Leveraging Acoustic Logging for Identification & Quantification of Induced Fractures

The main objective of the acoustic logging in 15K openhole multistage fracturing completions (OH MSFs) is to identify the fracture initiation points behind pipe and contributing fractures to gas production. The technique will also help to understand the integrity of the OH packers. A well was identified to be a candidate for assessment through such technique. The selected well was one of the early 15K OH MSF completions in the region that was successfully implemented with the goal of hydrocarbon production at sustained commercial rates from a gas formation. The candidate well was drilled horizontally to achieve maximum contact in a tight gas sandstone formation. Similar wells in the region have seen many challenges of formation breakdown due to high formation stresses. The objective of this work is to use the acoustic data to better characterize fracture properties. The deployment of acoustic log technology can provide information of fractures initiation, contribution for the production and the reliability of the isolation packers between the stages. The candidate well was completed with five stages open-hole fracturing completion. As the well is in an open hole environment, a typical PLT survey provides the contribution of individual port in the cumulative production but provides limited or no information of contributing fractures behind the pipe. The technique of acoustic logging helped to determine the fracture initiation points in different stages. If fractures can be characterized more accurately, then flow paths and flow behaviors in the reservoir can be better delineated. The use of acoustic logging has helped to better understand the factors influencing fracture initiation in tight gas sandstone reservoirs; resulting in a better understanding of fractures density and decisions on future openhole length, number of fracturing stages, packers and frac ports placement.

Application of Various Machine Learning Techniques in Predicting Water Saturation in Tight Gas Sandstone Formation

Water saturation (Sw) is a vital factor for the hydrocarbon in-place calculations. Sw is usually calculated using different equations; however, its values have been inconsistent with the experimental results due to often incorrectness of their underlying assumptions. Moreover, the main hindrance remains in these approaches due to their strong reliance on experimental analysis which are expensive and time-consuming. This study introduces the application of different machine learning (ML) methods to predict Sw from the conventional well logs. Function networks (FN), support vector machine (SVM), and random forests (RF) were implemented to calculate the Sw using gamma-ray (GR) log, Neutron porosity (NPHI) log, and resistivity (Rt) log. A dataset of 782 points from two wells (Well-1 and Well-2) in tight gas sandstone formation was used to build and then validate the different ML models. The data set from Well-1 was applied for the ML models training and testing, then the unseen data from well-2 was used to validate the developed models. The results from FN, SVM and RF models showed their capability of accurately predicting the Sw from the conventional well logging data. The correlation coefficient (R) values between actual and estimated Sw from the FN model were found to be 0.85 and 0.83 compared to 0.98, and 0.95 from the RF model in the case of training and testing sets, respectively. SVM model shows an R-value of 0.95 and 0.85 in the different datasets. The average absolute percentage error (AAPE) was less than 8% in the three ML models. The ML models outperform the empirical correlations that have AAPE greater than 19%. This study provides ML applications to accurately forecast the water saturation using the readily available conventional well logs without additional core analysis or well site interventions.

Seismic estimation of fluid saturation based on rock physics: A case study of the tight-gas sandstone reservoirs in Ordos Basin

Tight-gas sandstone reservoirs of the Ordos Basin of China are characterized by high rock-fragment content, dissimilar pore types and a random distribution of fluids, leading to strong local heterogeneity. We model the seismic properties of these sandstones with the double-double porosity (DDP) theory, which considers water saturation, porosity and the frame characteristics. A generalized seismic wavelet is used to fit the real wavelet and the peak frequency-shift method is combined with the generalized S-transform to estimate attenuation. Then, we establish rock-physics templates (RPTs) based on P-wave attenuation and impedance. We use the log data and related seismic traces to calibrate the RPTs and generate a 3D volume of rock-physics attributes for the quantitative prediction of saturation and porosity. The predicted values are in good agreement with the actual gas production reports, indicating that the method can be effectively applied to heterogeneous tight-gas sandstone reservoirs.

