Logging-while-drilling Resistivity Research Articles

Petrophysical interpretation of logging-while-drilling borehole measurements in the presence of electrical anisotropy, mud-filtrate invasion, noise, and well deviation effects

Petrophysical interpretation of logging-while-drilling (LWD) borehole measurements in the presence of electrical anisotropy, mud-filtrate invasion, noise, and well deviation effects remains a challenge in formation evaluation. In high-angle and horizontal (HAHZ) wells penetrating electrically anisotropic sandstones, phase and attenuation apparent resistivity logs often exhibit values larger than resistivity parallel to bedding planes. Consequently, traditional interpretation methods often fail to accurately estimate hydrocarbon saturation when using only the long-spacing phase apparent resistivity log (P40H) in petrophysical calculations. We implement two approaches (analytical and Bayesian) to estimate horizontal and vertical resistivities from apparent resistivity measurements. The first analytical approach is based on the numerical simulation of LWD resistivity measurements using synthetic models under various conditions of electrical anisotropy and well inclination to derive analytical models. The relative error of analytical approximations is less than 6%. In the presence of measurement noise and shoulder-bed effects, we implement a Bayesian method for well-log inversion and uncertainty quantification. The relative error of Bayesian inversion is less than 2%. Estimates of horizontal and vertical resistivities then can be used for petrophysical analysis. A challenging set of synthetic and field examples of HAHZ wells penetrating electrically anisotropic formations is selected for examination and verification of the new methods. For radial lengths of invasion less than 20 cm (8 in), sensitivity analysis indicates that the effects of conductive mud-filtrate invasion on long-spacing resistivity logs are negligible. The long-spacing phase (P40H) and attenuation (A40H) apparent resistivities are used to estimate horizontal and vertical resistivities. In the field examples under study, electrical anisotropy is caused by intercalated laminations of coarse- and fine-grained sandstones; the volumetric concentration of shale is negligible. Considering that Archie’s parameters are direction dependent, sensitivity analysis indicates that the effective value of the saturation exponent parallel to bedding planes is less sensitive to the volumetric concentration of fine-grained sandstone layers compared with the saturation exponent perpendicular to bedding planes. Thus, water saturation of grain-laminated sandstones in HAHZ wells can be estimated using horizontal resistivity with Archie’s parameters that are consistent with petrophysical interpretations performed in vertical wells. Estimates of water saturation in the field examples using horizontal resistivity agree with saturation-height models. Compared with conventional interpretation methods that use P40H as the formation resistivity, the new approach improved the estimation of hydrocarbon saturation by 10%.

Physics-guided deep-learning inversion method for the interpretation of noisy logging-while-drilling resistivity measurements

SUMMARY Deep learning (DL) inversion is a promising method for real-time interpretation of logging-while-drilling (LWD) resistivity measurements for well-navigation applications. In this context, measurement noise may significantly affect inversion results. Existing publications examining the effects of measurement noise on DL inversion results are scarce. We develop a method to generate training data sets and construct DL architectures that enhance the robustness of DL inversion methods in the presence of noisy LWD resistivity measurements. We use two synthetic resistivity models to test the three approaches that explicitly consider the presence of noise: (1) adding noise to the measurements in the training set, (2) augmenting the training set by replicating it and adding varying noise realizations and (3) adding a noise layer in the DL architecture. Numerical results confirm that each of the three approaches enhances the noise-robustness of the trained DL inversion modules, yielding better inversion results—in both the predicted earth model and measurements—compared to the basic DL inversion and also to traditional gradient-based inversion results. A combination of the second and third approaches delivers the best results.

Expanding Measuring Range of LWD Resistivity Instrument in High Permittivity Layers

The effective measuring range of an electromagnetic wave resistivity instrument used in logging while drilling (LWD) is small, and the resistivity measurement is greatly influenced by the dielectric constant, especially in high-dielectric-constant formations. In this paper, the response characteristics of the instrument under a high dielectric constant are investigated by a numerical simulation algorithm, and the resistivity conversion method is determined. The results show that the higher the working frequency of the electromagnetic wave resistivity instrument while drilling, and the greater the formation of background resistivity, the greater the influence of the dielectric constant on the logging response. The existence of the dielectric constant will cause the phase shift and amplitude attenuation of the measured signal to migrate, and this migration is proportional to the formation resistivity and the dielectric constant. According to this rule, the resistivity–permittivity response library is established, and the formation permittivity is calculated by the inversion of the library. On the basis of obtaining the formation permittivity, the migration of the logging signal permittivity is corrected, the influence of the dielectric constant is eliminated, and the measuring precision and measuring range of the instrument in the high-dielectric-constant formation are enlarged.

