Hydrocarbon-saturated Reservoirs Research Articles

The old and new of fluid indicators: An overview and application

Over the past decades, numerous fluid indicators have been introduced and proven to be sensitive to hydrocarbon presence. Mathematically, fluid indicators measure the deviation of hydrocarbon-saturated rocks from their background in a specific domain or space. The ideal indicator is defined as an attribute that responds to hydrocarbon presence only; at shale- or brine-saturated intervals, it shows weak or no noticeable variation. In this paper, we collect and review several common fluid indicators used in the oil industry. The collection includes common reflectivity-based indicators and impedance-based indicators from the late 1980s to present. We present an overview of these fluid indicators, their past and current uses, their limitations, and their integration using machine learning. We examine these indicators on 35 data samples collected from different world basins and analyze their performance using recent data analysis techniques. We then apply the attributes on real seismic data from offshore Australia and test their ability to detect hydrocarbon-saturated reservoirs. In closing, we invoke machine learning approaches to combine the attributes and produce a fluid probability attribute.

Implementation of the Poisson Impedance Inversion to Improve Hydrocarbon Reservoir Characterisation in the Poseidon Field, Browse Basin, Australia

The prediction process of lithology and fluid content is the most important part of reservoir characterization. One of the methods used in this process is simultaneous seismic inversion. In the Poseidon field, Browse Basin, Australia, the parameters generated through simultaneous seismic inversion cannot accurately characterize the reservoir because of the overlapping impedance values between hydrocarbon sand, water sand, and shale, which cause a high level of ambiguity in the interpretation. The Poisson impedance (PI) inversion provides a solution to this problem by rotating the impedance a few degrees through coefficient c. Coefficient c is obtained through the target correlation coefficient analysis by finding the optimum correlation coefficient between the PI and the target log, namely, gamma rays, effective porosity, and resistivity. The results show that the PI gives better outcomes in separating hydrocarbon-saturated reservoir zones. Based on the results of the lithology impedance–gamma rays, the ϕI-effective porosity cross-plot, and the fluid impedance-water saturation (Sw) cross-plot, with optimum correlations of 0.74, 0.91, and 0.82, respectively. The lithology of hydrocarbon-saturated porous sand is at values of LI ≤ 2800 (m/s)(g*cc), ϕI ≤ 5500 (m/s)(g*cc) and FI ≤ 4000 (m/s)(g*cc). The presence of low values for LI, ϕI and FI correlates accurately with the presence of hydrocarbons in the well. Each value of c is then applied to the seismic data. The results show that this method can determine the distribution of gas-saturated porous sand on the seismic inversion section in the northeast–southwest direction.

Numerical modeling of frequency-dependent velocity and attenuation in a fractured-porous rock saturated with two immiscible fluids

The dispersion and attenuation of seismic-wave propagation induced by ‘squirt flow’ effects in hydrocarbon-saturated reservoirs are significantly affected by their rock properties and fluid content. In this study, we analyse the frequency-dependent velocity, attenuation, and seismic responses when fractured porous rock is saturated with two immiscible fluids. First, when considering reservoir wettability, we calculate the effective fluid viscosity using a stable parameter, the capillary pressure, and a lattice Boltzmann model (LBM)-based relative permeability equation, which is a function of the saturation and viscosity ratio of the immiscible two-phase fluid. Then, we explore the frequency-dependent effects of fractured porous rocks saturated with two immiscible fluids under different cases of viscosity ratios and capillary pressure parameters by employing the Chapman model from the dynamic equivalent-medium theory. Then, we use a four-layer model to analyse the frequency-dependent seismic responses. The results show that the characteristics of frequency-dependent velocity and attenuation are both affected by the wettability, capillary pressure parameter, saturation, and viscosity ratio. The frequency-dependent features are greatly influenced by the capillary pressure parameter and viscosity ratio. For a larger viscosity ratio and lower capillary parameter, a dispersive effect can occur in the seismic frequency band. This indicates that the velocity dispersion anomalies are sensitive to wettability, capillary pressure parameter and viscosity ratio and should not be neglected. Synthetic seismic records demonstrate that the seismic reflection signatures, such as the waveform, amplitude, and reflective travel time, at the interfaces for saturated reservoirs are significantly affected by wettability and saturation. The numerical modeling helps to improve the wave propagation in rocks saturated by two immiscible fluids.

