Reservoir Lithofacies Research Articles

Geomechanical behavior of Cambrian Mount Simon Sandstone reservoir lithofacies, Iowa Shelf, USA

The Mount Simon Sandstone (Mt. Simon), a basal Cambrian sandstone underlying much of Midwestern US, is a target for underground CO2 storage and waste injection which requires an assessment of geomechanical behavior. The range of depositional environments yields a heterogeneous formation with varying porosity, permeability, and mechanical properties. Experimental deformational behavior of three distinct Mt. Simon lithofacies was examined via axisymmetric compressional testing of core samples. Initial yielding was confirmed with acoustic emissions in many tests and failure envelopes were determined for each lithofacies. Evolution of elastic moduli with stress and plastic strain was determined by use of unload–reload cycles, which permit separation of total measured strains into elastic and plastic strains. The Upper Mt. Simon lithofacies yields at higher shear stresses compared to two “Lower” lithofacies, with little modulus degradation with plastic strain. Lower Mt. Simon lithofacies are weaker and deform plastically with modulus degradation. This range in constitutive response is quantified with an elasto-plasticity model. Based on these results, Mount Simon Sandstone would likely deform elastically during CO2 injection and storage, with large pore pressure increases (∼8–9MPa above hydrostatic) predicted to initiate plastic yielding. Nonetheless, near-wellbore damage could result in weaker lithofacies during injection and/or brine extraction.

Integration of spectral gamma-ray and geochemical analyses for the characterization of the upper Jurassic Arab-D carbonate reservoir: outcrop analogue approach, central Saudi Arabia

Investigation by spectral gamma-ray (SGR) and inductively coupled plasma-mass spectrometry (ICP-MS) geochemical analyses of the Upper Jurassic Arab-D reservoir analogue (central Saudi Arabia) revealed a strong correlation between the SGR response of the outcrop lithofacies and their elemental content. The two units of the reservoir (the Upper Jubaila Member of the Jubaila Formation and the Arab-D Member of the Arab Formation) showed distinctive SGR log profiles controlled mainly by their lithofacies associations. The geochemical analysis revealed four groups of chemical associations. Group 1 includes SiO 2 , Al 3 O 2 , Fe 2 O 3 , K 2 O, TiO 2 , Zr and Zn. This group has a strong relationship with the radioactive elements U, K and Th (Group 4). The reservoir facies exhibit high concentrations of chemicals from these two clusters. Group 2 includes CaO and Sr. A high concentration of chemicals from this group indicates a tendency towards pure carbonate facies and fewer siliciclastic impurities. A high concentration of MgO, the only chemical included in Group 3, marks dolomitic zones. Group 4 contains the radioactive elements. The boundary between the Upper Jubaila Member and the Arab-D Member is clearly defined from vertical SGR log profiles, vertical geochemical data logging and cross-plots of Group 1 chemicals with the radioactive elements in Group 4. The geochemical data for the Upper Jubaila Member show a very low concentration of U, K and Th. Consequently, the SGR response of the lithofacies was very low. All of the reservoir lithofacies showed high concentration of Group 1 and Group 4 components compared with the non-reservoir lithofacies. The Th/U ratio indicates a general shoaling upwards following the same trend of the outcrop lithofacies. A high Th/U ratio characterizes reservoir lithofacies, whereas a low ratio characterizes non-reservoir lithofacies. The lithofacies and the SGR log motifs were related in the measured sections. This study provides a method for predicting lithofacies from SGR log motifs within a high-resolution stratigraphic framework integrated with the geochemical data analysis. Here, we introduce an exploration guide for subsurface reservoir zonation and the identification of formation tops.

Arabian carbonate reservoirs: A depositional model of the Arab-D reservoir in Khurais field, Saudi Arabia