Using logging while drilling resistivity imaging data to quantitatively evaluate fracture aperture based on numerical simulation

Abstract Fractured formations are strongly heterogenous, and thus exhibit a complex logging response mechanism. By using the logging while drilling (LWD) resistivity imaging tool, fractures can be visually identified and their aperture quantitatively calculated. Because physical fracture model simulation is time consuming and costly, we propose using a 3D finite element method (FEM) numerical simulation to interpret the LWD resistivity imaging tool logging responses in conjunction with a new aperture calculation model based on the forward model. First, we used the single fracture model to investigate the effect of fracture aperture and formation resistivity contrast on the maximum current contrast at the fracture. The results showed that the aperture is linearly related to the maximum current contrast, while the formation resistivity contrast exhibits a pronounced exponential relationship with the maximum current contrast. Both of these relationships are affected by the fracture's dip angle, so segmented fitting is required when the fracture dip angles differ. Next, using the forward model, we developed the fracture aperture calculation model based on the maximum current contrast. The aperture calculation model was established in three segments in accordance with the different fracture dips, and the influence factors affecting the fracture inverting inclination were analyzed using multi-fracture simulation images. Finally, the accuracy of the new model was verified with the simulated fracture images. The novel model for calculating fracture aperture is of great significance for processing and interpreting LWD resistivity imaging logging data.

Comparison of logging-while-drilling and wireline logging data from gas hydrate-bearing deep-sea sediments, the Ulleung Basin, East Sea

Gas hydrate exploration was conducted using logging-while-drilling (LWD) and wireline logging (WLL) at two sites (UBGH2-6 and UBGH2-10) in the Ulleung Basin, East Sea (Sea of Japan). Coring for gas hydrate sampling was also conducted. Seismic profiles revealed that the upper layers at the logged sites (∼180 m at UBGH2-6 and ∼150 m at UBGH2-10) are dominated by turbidite/hemipelagic sediments, whereas the lower-lying sediments are characterised by thick mass transport deposits. Except in the gas hydrate-bearing interval (140–160 metres below the seafloor) of UBGH2-6, the WLL velocity and resistivity data are a little higher (∼100 m/s and ∼0.4 ohm-m, respectively) than those indicated by LWD. Conversely, the density and porosity do not show a consistent pattern for the two methods. Discrepancies between LWD and WLL can be caused by the methodology, borehole condition, and gas hydrate occurrence type. The high resistivity values (∼100 ohm-m) in the gas hydrate-bearing zone of UBGH2-6 are typical of inclined fracture-filling gas hydrate. In this case, the LWD resistivity may be overestimated as a result of the data acquisition principle. The relationships between the physical properties are significantly controlled by the presence of gas hydrate. Therefore, in fracture-filling gas hydrate-bearing sediments, the WLL resistivity data are more reasonable than the LWD resistivity data. Both methods have advantages and disadvantages in terms of data quality, efficiency, and resolution. Therefore, it is necessary to compare and interpret data measured using both methods to identify the physical properties of gas hydrate-bearing sediments.

Fast anisotropic resistivities inversion of logging-while-drilling resistivity measurements in high-angle and horizontal wells

Information about anisotropic resistivity is essential in real-time correlation, updating of formation model and making more confident geosteering decisions in logging-while-drilling (LWD) application. However, abnormal responses such as curve separations and apparent resistivity “horns” often exist in the LWD resistivity measurements due to the influences of complex downhole environments. Thus, accurate formation resistivity is not readily available. In this paper, we present an efficient inversion scheme for the rapid estimation of anisotropic resistivity from LWD resistivity measurements acquired in high-angle and horizontal wells. Several strategies are adopted in the inversion: (1) a one-dimensional (1D) simulator with a simplified three-layered model guarantees the forward speed and keeps the number of inverted parameters as few as possible; (2) combined with geological and petrophysical bounds, the tool constraints derived from a detection capability analysis of LWD resistivity measurements are applied to scale down the inverted parameters’ searching scope, which avoids meaningless solutions and accelerates the inversion significantly; (3) multiple-initial guesses are used in the inversion to ensure a global solution. Inversion results over synthetic examples demonstrate that the proposed 1D inversion algorithm is well suited for complex formation structures. It is also robust and fast in extracting anisotropic resistivities from LWD resistivity measurements.