Estimation of the Pore Microstructure of Tight-Gas Sandstone Reservoirs with Seismic Data

Tight-sandstone reservoirs have a complex pore structure with microcracks and intergranular pores, which have a significant impact on the seismic properties. We have performed ultrasonic measurements at different confining pressures for 15 tight-gas sandstone samples of the Xujiahe formation in Western Sichuan Basin, and have available well-log and seismic data of this area. The aim of this work is to estimate the porosity and crack properties for variable pressure conditions. The EIAS (equivalent inclusion-average stress) model is adopted to compute the high- and low-frequency bulk and shear moduli as a function of crack aspect ratio and (soft) and (stiff) porosities. Then, we use the EIAS-Zener anelastic model to obtain the wave properties as a function of frequency, and compare results with those of the constant Q (Kjartansson) one for verification of the robustness of the approach. The corresponding P-wave impedance, density and phase velocity ratio (VP/VS) are computed in order to built 3D rock‐physics templates (RPTs) at the ultrasonic, well-log and seismic frequency bands. The methodology is applied to a survey line crossing two wells, which together with the laboratory experiments, provide calibration suitable data. The estimated stiff porosity and crack porosity and density are consistent with the available data and actual production records, indicating that 3D RPTs provide a useful interpretation tool in seismic exploration and prospect evaluation.

Rock Physical Modeling and Seismic Dispersion Attribute Inversion for the Characterization of a Tight Gas Sandstone Reservoir

Gas identification using seismic data is challenging for tight gas reservoirs with low porosity and permeability due to the complicated poroelastic behaviors of tight sandstone. In this study, the Chapman theory was used to simulate the dispersion and attenuation caused by the squirt flow of fluids in the complex pore spaces, which are assumed to consist of high aspect-ratio pores (stiff pores) and low aspect-ratio microcracks (soft pores). The rock physics modeling revealed that as the gas saturation varies, P-wave velocity dispersion and attenuation occurs at seismic frequencies, and it tends to move to high frequencies as the gas saturation increases. The velocity dispersion of the tight gas sandstone causes a frequency-dependent contrast in the P-wave impedance between the tight sandstone and the overlying mudstone, which consequently leads to frequency-dependent incidence reflection coefficients across the interface. In the synthetic seismic AVO modeling conducted by integrating the rock physics model and the propagator matrix method, the variations in the amplitudes and phases of the PP reflections can be observed for various gas saturations. The tests of the frequency-dependent AVO inversion of these synthetic data revealed that the magnitude of the inverted P-wave dispersion attribute can be used to indicate gas saturation in tight sandstone reservoirs. The applications of the frequency-dependent AVO inversion to the field pre-stacked seismic data revealed that the obtained P-wave dispersion attribute is positively correlated with the gas production from the pay zone at the well locations. Thus, the methods of the rock physics modeling and the frequency-dependent AVO inversion conducted in this study have good potential for the evaluation of the gas saturation in tight gas sandstone reservoirs.

Numerical Investigation of the Effect of Heterogeneous Pore Structures on Elastic Properties of Tight Gas Sandstones

Strong heterogeneity of pore microstructures leads to complicated velocity-porosity relationships in tight sandstone that cannot be well explained by conventional empirical formulas. To better understand the effect of complex pore structures on elastic properties of tight gas sandstone, we compared three rock physics models. In the first model, we used a single aspect ratio value to quantify varied pore geometry in the tight sands. In the second model, complex pore space was equivalent to the combination of high-aspect-ratio round pores (stiff pores) and low-aspect-ratio compliant microcracks (soft pores). In the third multiple pore-aspect-ratio model, pore spaces are represented using a set of pores with varied values of aspect ratio following statistical normal distribution. Modeling results showed that complex velocity-porosity relationships could be interpreted by the variations in pore aspect ratio in the first model, by the fraction of soft pores in the second model, and by the mean value and variance in the third statistical model. For a given mean value in the third model, higher variance of the multiple pore-aspect-ratio indicated stronger heterogeneity of pore spaces. Further studies on rock physical inversion showed that, compared with the first single pore-aspect-ratio model, the second dual-pore model gave better prediction in shear wave velocity by regarding the soft pore fraction as a fitting parameter. This finding revealed that the dual-pore model could be a more realistic representation of tight sandstone. The third statistical model showed comparable precision in the prediction of shear wave velocity compared with the dual-pore model; however, uncertainty existed for simultaneously determining mean value and variance of pore aspect ratio. On the basis of the dual-pore model, we evaluated the elastic modulus of dry frames of the tight sandstone using logging data in a borehole. Compared with empirical formulas, such as the Krief methods, the method in this paper provided a more rigorous way to determine elastic properties of dry frames for the tight sandstone. Comparisons of rock physical modeling methods offer a better understanding of the microstructures controlling the elastic behaviors of tight gas sandstone.