The Upper Jurassic Arab Formation in the Arabian Peninsula, the most prolific oil-bearing interval of the world, is a succession of interbedded thick carbonates and evaporites that are defined stratigraphically upsection as the Arab-D, Arab-C, Arab-B, and Arab-A. The Arab-D reservoir is the main reservoir in Khurais field, one of the largest onshore oil fields of the Kingdom of Saudi Arabia. In Khurais field, the Arab-D reservoir is composed of the overlying evaporitic Arab-D Member of the Arab Formation and the underlying upper part of the Jubaila Formation. It contains 11 lithofacies, listed from deepest to shallowest: (1) hardground-capped skeletal wackestone and lime mudstone; (2) intraclast floatstone and rudstone; (3) pelletal wackestone and packstone; (4) stromatoporoid wackestone, packstone, and floatstone; (5) Cladocoropsis wackestone, packstone, and floatstone; (6) Clypeina and Thaumatoporella wackestone and packstone; (7) peloidal packstone and grainstone; (8) ooid grainstone; (9) crypt-microbial laminites; (10) evaporites; and (11) stratigraphically reoccurring dolomite. The Arab-D reservoir lithofacies succession represents shallowing-upward deposition, which, from deepest to shallowest, reflects the following depositional environments: offshore submarine turbidity fans (lithofacies 1 and 2); lower shoreface settings (lithofacies 3); stromatoporoid reef (lithofacies 4); lagoon (lithofacies 5 and 6); shallow subtidal settings (lithofacies 7 and 8); peritidal settings (lithofacies 9); and sabkhas and salinas (lithofacies 10). The depositional succession of the reservoir represents a prograding, shallow-marine, reef-rimmed carbonate shelf that was subjected to common storm abrasion, which triggered turbidites.

Carbonate-platform scale correlation of stacked high-frequency sequences in the Arab-D reservoir, Saudi Arabia

The Late Jurassic Arab Formation contains a number of hydrocarbon-bearing carbonates, the most important of which is the lowermost Arab-D reservoir. The reservoir lithofacies in Khurais Field are: couplets of 1) lime mud and 2) intraclastic lithofacies representing basinal turbidites; 3) pelletal lithofacies representing lower shoreface sands and silts; 4) stromatoporoid lithofacies representing a reef; 5) Cladocoropsis and 6) dasyclad lithofacies representing a lagoon; 7) peloidal and 8) oolitic lithofacies representing shore-attached sand sheets; 9) cryptomicrobial lithofacies representing supratidal flats; 10) anhydrites representing sabkha followed by salina deposits; and 11) stratigraphically reoccurring dolomite.These are arranged in two, partially preserved, third-order sequences, the upper of which represents the Arab-D Member and the lower of which represents the upper Jubaila Formation. Within these sequences lie six fourth-order high frequency sequences, composed of fifth-order parasequences and parasequence-scale cycles.The preserved upward shallowing trend of the Arab-D reservoir is manifested laterally by a regional eastward thickening interpreted to be the result of an eastward progradation across the shallow Late Jurassic epeiric shelf and into the relatively deep Arabian intrashelf basin.This study presents a correlation model that explains the drastic thickening and downward climb of the reservoir lithofacies that is observed between the outcrops south of Riyadh and the subsurface in Ghawar Field.This model is different from the one currently used and predicts an eastward porosity improvement in the upper part of the reservoir accompanied by a porosity reduction in the lower part, assuming a null diagenetic modification effect.

High-resolution facies and porosity models of the upper Jurassic Arab-D carbonate reservoir using an outcrop analogue, central Saudi Arabia

Subsurface models of hydrocarbon reservoirs are coarse and of low resolution when compared with the actual geologic characteristics. Therefore, the understanding of the three-dimensional architecture of reservoir units is often incomplete. Outcrop analogues are commonly used to understand the spatial continuity of reservoir units. In this study, a Late Jurassic outcrop analogue for the Arab-D reservoir of central Saudi Arabia was used to build a high-resolution model that captures fine geologic details. Subsurface reservoir lithofacies were matched with those from the studied outcrop, and porosity values derived from published core and well log data from the Ain Dar, Uthmanyah, and Shudgum areas of the Ghawar Field, eastern Saudi Arabia, were then applied to the equivalent lithofacies in the outcrop. Maximum, minimum, and average subsurface porosity for each lithofacies were distributed in the facies model using a geostatistical algorithm to produce nine porosity models for the field data. Several realisations were run to visualise the variability in each model and to quantitatively measure the uncertainty associated with the models. The results indicated that potential reservoir zones were associated with grainstone, packstone, and some wackestone layers. Semivariogram analysis of the lithofacies showed good continuity in the N-S direction and less continuity in the E-W direction. The high-resolution lithofacies models detected permeability barriers and isolated low porosity bodies within the potential reservoir zones. This model revealed the porosity distribution in areas smaller than one cell in the subsurface model and highlighted the uncertainty associated with several aspects of the model.