On the depth of detection of logging-while-drilling resistivity measurements for looking-around and looking-ahead applications

The depth of detection (DOD), which is an important concept in logging data interpretation, describes the detection capability of the borehole measurements. We have extended the definition of DOD for azimuthal information, namely, the geosignal delivered by azimuthal resistivity tools, to resistivity logs in logging-while-drilling (LWD) applications. Instead of using the radial geometric factor, the detection thresholds in predicting a geologic boundary are used to describe the DOD of a measurement. This definition unifies the criteria to evaluate the detectability of different borehole measurements, such as LWD resistivity measurements and geosignals. It also can be generalized to other kinds of well logging methods in LWD applications. Using the proposed definition, we analyze the detection capability of the LWD resistivity measurements in looking-around and looking-ahead applications; they provide more tangible descriptions. In vertical or near-vertical wells, the definition provides an indicator to evaluate the capability and reliability of looking ahead of deep/ultradeep LWD resistivity tools. The investigations on the influence of the DOD on the distance-to-boundary inversion, which can help in developing a robust and accurate inversion scheme, also are presented and discussed.

Real-Time Intelligent Recognition Method for Horizontal Well Marker Bed

The accurate identification of the horizontal well marker bed is to guarantee the soft landing of the well trajectory. With the intelligent development of the petroleum industry, it is feasible to apply computers to identify the marker bed automatically. In case-based reasoning technology, the data of well logging while drilling (LWD) as characteristic parameters are compared with those of adjacent well. By taking the depth sequence of LWD data as time series and using Dynamic Time Warping (DTW) similarity measure algorithm, the similarity index of each drilling depth is calculated corresponding to the marker bed in the adjacent well. The total similarity curve is obtained by giving different weights of different feature parameters. Selecting natural gamma, deep resistivity, and shallow resistivity LWD curves as characteristic parameters, two horizontal wells in JL block of Junggar basin are analysed by this method. The result of similarity curve indicates the location of the marker bed and the total similarity value reaches 78%. The research shows that the method based on case-based reasoning can identify the marker bed of the horizontal well accurately and effectively, assist the geologist to carry out formation correlation of multiple wells at the same time, reduce the cost of human labour force, and improve work efficiency.

The effect factors analysis of the cave formation based on the LWD resistivity imaging method

The cave formation has strong non-homogeneity and the well logging response mechanism of it is very complex, which is of great significance to be studied. Based on the 3D finite element method, the logging response of the Logging While Drilling (LWD) resistivity imaging tool is simulated. The effects of cave diameter, cave extension and resistivity contrast between cave formation and background formation on ratio of measurement signals are investigated using a single cave model. The results show that the existence of the borehole has a great influence on the measurement signal, so it needs to be corrected or the measurement electrode of the tool should be close to the borehole. When the diameter of the cave is larger than a certain value, the relationship between the cave extension and the measurement signal can be quantitatively described. However, the resistivity contrast between the cave formation and the background formation shows a power index relationship under different cave diameter. The simulation results can provide a theoretical basis for the identification and interpretation of LWD resistivity imaging tool.

Parallel tempered trans-dimensional Bayesian inference for the inversion of ultra-deep directional logging-while-drilling resistivity measurements

As one of the most important downhole technology, directional electromagnetic (EM) logging-while-drilling (LWD) has been developing over the decades. The new generation of resistivity logging service expands the depth of investigation (DoI) to over 100 ft from the wellbore. As a result, more geological features are within the scope of the logging tool, which increases the complexity of logging measurements dramatically. Reservoir imaging relies on the inversion of the logging measurements, whereas most conventional inversion approaches depend on the deterministic optimization which oftentimes suffers from local minima. Many efforts were focused on the improvement of data processing workflow by using prior knowledge of the formation structure to constrain the optimizer from stepping into local minima although the prior can be inaccurate. To reduce the negative impact of inaccurate prior assumptions, we propose to infer the model parameters via the trans-dimensional Markov chain Monte Carlo (tMCMC) method. Governed by the Bayesian theorem, the trans-dimensional inference addresses the complexity of the model by allowing the number of layers of the target model to be a free parameter. Driven by the measurements, the joint posterior distribution of model parameters is sampled accordingly, which provides a probability solution of a potential answer. Bayesian sampling is computationally expensive with a slow convergence rate. In this paper, we propose a meta-technique called parallel tempering (PT) combining with tMCMC to improve the sampling performance. PT is also known as replica Bayesian sampling where multiple Markov chains are constructed to explore the posterior distribution simultaneously with periodic information exchange between chains. Verified by our experiments, combining tMCMC and PT builds an efficient and reliable framework for interpreting ultra-deep LWD resistivity measurements. The inversion results from a series of benchmark models demonstrate that the proposed data-driven framework is robust and can be used to infer a reservoir-scale earth model.

