Sand-shale Sequences Research Articles

Stochastic quantification of CO2 fault sealing capacity in sand-shale sequences

Structural fault trapping of buoyant fluids, such as hydrocarbons and CO2, relies on fault sealing capacity. The traditional approach to quantifying the sealing capacity of fault zone materials is Shale Gouge Ratio (SGR), which implicitly homogenizes fault properties. However, a large range of fault throw and the presence of fault heterogeneity can lead to different trapping capacities for the same structure. This paper presents a stochastic study to statistically determine the possible range of CO2 column height at a normal fault in sand-shale sequences. We present the procedures of two stochastic models including the continuous shale gouge model (CSGM) and the discrete smear model (DSM). The models are applied in an example case for the High Island field in the Gulf of Mexico (GOM) basin combining borehole geophysical data and measurements from laboratory experiments. Both one-dimensional and two-dimensional cases are discussed. The results show that more than 50% of the realizations predict negligible fault sealing capacity. The CSGM method shows that CO2 column height is overall proportional to SGR and breakthrough pressure. The DSM model suggests that clay smear continuity may significantly affect fault sealing capacity. Large fault throws (>100 m) result in smear breaches and therefore in highly variable maximum CO2 column heights, varying from 0 m to a maximum of ∼95 m. Both the DSM method and the CSGM method proposed in this paper permit explaining geologic uncertainties and the resulting variability of column heights observed in the field. Our results together with the field data from the literature demonstrate the utility of combining both methods to help improve column height prediction. Uncertainty quantification of clay ductility, smear location, and fault heterogeneity is important for determining fault sealing capacity and improving reservoir risk management associated with carbon dioxide geological storage.

A hybrid physics and machine learning approach for velocity prediction

Elastic well logs play an important role in reservoir characterization in the subsurface. However, due to the high expense of drilling, only a few wells are drilled to limited depths, making it difficult to understand the deposition and execute geophysical activities such as building background models for seismic inversion and property models for seismic forward modeling. We begin with P-velocity prediction between the wells and extension along the wellbore to tackle this problem. A hybrid workflow is introduced based on seismic and available P-velocity logs, including well-log decomposition, relative rock physics, seismic forward modeling, feature engineering based on seismic transform, optimal attribute selection, and machine learning network training and prediction. In this hybrid workflow, relative P-velocity instead of absolute P-velocity is used for labeling. The rock-physics study and seismic forward modeling contribute to label augmentation. The machine learning approach assists in discovering the relationship between the relative P-velocity and the optimal seismic attributes. Under physics rules, the predicted relative velocity through the trained network is integrated with the compaction trend to estimate the final absolute velocity. This hybrid workflow is applied to a case study of sand-shale sequences in northern China. The model-based deterministic inversion and data-driven machine learning approaches are also compared. The results of blind well testing indicate that the data-driven approach lacks generalization capability and fails to predict extension in some blind wells. The physics-based inversion performs differently in blind wells in different locations. By contrast, P-velocity prediction with the hybrid workflow improves prediction accuracy in all blind wells, horizontally and vertically. The results indicate that this hybrid workflow promises interpolating and extending elastic well logs when the deposition environment does not vary significantly. Further studies are recommended to discuss the applicability of this workflow.

Deep learning for predicting permeability logs in offset wells using an artificial neural network at a Waggoner Ranch reservoir, Texas

Permeability logs are critical data used to assess reservoir quality, which can impede the confidence of reservoir productivity without proper characterization. In particular, this can be significant in shale-sand sequence reservoirs that have heterogeneous lithology. Fortunately, permeability logs can be derived from Stoneley waves that are extracted from conventional full-waveform sonic logs. Because sonic logs are not always available in old wells, exploring alternatives to predict permeability is essential. The artificial neural network method is one option that provides elements to develop a model to predict permeability logs in offset wells. Consequently, a model is constructed using standard logs as input data and a Stoneley-wave permeability log as the desired output. These logs are obtained from a new well containing a complete suite of logs including full-waveform sonic data and a permeability log. The open-source Python library Keras provides the environment to generate the model. The model is applied to two nearby wells in which permeability logs do not exist. The borehole separation from the new well to the far well is 2055 ft, and the separation distance to the near well is 1370 ft. The logging data were acquired from wells located in an oil reservoir at Waggoner Ranch in northeast Texas. The reservoir geology is a sand-shale sequence intercepted by thin limestone markers at several depths. Permeability logs are predicted and correlated with other logs and their corresponding lithology. Sands partially saturated with hydrocarbons are identified by their permeability properties at the wells. The sands were previously characterized and mapped from impedance data using a nonlinear inversion of reflection seismic image constrained with well logs. The data analysis demonstrates the usefulness of the neural network approach to predict permeability in reservoirs where offset wells are available and only one well contains a permeability log.