Classification and identification of hydrocarbon reservoir lithofacies and their heterogeneity using seismic attributes, logs data and artificial neural networks

3D seismic data interpretation plays a key role in identifying Lithofacies and their lateral changes for hydrocarbon reservoirs exploration. Among mathematical analysis techniques, Artificial Neural Network (ANN) offers superior handling over inherent non-linearity of seismic data. Here we applied multi-attribute analysis based on ANN methods and well logs data to determine the lithofacies alteration and heterogeneity in one of the structural-stratigraphic oil fields at Persian Gulf. Statistical analysis on seismic attributes together with their geological significance were the main criteria to choose proper seismic attributes for classification. The results showed areas of the shaly- and sandy-dominated facies in the reservoir interval. We suggested further attempts to locate oil reserves at the northeast and southwest parts of the area according to our findings on dominancy of sandy-dominated facies with shaly interlayers in those regions.

Carbonate reservoir characterization with lithofacies clustering and porosity prediction

One of the objectives in reservoir characterization is to quantitatively or semi-quantitatively map the spatial distribution of its heterogeneity and related properties. With the availability of 3D seismic data, artificial neural networks are capable of discovering the nonlinear relationship between seismic attributes and reservoir parameters. For a target carbonate reservoir, we adopt a two-stage approach to conduct characterization. First, we use an unsupervised neural network, the self-organizing map method, to classify the reservoir lithofacies. Then we apply a supervised neural network, the back-propagation algorithm, to quantitatively predict the porosity of the carbonate reservoir. Based on porosity maps at different time levels, we interpret the target reservoir vertically related to three depositional phases corresponding to, respectively, a lowstand system tract before sea water immersion, a highstand system tract when water covers organic deposits and a transition zone for the sea level falling. The highstand system is the most prospective zone, given the organic content deposited during this stage. The transition zone is also another prospective feature in the carbonate depositional system due to local build-ups.

On the Capability of Support Vector Machines to Classify Lithology from Well Logs

The increasing technical demands placed on models with promising generalization performance to identify lithology from well-log data points has led to search for more efficient methods than conventional statistical methods. Conventional methods such as discriminant analysis recently applied neural networks belong to the general class of Empirical Risk Minimization techniques which aim to minimize training error. On the other hand, methods built on support vector machines (SVMs) are based on the Structural Risk Minimization principle which in turn is based on statistical learning theory. Statistical learning enhancement gives better generalization abilities by minimizing the testing error. In this research, a new modeling framework based on SVMs is described to identify lithfacies from well logs. A SVM classification formulation is presented together with feature selection based on fuzzy theory to identify potential features to enable discriminatory power from well logs. The results demonstrate that SVMs provide an accurate means to identify lithofacies in a heterogeneous sandstone reservoir. The true classification was based on detailed core description of a training well. The SVM-based lithology classifier was compared to discriminant analysis and probabilistic neural networks. The results reveal that the SVM classifier performs the best of the three methods.

Geologic controls on gas hydrate occurrence in the Mount Elbert prospect, Alaska North Slope

Data acquired at the BPXA-DOE-USGS Mount Elbert Gas Hydrate Stratigraphic Test Well, drilled in the Milne Point area of the Alaska North Slope in February, 2007, indicates two zones of high gas hydrate saturation within the Eocene Sagavanirktok Formation. Gas hydrate is observed in two separate sand reservoirs (the D and C units), in the stratigraphically highest portions of those sands, and is not detected in non-sand lithologies. In the younger D unit, gas hydrate appears to fill much of the available reservoir space at the top of the unit. The degree of vertical fill with the D unit is closely related to the unit reservoir quality. A thick, low-permeability clay-dominated unit serves as an upper seal, whereas a subtle transition to more clay-rich, and interbedded sand, silt, and clay units is associated with the base of gas hydrate occurrence. In the underlying C unit, the reservoir is similarly capped by a clay-dominated section, with gas hydrate filling the relatively lower-quality sands at the top of the unit leaving an underlying thick section of high-reservoir quality sands devoid of gas hydrate. Evaluation of well log, core, and seismic data indicate that the gas hydrate occurs within complex combination stratigraphic/structural traps. Structural trapping is provided by a four-way fold closure augmented by a large western bounding fault. Lithologic variation is also a likely strong control on lateral extent of the reservoirs, particularly in the D unit accumulation, where gas hydrate appears to extend beyond the limits of the structural closure. Porous and permeable zones within the C unit sand are only partially charged due most likely to limited structural trapping in the reservoir lithofacies during the period of primary charging. The occurrence of the gas hydrate within the sands in the upper portions of both the C and D units and along the crest of the fold is consistent with an interpretation that these deposits are converted free gas accumulations formed prior to the imposition of gas hydrate stability conditions.