A New Fluid Mobility Calculation Method Based on Frequency-Dependent AVO Inversion

Fluid mobility (i.e., permeability to viscosity ratio) is a key parameter that can evaluate the reservoir permeability and delineate the fluid characteristic in hydrocarbon-saturated reservoirs. Based on the asymptotic representation for the frequency-dependent reflections in the fluid-saturated pore-elastic media and frequency-dependent AVO inversion, we propose a novel method for estimating fluid mobility from poststack seismic data. First, we establish the relationship between fluid mobility and frequency-dependent AVO analysis. Then, the fluid mobility is estimated using the theory of frequency-dependent AVO inversion. Tests on synthetic data reveal that the fluid mobility shows excellent imageability for the fluid-saturated reservoirs and can accurately delineate the spatial distribution shape of the gas-saturated reservoir. The application of field data examples demonstrates that the fluid mobility calculated by the proposed method produces less background interferences caused by elastic layers compared with the conventional frequency-dependent fluid indicator. The frequency-dependent fluid mobility takes into account the dispersion features associated with hydrocarbon reservoirs, and it provides a new way to detect the location of hydrocarbon reservoirs and characterize their spatial distribution.

Poisson ratio-based AVO indicator to detect hydrocarbon-saturated reservoirs: example from North Western Australian Offshore

Poisson ratio-based AVO indicator to detect hydrocarbon-saturated reservoirs: example from North Western Australian Offshore

A Novel Methodology for Hydrocarbon Depth Prediction in Seabed Logging: Gaussian Process-Based Inverse Modeling of Electromagnetic Data

Seabed logging (SBL) is an application of electromagnetic (EM) waves for detecting potential marine hydrocarbon-saturated reservoirs reliant on a source–receiver system. One of the concerns in modeling and inversion of the EM data is associated with the need for realistic representation of complex geo-electrical models. Concurrently, the corresponding algorithms of forward modeling should be robustly efficient with low computational effort for repeated use of the inversion. This work proposes a new inversion methodology which consists of two frameworks, namely Gaussian process (GP), which allows a greater flexibility in modeling a variety of EM responses, and gradient descent (GD) for finding the best minimizer (i.e., hydrocarbon depth). Computer simulation technology (CST), which uses finite element (FE), was exploited to generate prior EM responses for the GP to evaluate EM profiles at “untried” depths. Then, GD was used to minimize the mean squared error (MSE) where GP acts as its forward model. Acquiring EM responses using mesh-based algorithms is a time-consuming task. Thus, this work compared the time taken by the CST and GP in evaluating the EM profiles. For the accuracy and performance, the GP model was compared with EM responses modeled by the FE, and percentage error between the estimate and “untried” computer input was calculated. The results indicate that GP-based inverse modeling can efficiently predict the hydrocarbon depth in the SBL.

New AVO expression and attribute based on scaled Poisson reflectivity

A new expression for Amplitude Variation with Offset (AVO) is proposed. The expression introduces reflection amplitudes as a function of two very common AVO parameters, the Gradient (G) and scaled Poisson reflectivity (SPR). The SPR is proven to be an excellent indicator of hydrocarbon with more sensitivity to fluid than other ordinary AVO attributes. Another advantage of the SPR is that it works for all types of gas-saturated sands commonly targeted by AVO. From the new expression, a new AVO classification based on SPR is introduced. The classification involves two classes: 1) Class H, with negative SPR and negative G, represents rocks with high probability of hydrocarbon presence, and 2) Class N, with nearly zero or positive G and SPR, includes rocks with high probability of no-hydrocarbon presence. An AVO attribute combining SPR and Gradient is derived from the expression and is proposed as a good indicator of fluid presence. The approximation and the attribute are applied on Marmousi-2 model datasets and on a field data from Alberta, Canada. The attribute has demonstrated a good identification of the hydrocarbon-saturated reservoirs in theoretical model and the real field data. The new AVO approximation, classification and attribute are intended to complement other existing approximations and reduce uncertainty from their interpretations.