Multiphase CO2-brine transport properties of synthetic fault gouge

Faults are key components in defining fluid migration pathways and seals in sedimentary basins. The sealing capacity of faults is closely related to the petrophysical and geomechanical properties of fault gouge. Clay smear, cataclasis, and diagenesis favor a high capillary breakthrough pressure and low permeability in clastic sediments, and therefore fault gouge seal. However, significant uncertainty remains in accurately predicting the sealing capacity of faults for CO2 storage. We conducted a series of experiments, including absolute permeability, breakthrough pressure, and post-breakthrough CO2 permeability measurements on synthetic fault gouge samples, made from homogeneous mixtures of Frio sand and Anahuac shale, lithofacies of tertiary sediments in the Gulf of Mexico basin. The results show that the permeability of synthetic fault gouge decreases by about one order of magnitude with increments of 10 wt% of clay (mostly smectite) from the Anahuac shale. Independent of clay content and bulk porosity, all permeability measurements scale with the void ratio of the clay fraction. The breakthrough pressure of synthetic fault gouge increases by approximately half order of magnitude with increments of 10 wt% clay. The samples with clay content above 40 wt% reach a breakthrough pressure equivalent to a (supercritical) CO2 column height of more than 100 m. The measurements on fault gouge properties are meaningful to quantitatively evaluate fault sealing capability and migration of buoyant fluids through faults in sand-shale sequences.

Integrated analysis of well logs for productivity prediction in sand-shale sequence reservoirs of the Niger Delta—a case study

Work on fluid productivity prediction in the Niger Delta is sparse or even rare because of the need for expensive but limited information from core data, well test data, and nuclear magnetic resonance (NMR) data. Paucity of this information in the study area due to prohibitive cost makes justification of results of fluid productivity predictions very difficult to justify. However, an integrated well log analysis method is applied to three sand-shale sequence reservoirs of the Niger Delta for fluid productivity predictions in this work using basic log suites. This work utilizes irreducible saturation analysis calculated from the Buckles’ method for three (3) reservoirs in Well “AW” and Well “T”. Rock Physics estimates of Poisson’s ratio values and Vp/Vs ratio values allow for fluid type designation from a cross plot of Poisson’s ratio and Vp/Vs ratio; hence, it is possible to interpret gas saturation, brine saturation, and oil saturation for these reservoirs. The Buckle method yields numbers that are used to estimate irreducible water saturation values independently of Archie’s and Archie’s modified equations. In addition, Buckle’s numbers allow for a pore size and grain size forecast for sandstone reservoirs being intercepted within the two wells. For each of these reservoirs, water saturation (Sw) is compared with the irreducible water saturation (Swirr) with the logic that for a reservoir having Swirr > Sw, no water production is expected. Conversely, for Swirr Sw, no water production should be expected. In well “T” reservoirs T1, T2, and T3, all had Swirr > Sw. Hence, this work demonstrated the usefulness and effectiveness of the Buckle’s method in estimating many useful petrophysical parameters to predict reservoir productivity in the studied area, Niger Delta for wells lacking core data, well test data, and NMR data. Field-wide deployment of this technique may help to improve the reduction in oil-related water production and the cost of managing the produced water at the initial stage of production in the Niger Delta in the reservoir.

Application of AVO attributes for gas channels identification, West offshore Nile Delta, Egypt

The offshore part of the Nile Delta is considered one of the most prolific provinces for gas production and for future petroleum exploration. Amplitude Variation with Offset (AVO) analysis supported by composite logs considered as one of the best-advanced techniques enables the interpreter to understand the seismic data. It is used to generate a new view of the output results, especially for the identification of gas zones as gas channels by using pre-stack AVO attributes that based on the intercept product gradient (A*B) and the Scaled Poisson’s Ratio Change. Free gas, regardless of the percentage show obvious AVO anomaly. Well log data, including gamma-ray, resistivity, and Vp sonic logs are used in the seismic data to well tie and in the generation of the synthetic seismogram. Seismic data conditioning processes with check-shot correction is performed to improve the resolution of the reflection events and signal to noise ratio. AVO attributes technique, as a direct hydrocarbon indicator, including AVO gradient analysis and AVO crossplot separate the gas levels in the sand-shale sequences. The identified gas-bearing zones consistent with well log data responses. As the main conclusion, we show the visual evidence for the gas-bearing zones by interpreting different AVO responses due to the changes in fluid and rock types.