Petroleum systems in rift basins – a collective approach inSoutheast Asian basins

This paper synthesizes some of the main conclusions reached in a recent regional review of the Tertiary basins of Southeast Asia, carried out by Shell. Four distinctive types of petroleum systems, correlating with the four main stages of basin evolution (early to late syn-rift and early to late post-rift), are developed widely in the basins. These petroleum system types have characteristic interbedded environmentally controlled source, reservoir and seal lithofacies which, in combination with the structural trap style, determine the hydrocarbon habitat. Variations in the tectonostratigraphic evolution consequent on differences in, for example, basin palaeogeographical position and proximity to late Tertiary collision events, are reflected in differences in the representation of the four petroleum system types. In turn, this is reflected in the overall hydrocarbon volumes found, the average field sizes and the ratio of oil to gas. The recognition of analogous petroleum systems (‘petroleum system types’) and reservoir lithofacies play types in well-explored basins can facilitate prediction of hydrocarbon prospectivity in less well-known rift/post-rift basins and plays, and thereby contribute to future exploration evaluation in these provinces.

Controls on the quality of Archean metamorphic and Jurassic volcanic reservoir rocks from the Xinglongtai buried hill, western depression of Liaohe basin, China

The common belief among many petroleum geologists that regions of volcanic and metamorphic rocks are generally to be avoided as potential hydrocarbon reservoirs has greatly slowed the research and exploration efforts on hydrocarbon potential in volcanic and metamorphic rocks. However, many hydrocarbon-bearing basins containing volcanic and metamorphic rocks have been found in convergent margin settings and in rift basins. This article describes the reservoir lithofacies and wire-line logs and elucidates the parameters controlling reservoir-quality evolution of Archean metamorphic and Jurassic volcanic rocks from the Xinglongtai buried hill, western depression of the Liaohe basin, China. Four lithofacies (pyroclastics, lavas, volcaniclastics, and volcaniclastic-epiclastics) have been identified in the Jurassic volcanic reservoir rocks, each having different pore types and variable porosity and permeability values and, thus, different reservoir potentials. Pore types in the volcanic rocks include voids, fractures, fissures, weathering cracks, interstices, and vesicles. The volcanic-rock reservoir evolution is primarily controlled by the burial-thermal diagenesis. Plastic deformation and alteration of the biotite during the eogenetic phase led to the considerable loss of primary pores. Destruction of the primary porosity by compaction was limited by the presence of eogenetic carbonate and zeolite cement formation. Dissolution during the deep-burial mesogenetic phase and during near-surface leaching and erosion in the intervening volcanic eruptions enhanced the permeability and increased reservoir quality. The pore types in the Archean metamorphic reservoir include fractures, dissolution voids, and weathering fissures. Where the Jurassic volcanic rocks or the Paleogene source rocks directly cover the weathered zone, the fissures and fractures have remained open, but where the metamorphic rocks are covered by the Mesozoic mudstones, most fissures are filled with mud and iron oxides. Reservoir quality of the Archean metamorphic and Jurassic volcanic rocks is also partly related to the paleogeomorphology of the area. Rocks in the paleohighs and in adjacent transitional areas have enhanced reservoir properties greater than those in paleolows because of more extensive weathering and the development of vugs and fissures.

Gradual deformation and iterative calibration of truncated Gaussian simulations

Recently, we proposed the gradual deformation approach for constraining stochastic models to dynamic data (well-tests and production history). In this paper, we review the basic gradual deformation algorithm and extend its application to different types of truncated Gaussian simulations (including non stationary truncated Gaussian and truncated pluri-Gaussian simulations). A case study on the calibration of a reservoir lithofacies model to well-test pressure data illustrates the efficiency of the gradual deformation approach.