DELINEATION OF HYDROCARBON SATURATED RESERVOIR SAND USING INTEGRATED 3D PRE-STACK SEISMIC AND WELL LOG DATA IN BONGA – FIELD, CENTRAL SWAMP DEPOBELT, ONSHORE NIGER DELTA, NIGERIA

This study has successfully delineated the lateral continuity of hydrocarbon saturated sand reservoir in Bonga field, Niger Delta. 3D pre-stack seismic volume and well logs from two (2) exploratory wells were employed in the pre-stack seismic inversion analysis. The delineated BGA reservoir sand spans across the two (2) wells labelled Bonga-26 and Bonga-30. The reservoir depth ranges from 10490 ft to 10620 ft in Bonga-26 while the reservoir depth ranges from 10390 ft to 10490 ft in Bonga-30. The delineated reservoir is characterized by low gamma ray (< 75 API), water saturation, shale volume and high resistivity as deciphered in their respective well log curves signature. Rock attribute crossplot was carried out to discriminate between the formation fluid and lithology. The crossplot space of VP-VS ratio versus acoustic impedance (AI), discriminates the formation properties into lithology and fluid (gas and brine sand) based on clusters inferring the presence of each formation fluid properties. The inversion cross sections of P-impedance, S-impedance, density (ρ) and VP-VS ratio depicts the spread and lateral continuity of the reservoir sand across the well locations. The delineated zones reveal low P-impedance, density, VP-VS ratio and slight increase in S-impedance which further validate the presence of hydrocarbon in the field.

Modelling and mapping hydrocarbon saturated sand reservoir using Poisson’s impedance (PI) inversion: a case study of Bonna field, Niger Delta swamp depobelt, Nigeria

3D seismic volume and two well logs data labelled Bonna-6 and Bonna-8 were employed in the inversion process. The data set was simultaneously inverted to produce P- and S-impedances, density, VP − VS, and PI seismic attributes. An average “c” term value of 1.37 was obtained from the inverse of the slope of the crossplot of P-impedance versus S-impedance for Bonna-6 and Bonna-8 wells. This value was employed in the inversion process to generate the PI attribute, which aided in reducing the non-uniqueness inherent in discriminating the probable reservoir sands. Five seismic attributes slices were generated to ascertain the superiority of each attribute in delineating the probable reservoir sand. These attributes were: density, S-impedance, P-impedance, VP− VS ratio and PI. These attributes reveal low value of density (1.96 − 2.14 g/cc), P-impedance (1.8 × 104 − 2.1 × 104) ft/s*g/cc, S-impedance (9.2 × 103 − 1.1 × 104) ft/s*g/cc, VP − VS (1.65 − 1.72) and PI (4.9 × 103 − 5.1 × 104) ft/s*g/cc around the area inferred to be hydrocarbon saturated reservoir. Although the attributes considered reveals the same zone suspected to be probable hydrocarbon zone, PI gives a better discrimination when compared to other attributes. A distinctive spread and demarcation of the delineated hydrocarbon sand are observed in the PI attribute slice.

Seismic amplitudes and spectral attribute analysis in reservoir characterisation, \u2018MUN\u2019 onshore Niger delta field

Integrating seismic amplitudes and spectral attribute analysis has successfully mapped, validated and characterised hydrocarbon-saturated channel sands by high-amplitude low-frequency anomaly. The aim of the study was targeted at using these novel geophysical tools to improve characterisation of tertiary clastic reservoir in the field. These attributes were extracted along H4 seismic horizon and analysed independently for structure, lithology and hydrocarbon saturation. The result of the analysis shows that both attributes complimented each other in mapping the hydrocarbon-saturated reservoir channel sands. However, the spectral attributes in combination with spectral-based Red, Blue and Green (RGB) colour blending attribute map reveal finer and subtle details of the channel structure and stratigraphy which hitherto were not apparent in the seismic amplitude maps. The channel sands trend NE–SW, broadening towards the southwest and bounded by major growth faults to the northeast and southwest, respectively. It is thick to the southwest and thins to the northeast. By-passed hydrocarbon prospect was delineated to the northeast of the existing wells, and as such, infill wells can be drilled in these areas to recover hydrocarbons.