Petrophysical interpretation in shaly sand formation of a gas field in Tanzania

An onshore gas field (hereafter called the R field—real name not revealed) is in the southeast coast of Tanzania which includes a Tertiary aged shaly sand formation (sand–shale sequences). The formation was penetrated by an exploration well R–X wherein no core was acquired, and there is no layer-wise published data of the petrophysical properties of the R field in the existing literature, which are essential to reserves estimation and production forecast. In this paper, the layer-wise interpretation of petrophysical properties was undertaken by using wireline logs to obtain parameters to build a reservoir simulation model. The properties extracted include shale volume, total and effective porosities, sand fractions and sand porosity, and water saturation. Shale volume was computed using Clavier equation from gamma ray. Density method was used to calculate total and effective porosities. Thomas–Stieber method was used to determine sand porosity and sand fraction, and water saturation was computed using Poupon–Leveaux model. The statistics of the parameters extracted are presented, where shale volume obtained that varies with zones is between 6 and 54% volume fraction, with both shale laminations and dispersed shale were identified. Total porosity obtained is in a range from 12 to 22%. Sand porosity varies between 15 and 25%, and sand fraction varies between 33 and 93% height fraction. Average water saturation obtained is between 32 and 49% volume fraction.

Numerical local upscaling of elastic geomechanical properties for heterogeneous continua

An efficient, numerical local upscaling technique for estimating elastic geomechanical properties in heterogeneous continua is proposed. The upscaled anisotropic elastic properties are solved locally with various boundary conditions and reproduce the anisotropic geomechanical response of fine-scale simulations of sand–shale sequence models with horizontal and inclined shale bedding planes. The algorithm is automated in a parallel program and can be used to determine optimum upscaling ratios in different regions of the reservoir. The successful application of the proposed upscaling method in a field-scale coupled reservoir–geomechanics simulation demonstrates an improvement in overall computational efficiency while maintaining accuracy in the geomechanical response and reservoir performance.

Nonlinear approach to spectral ratio method for estimation of seismic quality factor from VSP data

Conventional spectral ratio method for estimating Seismic Quality factor (Q) involves log-linearization and least square fitting, which is very sensitive to noise. In this work we have proposed a new approach to spectral ratio method, where the seismic quality factor is estimated by non-linear inversion of spectral ratios using Levenberg-Marquardt (LM) method. The efficacy of the proposed methodology has been tested on synthetic and real VSP datasets. Both conventional log-spectral ratio method (LSR) and nonlinear optimization method (LM) could effectively estimate the Q model for datasets having good signal to noise ratio. Numerical tests indicated that with increase in noise floor LM method provided more accurate and stable results. Application on real VSP dataset having high S/N ratio revealed that the estimated Q models using both the approaches are almost similar. Results demonstrate a reasonable correlation of Q model in sand-shale sequence and low Q values around 69 in gas reservoir.

Rock physics model for seismic velocity & fluid substitution in sub‐resolution interbedded sand–shale sequences

ABSTRACTThe measured geophysical response of sand–shale sequences is an average over multiple layers when the tool resolution (seismic or well log) is coarser than the scale of sand–shale mixing. Shale can be found within sand–shale sequences as laminations, dispersed in sand pores, as well as load bearing clasts. We present a rock physics framework to model seismic/sonic properties of sub‐resolution interbedded shaly sands using the so‐called solid and mineral substitution models. This modelling approach stays consistent with the conceptual model of the Thomas–Stieber approach for estimating volumetric properties of shaly sands; thus, this work connects established well log data‐based petrophysical workflows with quantitative interpretation of seismic data for modelling hydrocarbon signature in sand–shale sequences. We present applications of the new model to infer thickness of sand–shale lamination (i.e., net to gross) and other volumetric properties using seismic data. Another application of the new approach is fluid substitution in sub‐resolution interbedded sand–shale sequences that operate directly at the measurement scale without the need to downscale; such a procedure has many practical advantages over the approach of “first‐downscale‐and‐then‐upscale” as it is not very sensitive to errors in estimated sand fraction and end member sand/shale properties and remains stable at small sand/shale fractions.