Lithological and Zonal Porosity-Permeability Distributions in the Arab-D Reservoir, Uthmaniyah Field, Saudi Arabia (Discussion & Reply)

Saner and Sahin (1999) considered the porosity and permeability distributions for the Arab-D reservoir in the Uthmaniyah field, Saudi Arabia, and presented summaries of the data by (1) reservoir zone and (2) lithofacies type. They identified three lithofacies types, granular, muddy-granular, and muddy, and described the permeability and porosity distributions by layer and by lithofacies. This approach, breaking down the lithofacies, is broadly following that promoted by Lucia (1999) because Saner and Sahin assumed that the pore types are lithofacies-controlled. This approach is suggested by the representative photomicrographs shown in Saner and Sahin (1999). Although they considered the variability, expressed by the coefficient of variation ( Cυ ), of both porosity and permeability and showed how this increases with depth in the reservoir (Figure 1), they did not appear to appreciate the wider implications of their analysis in their interpretation of the permeability data. Figure 1 Plot of coefficient of variation ( Cυ ) and tolerance (see equation 2 in text) …

Abstract: Reservoir Lithofacies in the Lance Formation, Jonah Field, Sublette Co., Wyoming 

Abstract: Reservoir Lithofacies in the Lance Formation, Jonah Field, Sublette Co., Wyoming 

Integration of acoustic impedance into genetic reservoir characterisation: A synthetic model study

Whilst the adequate characterisation of reservoir heterogeneity is an acknowledged problem in the petroleum industry, surprisingly little use is made of seismic data to predict lithofacies and porosity in reservoir regions without adequate well control. Previous attempts at using seismic attributes to predict lithofacies and porosity are reviewed and a new technique based on simultaneous use of seismic and well data is proposed. This new procedure is based on a two-step collocated cokriging method. The first step simulates lithofacies architecture and is followed by the estimation of porosity for each lithofacies group. Model studies show that this approach results in an improved description of reservoir lithofacies architecture and porosity variation. Moreover, the proposed technique is consistent with concepts of genetic reservoir characterisation, which aims to characterise the reservoir in terms of lithological flow units. The cokriging results are shown to be more reliable than those obtained using older and more established techniques.

南長岡ガス田における断裂分布の予測 応力分布および岩石物性変化からみた断裂の発達様式

In the Minami Nagaoka gas field, north-northeast to south-southwest trending break-out dominate. The trend of maximum horizontal stress is vertically crossing the break-out that means west-northwest to east-southeast. The minimum horizontal stress value estimated from hydraulic fracturing method is slightly smaller than overburden pressure. The maximum horizontal stress is 1.58 times larger than the minimum horizontal stress. The Green Tuff in this field is expected to be in a strike-slip faulting regime, and the estimated differential stress at the depth of 4, 300m is about 490ksc. The Green Tuff exposed to tectonic stress largely exceeding the horizontal stress of a standard overburden pressure state. Therefore the dominant trend of opening fractures is assessed to be controlled by subsurface stress and to be parallel to the maximum horizontal stress.The results of triaxial compression test show that different lithofacies exhibit different stress-strain profile. This implies that the Green Tuff has the inner stress distribution controlled by lithological variation. Therefore, it is highly possible that the difference in deformation behavior, such as brittleness or ductility of the lithofacies in reservoir creates the environment in which remnant stress and local opening fractures are maintained in the Green Tuff reservoir.The combination of the regional tectonic stress and local stress distribution caused by lithofacies's variation is likely to control the distribution of opening fractures and therefore quality of the Green Tuff reservoir.

Stochastic methods for petroleum reservoir characterization and production forecasting.

Stochastic models of petroleum reservoir geological attributes are used in reservoir studies to: (i) generate effective reservoir properties at the reservoir gridblock scale; and (ii) assess uncertainty in reservoir performance forecasting. The present paper formalizes the methodology in terms of transfer functions and introduces an alternative implementation of the sequential indicator simulation algorithm based on relative indicator variables. In addition, the determination of effective block permeabilities from stochastic images of point support-scale permeability fields is presented in the context of generalized power averages. Applications of the above are demonstrated in the simulation of reservoir lithofacies and gridblock permeabilities. The effects of stochastic imaging and reservoir characterization in assessing reservoir forecasting are illustrated.