Model Calibration of Stochastic Process and Computer Experiment for MVO Analysis of Multi-Low-Frequency Electromagnetic Data

An electromagnetic (EM) technique is employed in seabed logging (SBL) to detect offshore hydrocarbon-saturated reservoirs. In risk analysis for hydrocarbon exploration, computer simulation for subsurface modelling is a crucial task. It can be expensive and time-consuming due to its complicated mathematical equations, and only a few realizations of input-output pairs can be generated after a very lengthy computational time. Understanding the unknown functions without any uncertainty measurement could be very challenging as well. We proposed model calibration between a stochastic process and computer experiment for magnitude versus offset (MVO) analysis. Two-dimensional (2D) Gaussian process (GP) models were developed for low-frequencies of 0.0625–0.5 Hz at different hydrocarbon depths to estimate EM responses at untried observations with less time consumption. The calculated error measurements revealed that the estimates were well-matched with the computer simulation technology (CST) outputs. Then, GP was fitted in the MVO plots to provide uncertainty quantification. Based on the confidence intervals, hydrocarbons were difficult to determine especially when their depth was 3000 m from the seabed. The normalized magnitudes for other frequencies also agreed with the resulting predictive variance. Thus, the model resolution for EM data decreases as the hydrocarbon depth increases even though multi-low frequencies were exercised in the SBL application.

Vertical dipole CSEM: 3D acquisition and data impact from infrastructure

Abstract Marine CSEM methods for subsurface investigations were developed nearly 30 years ago (Cox, 1981), and have found extensive applications within the offshore hydrocarbon exploration industry over the past 15 years (e.g. Constable, 2010). These methods detect contrasts in electrical conductivity, exploiting the fact that the electrical conductivity of hydrocarbon-saturated reservoirs is significantly smaller than in the surrounding sediments (Ell-ingsrud et al., 2002). While marine CSEM has proven itself as a valuable tool in exploration and mapping of frontier areas, there is growing increased interest in applying CSEM for near-exploration and reservoir monitoring applications. A vertical-based time domain EM exploration method (Barsukov et al., 2007) has been developed by the Norwegian geophysical company PetroMarker, founded in 2005. In the past the method has primarily been used for exploration, but since the vertical method relies on a stationary acquisition mode with very high accuracy in transmitter positioning it allows both repeatability and freedom of operation close to existing infrastructure and installations, and in vulnerable environments. Over the past few years there have also been improvements in receiver technology, allowing efficient 3D acquisition. We will present improvements to the method and a 3D field data example. We will also present investigations of the impact of the method on field data from infrastructure.

A simple geologic risk-tailored 3D controlled-source electromagnetic multiattribute analysis and quantitative interpretation approach

Three-dimensional surveying is the method of choice in marine controlled-source electromagnetic (CSEM) exploration for hydrocarbons in frontier regions, but robust interpretation of the typically large-size field data faces significant challenges, including how to determine the correct resistivity, depth, and lateral limits of hydrocarbon-saturated reservoirs in the presence of heterogeneous host rocks or anisotropy and how to relate CSEM information to the key elements of geologic prospect evaluation (the presence of source rocks, migration and charge, reservoir rock, trap, and seal). We have developed a simple geologic risk-tailored approach for multiattribute analysis and first-pass interpretation of CSEM data in frontier exploration in which little prior information is available. First, geometric normalization of electric field amplitudes at each receiver location yields “phase-consistent” sounding curves that directly represent subsurface electrical structure (and can indicate reservoir rock presence). It enables accurate determination of seafloor resistivity (whose areal variation and direct correlation with seepage-induced geochemical and seismic shallow-gas anomalies can indicate the presence of a working petroleum system). Edge-detection attributes are then used to determine the geographical position and boundary shape of anomalous 3D resistive bodies (the trap presence and structural closure). Keeping these known parameters fixed, the most likely burial depth and resistivities of the sought 3D bodies are found using a simple line search technique involving rigorous 3D modeling and the results are validated and optimized post facto using seismic depth constraints to locally improve the prediction of the size and resistivities of hydrocarbon-charged or water-bearing sections crucial for prospect derisking, reserve estimation, and well placement.