Characteristics of gas hydrate reservoir from resistivity image in the Shenhu area, China

In 2016, logging-while-drilling (LWD) was conducted at 11 sites in the Shenhu area of the South China Sea to characterise the gas hydrate reservoir. The authors used LWD resistivity image from these sites to analyse the hydrate occurrence mode, near-well structure, sedimentary structure, fracture and in situ stress orientation of the gas hydrate reservoir. The analysis revealed the following. (a) Three categories of gas hydrate occurrence mode were identified: thick-bedded, dispersed and thin-bedded. (b) The dip angle of the regional stratigraphic structure is concentrated between 2 and 4°, and the dip direction is mainly south-west. (c) The typical sedimentary structure is deformed bedding and primarily developed in the gas hydrate intervals. It is inferred that the deformed bedding is affected by gas hydrate formation and the drilling process. (d) Based on the borehole breakout, the minimum horizontal principal stress direction was determined to be north-east–south-west, which provides valuable information for the design of the gas hydrate production. (e) Two categories of fracture were identified: conductive fracture and resistive fracture. Conductive fracture developed in the gas hydrate zone and contributed to higher gas hydrate saturation. High-resolution resistivity images provide extensive visual geological information and are particularly important in future exploration plans.

Observed stress state for the IODP Site C0002 and implication to the stress field of the Nankai Trough subduction zone

Conducting a stress state analysis is one of major challenges for evaluating earth crust and formation conditions. Stress magnitude is especially essential to comprehend stress heterogeneity, significant structural anisotropy, and/or pre-existing fracture systems. Stress state is influenced by rock strength, structural properties, and near-field principal stresses, which impact borehole integrity during drilling. Factors that we can measure through Logging While Drilling (LWD) and Measure while Drilling (MWD) to better understand borehole conditions, include mud weight, overburden weight and velocity. The LWD resistivity images in Holes C0002A and C0002F of the Nankai Trough Seismogenic Zone Experiment (NanTroSEIZE) indicate that most of the drillings in stable environments. However, the bottom hole assembly became stuck around 3 km depth in Hole C0002P and did not reach the mega-thrust fault. We evaluated the stress state for the Site C0002 by the geomechanical model. With the breakout width and rock strength estimation, we constrain the stress profiles in the drilled depth. Our analysis inferred that the instability of Hole C0002P had been caused by an overpressure drilling fluid state and low horizontal principal stress. Furthermore, we developed an optimally oriented plane (OOP) model to exam the stress state in the Site C0002 from Nankai accretionary prism to the Nankai Trough subduction zone. The normal faulting stress regime modeled from OOP is consistent with the geomechanical model in Site C0002. The horizontal principal stresses magnitude appears to less than the overburden weight above this subduction zone.

A study of azimuthal electromagnetic wave LWD based on self-adaptive hp finite element method

Azimuthal electromagnetic wave logging-while-drilling (LWD) technology can detect weak electromagnetic wave signal and realize real-time resistivity imaging. It has great values to reduce drilling cost and increase drilling rate. In this paper, self-adaptive hp finite element method (FEM) has been used to study the azimuthal resistivity LWD responses in different conditions. Numerical simulation results show that amplitude attenuation and phase shift of directional electromagnetic wave signals are closely related to induced magnetic field and azimuthal angle. The peak value and polarity of geological guidance signals can be used to distinguish reservoir interface and achieve real-time geosteering drilling. Numerical simulation results also show the accuracy of the self-adaptive hp FEM and provide physical interpretation of peak value and polarity of the geological guidance signals.