Unexpected behavior of logging-while-drilling neutron porosity logs in water-wet, sand-shale sequences

When logging through certain water-wet sand-shale sequences offshore Malaysia, the thermal neutron porosity measurement from an 8-in logging-while-drilling (LWD) tool exhibits an apparent lack of dynamic range in its sandstone porosity response. Petrophysicists using these data to determine sandstone-silt-shale points were finding that the shale points fell too near the sandstone line to be usable. An extensive nuclear Monte Carlo modeling campaign was performed to address this issue, which indicated that the tool response, while unexpected, was accurate. Modeling verified that neutron logs can exhibit a poor dynamic range just by happenstance, but an accurate assessment of the shale volume fraction [Formula: see text] should still be feasible. Surprisingly, the shale responses for this LWD tool, a smaller LWD tool, and a wireline tool are quite similar, invalidating a common expectation that LWD tools should be noticeably more epithermal in their response, and thus be less sensitive to absorbers in the clays. Modeling the actual shales, based on X-ray diffraction (XRD) analyses of cuttings, revealed the answer. In the wells with a poor dynamic range in the shale response, the quartz content was very high. Simulating the actual XRD-determined shales reproduced the actual log crossplot very nicely. Points in the shale crossplot fall near the sandstone line because the formations are primarily [Formula: see text], with only a small amount of clay. This result explains the response of the LWD tool.

Bayesian inversion of synthetic AVO data to assess fluid and shale content in sand-shale media

Reservoir characterization of sand-shale sequences has always challenged geoscientists due to the presence of anisotropy in the form of shale lenses or shale layers. Water saturation and volume of shale are among the fundamental reservoir properties of interest for sand-shale intervals, and relate to the amount of fluid content and accumulating potentials of such media. This paper suggests an integrated workflow using synthetic data for the characterization of shaley-sand media based on anisotropic rock physics (T-matrix approximation) and seismic reflectivity modelling. A Bayesian inversion scheme for estimating reservoir parameters from amplitude vs. offset (AVO) data was used to obtain the information about uncertainties as well as their most likely values. The results from our workflow give reliable estimates of water saturation from AVO data at small uncertainties, provided background sand porosity values and isotropic overburden properties are known. For volume of shale, the proposed workflow provides reasonable estimates even when larger uncertainties are present in AVO data.

Stress-induced seismic azimuthal anisotropy, sand-shale content, and depth trends offshore North West Australia

Seismic azimuthal anisotropy is apparent when P-wave velocities vary with source-receiver azimuth and downward-propagating S-waves split into two quasi-S-waves, polarized in orthogonal directions. Not accounting for these effects can degrade seismic image quality and result in erroneous amplitude analysis and geologic interpretations. There are currently no physical models available to describe how azimuthal anisotropy induced by differential horizontal stress varies with sand-shale lithology and depth; we develop a model that does so, in unconsolidated sand-shale sequences offshore North West Australia. Our method naturally introduces two new concepts: “critical anisotropy” and “anisotropic depth limit.” Critical anisotropy is the maximum amount of azimuthal anisotropy expected to be observed at the shallowest sediment burial depth, where the confining pressure and sediment compaction are minimal. The anisotropic depth limit is the maximum depth where the stress-induced azimuthal anisotropy is expected to be observable, where the increasing effects of confining pressure, compaction, and cementation make the sediments insensitive to differential horizontal stress. We test our model on borehole log data acquired in the Stybarrow Field, offshore North West Australia, where significant differential horizontal stress and azimuthal anisotropy are present. We determine our model parameters by performing regressions using dipole shear log velocities, gamma-ray shale volume logs, and depth trend data. We perform a blind test using the model parameters derived from one well to accurately predict the azimuthal anisotropy values at two other wells in an adjacent area. We use our anisotropy predictions to improve the well-tie match of the modeled angle-dependent reflectivity amplitudes to the 3D seismic amplitude variation with offset data observed at the well locations. Future applications of our method may allow the possibility to estimate the sand-shale content over a wide exploration area using anisotropic parameters derived from surface 3D seismic data.

