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The Sangomar Field Development – Phase1, located offshore Senegal, will consist of 23 wells targeting stacked reservoirs, with horizontal lengths up to 1,500m. Due to the long drilling campaign, wells are likely to be drilled after first production, targeted for 2023. At the time of drilling, reservoir pressure in these wells will be affected by nearby producers and injectors, which will reduce the mud window in the boreholes, affecting the drillability.
Vulnerable wells are identified by a deterministic borehole stability assessment based on mud weight windows and a probabilistic well-by-well analysis of reservoir pressure at the time of drilling. The estimated mud weight windows are unique to each well and a function of completion type, overburden thickness and well azimuth. Capturing reservoir uncertainties within the uncertainty framework results in 216 models which are reduced to a more manageable 20 models for simulation using a distance-based K-medoid algorithm. Maps of maximum depletion and inflation are generated for each of the medoids.
With this work, the importance of probabilistically assessing reservoir pressures is demonstrated in the context of developing a robust drilling sequence, highlighting that results can vary significantly depending on the reservoir models used. Potential magnitudes of depletion and inflation in some scenarios are significantly greater than initially anticipated. The combination of borehole stability assessment and probabilistic well-by-well analysis of reservoir pressure allows clear identification of wells at increased risk of borehole stability problems caused by injection or depletion. Subsequently, the drilling sequence is updated to mitigate borehole stability risks by executing potential problem wells prior to first production and prioritising key water injectors, enabling management of post-production depletion while continuing to meet the other objectives such as maximising early production potential.
This paper outlines an innovative workflow which captures the range of subsurface uncertainties to define probabilistic impact of depletion and injection on borehole stability. Within the literature we have not seen any examples of depletion and inflation being assessed probabilistically on multiple models or using a map-based format. Depletion and inflation are also often discussed in the context of producing fields, not during the first phase of drilling, as is the case for the Sangomar Field.
Summary In this work, we present two exact analytical formulas for the semisteady-state (SSS) productivity index (PI) of an arbitrarily positioned well in a closed, rectangular reservoir: one for production at a constant rate and one for production at a constant pressure. They are based on exact analytical solutions for the long-time well-pressure and well-rate responses obtained by means of Fourier transformation. The formulas are relatively simple and can be implemented in a standard spreadsheet program. Constant-rate and constant-pressure dimensionless PIs and associated shape factors are presented for a wide range of dimensionless well radii, well locations, and aspect ratios. Constant-pressure PIs are always lower than constant-rate PIs. The difference depends on dimensionless well radius and aspect ratio and can be as much as 20% for very large aspect ratios. We illustrate the new formulas by an example calculation of the SSS production rate of a vertical and a horizontal well in a box-shaped gas reservoir.
Depletion effects occurs in unconventional reservoirs when the hydraulic fractured wells are completed within the drainage volume of existing producers. Field production and monitoring data show that the existing (parent) wells negatively affect the new (child) wells' productivity, making the new wells produce less than if all the wells are drilled and produced at the same time. This paper presents a systematic study on quantifying the offset well depletion effect in the Permian basin through advanced reservoir modeling and data analytics from field pilots.
The workflow starts with building an Earth model for parent wells in the area of interest, generating a hydraulic fracture network, and performing reservoir simulation for production forecast. The depletion effect, including changes in geomechanical properties on child wells, is properly updated in the Earth model and further captured through fracture geometry distortion and production decrease in the depleted environment. The results from the simulation models are further validated with actual field data. Simulations and pilot studies in both Midland and Delaware basins demonstrate that offset well depletion effect can have significant impact on production performance.
The ability to quantify depletion effect has significant business impacts on development sequence, facility design, completion design, and overall project economics. Analysis on various development scenarios was performed to evaluate the economic impact of depletion effect and determine how to mitigate this effect. Net present value (NPV) economic analysis of different simulation results indicates that time duration of production in the parent well ahead of child well has more impact on depletion effect than the distances between parent and child wells. As examples, depletion quantifications are applied to optimize well production near lease boundary with parent well depletion on the competitor land and guide section development strategy by evaluating pad sequence scenarios.
Maricic, N. (Chevron Corporation) | Zuluaga, E. (Chevron Corporation) | Somasundaran, S. (Chevron Corporation) | Manzoor, A. (Chevron Corporation) | Bungo, E. (Chevron Corporation) | Saeedi, A. (Chevron Corporation)
A novel in-house technique has been developed for infill well production forecasting for brown fields on primary depletion as an alternative method to forecast production when reservoir simulation models are not available. The paper demonstrates the use of an unconventional approach to forecast infill well performance for a complex carbonate reservoir with fractures and vuggy porosity on primary depletion. The flow equation was used to determine the initial rates of new development wells and to address expected pressure depletion while a new methodology was developed to take into account well interference. The interference equation takes into account five factors classified as main contributors to well production interference: distance to nearby producers, years on production of existing wells and respective initial rates, presence of faults and density of natural fractures. A correlation between these factors and lost oil volume was established based on historical production data and used to predict the interference of new development wells taking into account their locations. The statistical analysis factored all combinations of potential outcomes for new wells based on historical data and built probabilistic cumulative distribution curve to predict performance of new wells, generating a P10/P50/P90 range of production forecast. Also, a methodology was developed to account for gas and water production, which is also described in the paper.
Guenther, Kurt Thomas (ExxonMobil Development Co.) | Perkins, D. Sam (ExxonMobil Production Co.) | Dale, Bruce A. (ExxonMobil Upstream Research Co.) | Pakal, Rahul (ExxonMobil Upstream Research Co.) | Wylie, Phillip L. (ExxonMobil Upstream Research Company)
Abstract South Diana is a single-well gas condensate field in the deepwater Gulf of Mexico (GOM). The reservoir consists of turbidite unconsolidated sands separated by thin shales. Geomechanical characterization of South Diana core revealed high rock compressibility and potential for compaction- induced permeability reduction. This paper discusses various modeling studies conducted prior to field startup to assess the impact of rock compaction on well integrity and producibility. Geomechanical models, reservoir simulation studies, and core measurements were used to develop physics-based integrated well performance technical limits. These technical limits have been used to successfully manage rock compaction related risks to well integrity and producibility. Reservoir surveillance data and comparison with model predictions are discussed. Reservoir management issues and insights gained from field data for this compacting deepwater reservoir are also discussed. Introduction As offshore developments trend toward fewer wells with high per-well production volumes and rates, new technologies are required to ensure long-term mechanical integrity and optimum producibility of wells. An example of one such development is the South Diana single-well satellite gas field in deepwater GOM. The field was developed through an 8-mile subsea well tie back to existing infrastructure in the Diana Basin (4400-ft water depth). The reservoir consists of several high quality distal turbidite unconsolidated sands separated by thin shales. At the time of field development, key geologic uncertainties included connectivity across the reservoir area and sand thickness away from existing well control. Natural depletion with moderate water-drive is the expected depletion mechanism. Cores and fluid samples were obtained from the discovery well and a sidetrack well. Geomechanical characterization of South Diana core revealed high rock compressibility with depletion and potential for compaction-induced permeability reduction. Pressure transient analysis from offset ExxonMobil operated reservoirs (Diana, Hoover, Marshall, Madison) within the Diana basin has confirmed reservoir-wide compaction. These analyses have shown reductions of up to 80% of the original flow capacity (Kh) for several wells. The quantitative impact of compaction could not be predicted directly from laboratory measurements on cores for a number of reasons including differences in stress paths between experimental and actual reservoir depletion. Similar compaction induced reduction of Kh has been documented by other GOM operators.