Study on Ultra-deep Azimuthal Electromagnetic Resistivity LWD Tool by Influence Quantification on Azimuthal Depth of Investigation and Real Signal

This paper proposes a new tool design of ultra-deep azimuthal electromagnetic (EM) resistivity logging while drilling (LWD) for deeper geosteering and formation evaluation, which can benefit hydrocarbon exploration and development. First, a forward numerical simulation of azimuthal EM resistivity LWD is created based on the fast Hankel transform (FHT) method, and its accuracy is confirmed under classic formation conditions. Then, a reasonable range of tool parameters is designed by analyzing the logging response. However, modern technological limitations pose challenges to selecting appropriate tool parameters for ultra-deep azimuthal detection under detectable signal conditions. Therefore, this paper uses grey relational analysis (GRA) to quantify the influence of tool parameters on voltage and azimuthal investigation depth. After analyzing thousands of simulation data under different environmental conditions, the random forest is used to fit data and identify an optimal combination of tool parameters due to its high efficiency and accuracy. Finally, the structure of the ultra-deep azimuthal EM resistivity LWD tool is designed with a theoretical azimuthal investigation depth of 27.42–29.89 m in classic different isotropic and anisotropic formations. This design serves as a reliable theoretical foundation for efficient geosteering and formation evaluation in high-angle and horizontal (HA/HZ) wells in the future.

Solving geosteering inverse problems by stochastic Hybrid Monte Carlo method

The inverse problems arise in almost all fields of science where the real-world parameters are extracted from a set of measured data. The geosteering inversion plays an essential role in the accurate prediction of oncoming strata as well as a reliable guidance to adjust the borehole position on the fly to reach one or more geological targets. This mathematical treatment is not easy to solve, which requires finding an optimum solution among a large solution space, especially when the problem is non-linear and non-convex. Nowadays, a new generation of logging-while-drilling (LWD) tools has emerged on the market. The so-called azimuthal resistivity LWD tools have azimuthal sensitivity and a large depth of investigation. Hence, the associated inverse problems become much more difficult since the earth model to be inverted will have more detailed structures. The conventional deterministic methods are incapable to solve such a complicated inverse problem, where they suffer from the local minimum trap. Alternatively, stochastic optimizations are in general better at finding global optimal solutions and handling uncertainty quantification. In this paper, we investigate the Hybrid Monte Carlo (HMC) based statistical inversion approach and suggest that HMC based inference is more efficient in dealing with the increased complexity and uncertainty faced by the geosteering problems.

Mapping the resistivity structure of Walker Ridge 313 in the Gulf of Mexico using the marine CSEM method

A marine controlled source electromagnetic (CSEM) campaign was carried out in the Gulf of Mexico to further develop marine electromagnetic techniques in order to aid the detection and mapping of gas hydrate deposits. Marine CSEM methods are used to obtain an electrical resistivity structure of the subsurface which can indicate the type of substance filling the pore space, such as gas hydrates which are more resistive. Results from the Walker Ridge 313 study (WR 313) are presented in this paper and compared with the Gulf of Mexico Gas Hydrate Joint Industry Project II (JIP2) logging while drilling (LWD) results and available seismic data. The hydrate, known to exist within sheeted sand deposits, is mapped as a resistive region in the two dimensional (2D) CSEM inversion models. This is consistent with the JIP2 LWD resistivity results. CSEM inversions that use seismic horizons provide more realistic results compared to the unconstrained inversions by providing sharp boundaries and architectural control on the location of the resistive and conductive regions in the CSEM model. The seismic horizons include: 1) the base of the gas hydrate stability zone (BGHSZ), 2) the top of salt, and 3) the top and bottom of a fine grained marine mud interval with near vertical hydrate filled fractures, to constrain the CSEM inversion model. The top of salt provides improved location for brines, water saturated salt, and resistive salt. Inversions of the CSEM data map the occurrence of a ‘halo’ of conductive brines above salt. The use of the BGHSZ as a constraint on the inversion helps distinguish between free gas and gas hydrate as well as gas hydrate and water saturated sediments.