Stochastic Modelling of Turbidite Reservoirs Constrained by Seismic Informations (Campos Basin, Offshore Brazil): ABSTRACT

A new methodology of reservoir probabilistic modelling was applied at an oil field scale in the brazilian continental margin. The Namorado field, located in the Campos basin in the passive margin of eastern Brazil, is a mature oil field with 60 wells and 1326 km of 3D seismic lines. The reservoir (Albian/Cenomanian), deposited in an overall-transgressive context, produces from turbidite sandstones and is composed by massive sandstones, classical Bouma turbidities, debris-flows, marls and shales. Three depositional sequences were correlated across the field, each of them corresponding to cycles of relative sea-level falls. The stochastic simulation of the spatial lithofacies distribution as a non stationary truncated gaussian function was carried out to generate realistic reservoir images. The important lateral variation in the facies and thickness of the sedimentary bodies is characteristic of non stationarity. In this case, the seismic data integration is crucial for a successful modelling of the phenomenon. A reservoir oriented processing of the seismic data was carried out, including a post-stack stratigraphic inversion. Seismic attributes on inversion results were calibrated at wells in terms of lithofacies. In the non stationary approach, the images of the reservoir lithofacies distribution are conditioned to wells and deduced from the Vertical Proportionmore » Matrix, which represents the percentage of each lithofacies at a given spatial coordinate and in each depositional sequence. This matrix, defined over a regular grid, is computed from wells and seismic derived constraints. The incorporation of the seismic information in the non stationary gaussian function model has ensured a successful reproduction of the reservoir architecture.« less

Recognition and Regional Correlation of Impact-Related Ames Crater"Arbuckle and Simpson Reservoir Lithofacies: ABSTRACT"

The concentric structural feature known as the Ames Hole, or Ames Crater, located on the northern shelf of the Anadarko Basin, contains several heterogeneous and uniquely associated hydrocarbon reservoirs, as well as a locally thick (crater-filling) Middle Ordovician (Simpson shale) source rock. Critical diagnostic structural and morphological features, along with petrographic and shock metamorphism evidence, strongly support an impact origin of the structure. Principle crater reservoirs include extremely brecciated, fractured, and faulted, Cambro-Ordovician Arbuckle Group dolomites, PreCambrian granodiorites, devitrified pseudo-pyroclastic (impact melt) rocks, and a rather homogenous, dolomitic ejectafallout breccia, which is present along the rim and flanks of the crater. Stratigraphic trapping of hydrocarbons associated with the presence of reservoir-quality ejecta-fallout lithologies unconformably present in the upper portion of the Arbuckle Group, and in reworked, arkosic/dolomitic impact-related lithofacies within the overlying basal Simpson Group, may exist both locally and regionally relative to the Ames Crater. Recognition and regional correlation of Arbuckle ejecta-failout breccias, and arkosic/dolomitic (reworked) Simpson clastics, requires a thorough understanding of the genesis, distribution, structural complexities, and petrographic/petrophysical properties associated with various Ames Crater lithofacies. Calibration of log-rock characteristics of ejecta-fallout reservoir lithofacies from key crater rim wells provides the basis for field-wide and regional inferences about lithologies, reservoir quality, and related production characteristics. An awareness and understanding of impact-related Ames Crater Arbuckle and Simpson lithofacies should lead to refinement of regional Lower and Middle Ordovician stratigraphy, and create renewed exploration strategies for potential stratigraphic traps.

Oil Reservoirs in Grainstone Aprons Around Bryozoan Mounds, Upper Harrodsburg Limestone, Mississippian, Illinois Basin

Several oil pools have been discovered recently in the upper Harrodsburg Limestone (middle Mississippian) of the Illinois basin. A depositional model for bryozoan mound complexes has allowed more successful exploration and development in this play. In the Johnsonville area of Wayne County, Illinois, three lithofacies are dominant in the upper Harrodsburg: (1) bryozoan boundstones, (2) bryozoan grainstones, and (3) fossiliferous wackestones. Bryozoan boundstones occur as discontinuous mounds and have low porosity. Although bryozoan boundstones are not the main reservoir lithofacies, they are important because they influenced the distribution of bryozoan grainstones and existing structure. Bryozoan grainstones have intergranular porosity and are the main reservoir rock. Bry zoan fragments derived from bryozoan boundstone mounds were concentrated in grainstones around the mounds. Fossiliferous wackestones are not porous and form vertical and lateral seals for upper Harrodsburg grainstones. Fossiliferous wackestones were deposited in deeper water adjacent to bryozoan grainstone aprons, and above grainstones and boundstones after the mounds were drowned. Upper Harrodsburg oil reservoirs occur where grainstone aprons are structurally high. The Harrodsburg is a good example of a carbonate mound system where boundstone cores are not porous, but adjacent grainstones are porous. Primary recovery in these upper Harrodsburg reservoirs is improved by strong pressure support from an aquifer in the lower Harrodsburg. Unfortunately, oil production is commonly decreased b water encroaching from that underlying aquifer.