Petrophysical Properties’ Evaluation for Reservoir Characterization of AK Field, Onshore Eastern Niger Delta, Southern Nigeria

In this study, well log derived petrophysical parameters of four (4) delineated clastic reservoirs in AK field, located onshore eastern Niger Delta have been effectively employed to characterize and assess hydrocarbon prospect potential of the field. Wireline well log data, such as gamma ray, resistivity log suite, Compensated Neutron Log (CNL) and Formation Density Compensated (FDC) were studied and analyzed for qualitative and quantitative evaluation of the formation units in the field. Lithologic discrimination aided the identification of sandy units, while fluid identification and discrimination defined the hydrocarbon saturated reservoir units in the field. Other derived parameters such as porosity, permeability, water saturation, hydrocarbon saturation, Net To Gross (NTG), net hydrocarbon pay, Bulk Volume Water (BVW) among others were employed to quantitatively characterize the delineated reservoir units, especially to establish their hydrocarbon potential. Four (4) sandy reservoir units, A1, A2, A3 and A4 which ranged in thickness from about 60-350 ft were identified from four exploratory wells AK-01, AK-02, AK-03 and AK 04 to be hydrocarbon bearing. The clastic reservoirs presented medium to relatively high formation porosity (0.27-0.38), low to average permeability value (61.6-685.5 mD) and significant to high hydrocarbon saturation (0.42-0.97). A plot of true formation resistivity values (Rt) against water saturation (Sw) indicate that all reservoir units encountered in well AK-01 are oil saturated. However, only reservoir sands A1 and A2 are predominantly oil reservoirs in well AK02 while sands A3 and A4 plot in oil and water field. In well AK-03, reservoir A1 contains only oil while the remaining reservoirs contain oil and water. The reservoir units as encountered in well AK-04 show slightly different fluid saturation pattern as reservoir A1 contains only oil, A4 is gas saturated while the remaining two reservoir units (A3 and A4) plot in the field of both water and oil.

Pyritization effect on well logging parameters in Jurassic reservoirs within S-E Western Siberian oil fields

Authigenic sulfide mineralization in hydrocarbon-saturated reservoirs distorts the electrical and density properties of rocks. The correlation between volumetric density, electro-conductive minerals and open porosity in 300 samples were determined. This fact made it possible to develop a nomograph in evaluating oil saturated reservoirs and could be applied in well geophysical survey data interpretation.

Determination of subsurface rock properties from AVO analysis in Konga oil field of the Niger Delta, Southeastern Nigeria

Amplitude variation with offset (AVO) analysis was carried out on Konga oil field, an onshore oil field in the Niger Delta, Southeastern Nigeria. The study consisted of forward modeling from rock parameters measured from well logs and AVO analysis of events on pre-stack time migrated 3D seismic gathers. Forward modeling predicted specific AVO behaviour of anomalous reservoir sands in the field. Density, compressional and shear wave velocity logs, combined with a wavelet extracted from recorded seismic gathers were used to generate synthetic seismic gathers and Gassmann fluid substitution models. These synthetics supported key observations made of the AVO response in the field data. AVO attributes (intercept and gradient) were derived from analysis of common depth point (CDP) gathers obtained from a 3D pre-stack seismic survey. The attributes were cross-plotted to establish trends against which anomalous amplitude behaviour were identified. Reflections related to shales and brine sands exhibit a relatively small range of orientations creating a dominant “background trend” against which anomalous events related to hydrocarbon-saturated reservoirs show clear deviations. On the basis of crossplot analyses (reflectivity versus offset/angle and intercept versus gradient) and modeled acoustic impedance, Class 1 type AVO anomalies observed are associated with non-hydrocarbon bearing clastic rocks that are most probably brine saturated in the field. Evidence from these results show that drilling in this field in search of hydrocarbon reservoirs poses a risky venture.

Phase-Shifted Based Numerical Method for Modeling Frequency-Dependent Effects on Seismic Reflections