Analysis and application of the response characteristics of DLL and LWD resistivity in horizontal well

There exist different response characteristics in the resistivity measurements of dual laterolog (DLL) and logging while drilling (LWD) electromagnetic wave propagation logging in highly deviated and horizontal wells due to the difference in their measuring principles. In this study, we first use the integral equation method simulated the response characteristics of LWD resistivity and use the three dimensional finite element method (3D-FEM) simulated the response characteristics of DLL resistivity in horizontal wells, and then analyzed the response differences between the DLL and LWD resistivity. The comparative analysis indicated that the response differences may be caused by different factors such as differences in the angle of instrument inclination, anisotropy, formation interface, and mud intrusion. In the interface, the curves of the LWD resistivity become sharp with increases in the deviation while those of the DLL resistivity gradually become smooth. Both curves are affected by the anisotropy although the effect on DLL resistivity is lower than the LWD resistivity. These differences aid in providing a reasonable explanation in the horizontal well. However, this can also simultaneously lead to false results. At the end of the study, we explain the effects of the differences in the interpretation of the horizontal well based on the results and actual data analysis.

Numerical simulation of resistivity LWD tool based on higher-order vector finite element

Numerical simulation of resistivity logging-while-drilling (LWD) tool response in complex borehole environments is of great importance for interpretation of measurement data and characterization of oil reservoirs. The simulation results can provide important theoretical guidance for designing novel electrical logging instruments and interpreting real-time logging data. In this paper, higher-order vector finite element method had been used to investigate the resistivity LWD tool response by changing coils spacing, transmitting frequency and structure of antenna system in the anisotropic formation. Numerical simulation results indicate that the change of T–R 1 spacing is an obvious influence on the investigation depth and detecting precision of the resistivity LWD tool, and the change of R 1–R 2 spacing can affect the resolution of the thin-layer distinguish. The change of transmitting frequency can improve the resolution of low-resistivity formation and high-resistivity formation of resistivity LWD tool. The change of the structure of the antenna system can provide accurate geosteering drilling information to directional resistivity LWD tool. Simulation results also indicated that the higher-order vector finite element method has good convergence speed and calculation accuracy and it is suitable to simulate the response of resistivity LWD tools.

Numerical Simulation of a Multi-Frequency Resistivity Logging-While-Drilling Tool Using a Highly Accurate and Adaptive Higher-Order Finite Element Method

A novel, highly efficient and accurate adaptive higher-order finite ele- ment method (hp-FEM) is used to simulate a multi-frequency resistivity logging- while-drilling (LWD) tool response in a borehole environment. Presented in this study are the vector expression of Maxwell's equations, three kinds of boundary conditions, stability weak formulation of Maxwell's equations, and automatic hp- adaptivity strategy. The new hp-FEM can select optimal refinement and calculation strategies based on the practical formation model and error estimation. Numeri- cal experiments show that the new hp-FEM has an exponential convergence rate in terms of relative error in a user-prescribed quantity of interest against the degrees of freedom, which provides more accurate results than those obtained using the adaptive h-FEM. The numerical results illustrate the high efficiency and accuracy of the method at a given LWD tool structure and parameters in different physical models, which further confirm the accuracy of the results using the Hermes library (http://hpfem.org/hermes) with a multi-frequency resistivity LWD tool response in a borehole environment.

Multidisciplinary approach in determining the best zone to land a Haynesville horizontal well

The Upper Jurassic Haynesville Shale Formation in the East Texas Basin, North America, is a black, organic-rich, calcareous mudstone that lies below the Bossier Shale and above the Cotton Valley Limestone. The reservoir quality was controlled by primary depositional process and secondary diagenesis. The best lithology type in terms of drilling, completion, and production is the organic-rich, silty calcareous mudstone with low clay content. The studied well traversed the entire Haynesville Formation with the objective to assess the production potential of this formation. We acquired open-hole, triple-combo logging while drilling (LWD) logs, two types of production logs, and regional microseismic data. Postdrill log modeling confirmed that the horizontal well stayed on the planned trajectory, based on the log correlation between the horizontal and offset wells. Log modeling demonstrated that the LWD resistivity logs in horizontal wells are subject to resistivity anisotropy and polarization horn effects. We integrated the production log results with the open-hole, log formation evaluation and mineralogy-based brittleness index, to understand the static reservoir properties and dynamic inflow performance. The open-hole and cased-hole logs consistently showed that the “rabbit ears” interval at the base of the Upper Haynesville and the top interval of the Upper Haynesville were excellent lateral well-landing zones for best production. We combined microseismic data with production log data and found that the effective stimulated rock volume by hydraulic fracturing was mostly concentrated in the top interval of the Upper Haynesville and the “rabbit ears” interval at the base of the Upper Haynesville. The study demonstrated that a multidisciplinary approach was necessary in determining the best zone to land Haynesville horizontal wells.