Fluid substitution for thinly interbedded sand-shale sequences using the mesh method

Gassmann’s fluid substitution model is intended for a monomineralic, homogeneous porous rock, in which pore pressures induced by applied loads can equilibrate throughout the pore space. These assumptions are violated when Gassmann’s equations are applied to measurements that represent effective medium averages over subresolution layers of alternating sand and shale. The conventional procedure for treating this problem has been to first downscale; i.e., estimate the properties of the fine-scale sand and shale endmembers from the coarse-scale measurements, apply Gassmann’s fluid substitution to the sand only, and then Backus average back to the original scale. This procedure, however, is very sensitive to errors in estimated sand fraction and shale properties and becomes particularly unstable at small sand fractions. A new method for fluid substitution combines rock-physics models for dispersed and interbedded sand-shale systems, which are often approximated with Reuss or lower Hashin-Shtrikman interpolations between endmembers quartz mineral, clean sand, and shale. When expressed as P-wave compliance versus porosity, these trends become approximately linear. The Backus average of the normal incidence P-wave compliance of thinly layered mixtures of various sand-shale facies is also a linear trend with porosity. As a result, the upscaled fluid substitution change of compliance of any point within the dispersed or layered sand-shale system is approximately proportional to the fluid-substituted change of compliance of the clean sand endmember, scaled by the ratio of effective porosity to clean sand porosity. The result is a fluid substitution procedure that operates directly at the measurement scale, without the need to downscale the measurements, while still changing fluid in the sand layers only.

A geometrical model for shale smear: implications for upscaling in faulted geomodels

A new 1D bed-scale model has been built to help model shale smear in interbedded sand–shale sequences using the shale smear factor (SSF). A smear envelope is generated by mapping each potential shale smear onto the fault plane employing five different shale smear geometries. Graphical outputs then focus on the cumulative length of the resultant smears and the remaining sand–sand juxtaposition windows in the predicted shale smear envelope. The smears are evaluated stochastically with lengths that are a randomized function of the estimated Vclay content of the source shale layers, allowing the smear pattern to change with each realization. A new fragmented smear mode is developed that allows discontinuous smears to be distributed randomly on the fault plane and can be used to modify the smear pattern as fault displacement increases. The model has been tested using well data. Results show that windows in the smear envelope are commonly present, and that their frequency and location are dependent on the smear placement model and sand–shale stacking pattern. Smear fragmentation leads to more windows being preserved. The 1D model can also assess the impact of geocellular upscaling on fault seal analysis. Upscaling reduces cross-fault sand connectivity due to the elimination of thin beds. Shale smear envelopes are also reduced in length as fewer shale beds are involved, even though layers are thicker. A fault may or may not appear more sealing dependent on the layer configuration and net-to-gross ratio (NTG). The model offers results that can inform input to fault seal evaluations and allows the effect of geomodel upscaling to be more closely interrogated.

Mechanical characteristics of laminated sand–shale sequences identified from sonic velocity and density correlations

In the past, numerous relations between sonic velocity (i.e. an inverse of sonic travel time DT) and rock density were developed that were suitable for certain fields or certain rocks only. In this paper, the correlations between sonic and density log measurements were investigated again using the data information from multiple fields of Gulf of Mexico (GOM) and North Sea (NS). For sandstone-shale sequences, the dominant linear relationships between sonic travel time (DT) and formation density (RHOB) were observed, and compared with the popular Gardner’s method (Gardner et al. in Geographics 39(6):770–780, 1974) along with other known methods. The implications of data clusters distinguished by formation lithologies and rock mechanical strengths were revealed from cross-plot analysis. The probabilities and uncertainties of the developed correlations were determined using the actual histograms from the collected data of GOM and NS fields coupled with Monte Carlo simulations.

Pore-scale analysis of electrical properties in thinly bedded rock using digital rock physics

We investigated the electrical properties of laminated rock consist of macro-porous layers and micro-porous layers based on digital rock technology. Due to the bedding effect and anisotropy, traditional Archie equations cannot well describe the electrical behavior of laminated rock. The RI-Sw curve of laminated rock shows a nonlinear relationship. The RI-Sw curve can be divided into two linear segments with different saturation exponent. Laminated sand-shale sequences and laminated sands of different porosity or grain size will yield macroscopic electrical anisotropy. Numerical simulation and theoretical analysis lead to the conclusion that electrical anisotropy coefficient of laminated rock is a strong function of water saturation. The function curve can be divided into three segments by the turning point. Therefore, the electrical behavior of laminated rock should be considered in oil exploration and development.