The significant velocity dispersion and attenuation has often been observed when seismic waves propagate in fluid-saturated porous rocks. Both the magnitude and variation features of the velocity dispersion and attenuation are frequency-dependent and related closely to the physical properties of the fluid-saturated porous rocks. To explore the effects of frequency-dependent dispersion and attenuation on the seismic responses, in this work, we present a numerical method for seismic data modeling based on the diffusive and viscous wave equation (DVWE), which introduces the poroelastic theory and takes into account diffusive and viscous attenuation in diffusive-viscous-theory. We derive a phase-shift wave extrapolation algorithm in frequencywavenumber domain for implementing the DVWE-based simulation method that can handle the simultaneous lateral variations in velocity, diffusive coefficient and viscosity. Then, we design a distributary channels model in which a hydrocarbon-saturated sand reservoir is embedded in one of the channels. Next, we calculated the synthetic seismic data to analytically and comparatively illustrate the seismic frequency-dependent behaviors related to the hydrocarbon-saturated reservoir, by employing DVWE-based and conventional acoustic wave equation (AWE) based method, respectively. The results of the synthetic seismic data delineate the intrinsic energy loss, phase delay, lower instantaneous dominant frequency and narrower bandwidth due to the frequency-dependent dispersion and attenuation when seismic wave travels through the hydrocarbon-saturated reservoir. The numerical modeling method is expected to contribute to improve the understanding of the features and mechanism of the seismic frequency-dependent effects resulted from the hydrocarbon-saturated porous rocks.

Unbiased AVO crossplotting?

AVO crossplotting of intercept and gradient attributes has been a mainstay of AVO interpretation and analysis for more than two decades. In binary sand-shale settings, the viability of a lead or prospect can be further evaluated by identifying a background trend of wet sands and shales, and observing how removed the prospect's intercept-gradient pairs are from the background trend using small temporal or stratigraphic-consistent windows. This technique has primarily been performed visually, and, as such, contains inherent interpretation bias. While overall the visual methodology of the technique has been successful, methods to reduce such errors are valued as prospect economics become more challenging. To mitigate this interpretation bias, an unsupervised neural network methodology is presented. The unsupervised vector quantizer (neural network) assists in subgrouping (classifying) those seismic pairs that comprise the AVO background trend and those pairs that may subgroup as outliers — possibly indicative of hydrocarbon-saturated reservoirs. With this methodology, a clearer determination of what is AVO background trend and what is AVO outlier is presented using 2D seismic data in a frontier exploration province. Use of unsupervised neural networks for AVO crossplot assessment is accompanied with additional benefits that further assist in understanding geologies or seismic facies within the AVO crossplot subset.

Differentiation of Pore Fluids Using Amplitude versus Offset Attributes in Clastic Reservoirs, Middle Indus Basin, Pakistan

Lower Goru sand intervals of the Cretaceous age in Kadanwari field of the middle Indus Basin, Pakistan, are interpreted as reservoir intervals. Based on seismic interpretation and geology, several wells were drilled in these sands. However, most of the wells drilled were dry and declared abundant because highly saturated brine was encountered with minute amount of hydrocarbon gas. The main reason for drilling dry wells was limitation of seismic reflection data to differentiate seismic response of hydrocarbon-saturated reservoir interval from non-hydrocarbon-saturated interval. Amplitude versus offset (AVO) analysis is widely used to differentiate hydrocarbon intervals from background lithology. In this work, AVO-derived attributes are used for fluid discrimination in the sand intervals. Amplitude differences are associated with density and compressibility of fluid under in situ temperature and pressure conditions of the reservoir interval. The results reveal that seismic amplitude anomalies associated with AVO analysis can differentiate hydrocarbon fluids from non-hydrocarbon fluids and thus can optimize the exploration of gas. The gas sand anomaly in the study area is of weak impedance as compared to brine sand. The intercept and fluid factor are very promising attribute pairs to discriminate gas sands from background sands. The results may be helpful to discriminate low gas saturation or fizz water from high gas saturation.

Dispersion-dependent attribute and application in hydrocarbon detection

Previous work has demonstrated that seismic velocity dispersion is often related to a hydrocarbon-saturated reservoir with a high value of attenuation. The velocity dispersion properties can be used as new hydrocarbon indicators if they can be estimated quantitatively from seismic data. In this context, based on the assumption that the reflection coefficient of the interface between dispersive media varies with frequency, we propose an approximation of the reflection coefficient which involves the dispersion-dependent attributes indicating the level and gradient of P-wave velocity dispersion. We develop a new generalization of an AVO inversion scheme to extract the dispersion-dependent attributes from multi-frequency prestack seismic data obtained by the Morlet wavelet decomposition method. The method test and real application show that the dispersion-dependent attributes have the potential to be useful in the discrimination of hydrocarbon accumulation. However, the hydrocarbon detection quality of the dispersion-dependent attributes can be degraded by the inverse Q-filtering procedure which compensates the high-frequency amplitudes.