary according to the number of data. This improved neural network method is proven to be more robust than other empirical methods and redefines the standard of missing log prediction.
- Geology > Geological Subdiscipline > Stratigraphy (0.63)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.41)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.41)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Processing (0.68)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Neural networks (1.00)