Validation of lateral fluid flow in an overpressured sand-shale sequence during development of Azeri-Chirag-Gunashli oil field and Shah Deniz gas field: South Caspian Basin, Azerbaijan

Data collected over the past 15 years from exploration, appraisal and production in the offshore South Caspian Sea validates the previously developed model of lateral fluid flow from the overpressured basin center to the basin margins within the sandstone aquifers of the Pliocene Productive Series. Specifically, new data confirm the predictions that 1) although both sandstones and shales are overpressured, sandstones are generally less overpressured than shales, 2) there is a lateral, regional gradient in sandstone overpressure, decreasing from the basin center to the basin margin and 3) the impact on the pressure field from local features such as mud volcanoes or local faults is limited. Additional pressure data, combined with regional seismic mapping, suggests variations in lateral fluid flow in different stratigraphic intervals. These data show that the less continuous sandstones of the upper and lower Productive Series are closer to the surrounding shale pressures as they are less well connected to the basin margin outlet, whereas, continuous sandstones in the middle Productive Series show the highest amount of lateral pressure transfer from the basin center and are therefore at lower pressures than the surrounding shales. Pressure data from development wells at the Azer-Chirag-Gunashli oil field and the Shah Deniz gas-condensate field reveal local variations in sandstone and shale overpressure resulting from the lateral pressure transfer affect (Traugott and Heppard, 1994; Traugott, 1996; Swarbrick and Osborne, 1998; Yardley and Swarbrick, 2000). Across large, high relief structures, well-connected sandstones transmit fluid pressures from the adjacent, deep overpressured synclines into the shallower crest of the structure. Pressures in sandstones decrease updip along a hydrostatic gradient (0.433 psi/ft). The pressure gradient in the shales however, will change according to the shale overpressure gradient. In the South Caspian Basin the overpressure gradient in the shales varies between 0.6 and 0.9 psi/ft. Therefore, the relative overpressure between the sandstones and shales varies along structural dip. There are a number of important implications to exploration, appraisal, and development because of large scale lateral fluid flow. Lateral fluid flow has consequences for the sealing capacity of sandstone reservoirs and the variable position of hydrocarbon –to- water contacts around a structural accumulation. This requires each sandstone–shale couplet be considered separately for pore pressure prediction. Basin-scale 3D models were constructed to better understand the implications of basin-scale fluid flow within and between individual reservoirs at each structure.

An effective inclusion-based rock physics model for a sand–shale sequence

A simple inclusion-based rock physics method is investigated for modelling the elastic logs recorded in a sand–shale sequence. The model uses a single aspect ratio at each depth applied to the total porosity. The aspect ratio varies with depth whilst the elastic properties of the component minerals are held constant. The variation in the effective aspect ratio with depth is predictable from petrophysical properties. Once the relationship has been established, it can be used to identify and correct data quality issues and improve the petrophysical interpretation, resulting in a consistent and corrected set of logs for seismic reservoir characterization workflows. The model relies on the ability to predict both shear and compressional velocities using a single aspect ratio at each depth, and on this aspect ratio being predictable from data other than the elastic logs themselves. It is not anticipated that these criteria will be fulfilled for all rocks. However, it is expected that even when the method fails the results will still lend insight into the physics of the rocks.

Unearthing New Layers - Crosswell Seismic Redefines Seismic Imaging in Bunyu Field, Indonesia

Surface seismic is fundamental information for reservoir mapping and in-fill drilling decisions. A good seismic is critical to successful development of a field. However, at times, the surface seismic is of degraded quality due to various reasons which makes the mapping and interpretation of the reservoir layers difficult and uncertain. Near-surface conditions such as topography, weathering layer adversely affect the surface seismic data acquisition & processing. In Bunyu field in Indonesia, problem is further compounded by the presence of near surface coal seams which renders seismic to be of poor quality. In order to optimize the field development and boost recovery, enhanced seismic is seen as a fundamental requirement to make informed in-fill drilling decisions. Crosswell seismic provides high resolution imaging of the subsurface at the reservoir scale. The technology is used for delineating complex structure. It is not affected by the surface conditions as the transmitter and receivers are deployed downhole in separate wells, providing velocity tomogram and reflection imaging between the wells. Bunyu Field in East Kalimantan is on production since 1950 with declining production over the years. It is primarily a discontinuous sand-shale sequence with shallow coal layers. The existing 3D seismic is of poor quality which makes reservoir interpretation very uncertain. It is difficult to map these channel sands due to poor seismic. Crosswell seismic was thus acquired to complement the 3D seismic information for informed infill drilling decisions and field optimization. Crosswell seismic has provided a dramatic improvement in seismic imaging even at large interwell distances and will be helpful in delineating reservoir and ultimately aid in better in-fill drilling.