Surface deformation reveals dynamic reservoir behaviors

Ahmed Hagag
Suez University
Alexandria University
Egypt

S. Elnaghi
Aly Mohamed Gad El Naggar
Alexandria University
Egypt

Eslam Alhogaraty
Aldar University College
Dubai

Ahmed Gaber
Port Said University
Egypt

Surface-deformation monitoring can provide valuable information on the dynamic behavior of reservoirs in production.¹ Compacting reservoirs induce surface subsidence and contraction (Fig. 1).^2-9 Measurement of these deformations identifies undepleted compartments, detects fault reactivation, and mitigates risks associated with the failure of the well.^10-16 In addition, monitoring surface deformation is, in some countries, a legal requirement for oil extraction because extreme rock stresses lead to hole collapse and stuck pipe.¹⁷

Global Positioning System (GPS), optical levelling, tiltmeters, and satellite radar interferometry are the most frequent technologies used to detect surface subsidence.^18-27 Among these technologies, only satellites employing interferometric synthetic aperture radar (InSAR) technology allow for comprehensive coverage over the area of interest, with a data point every few meters. InSAR provides precise measurement of soil-surface sinking to the millimeter level.^{28 29} For all other technologies, the distance between neighboring measurement points is on the scale of hundreds to thousands of meters, and data must be interpolated to obtain a displacement field.^30-34 As a result, it is possible that characteristics with a shorter length scale will not be captured.

Differential interferometry, based on the topographic phase of SAR interferograms and an independent digital elevation model (DEM), provides precise surface deformation estimates. Different approaches of differential interferometry exist, including two-pass, three-pass, and four-pass interferometry.^{35 36} The technology also uses advanced algorithms such as permanent scatterers (PS) and small baseline subset (SBAS).^37-41 This has allowed for millimeter-level precision in vertical subsidence motions.^{42 43}

This study employed differential synthetic aperture radar interferometry (DInSAR) technology with the SBAS algorithm to monitor land subsidence rates in Egypt’s Western Desert.⁴⁴ Synthetic aperture radar pictures were taken from advanced land observing satellite (ALOS) phased array type L-band synthetic aperture radar-2 (PALSAR-2) satellites from 2018-20 to precisely detect land deformation in the region and to correlate subsidence results with oil production rates.

Study area

Egypt’s Western Desert extends over an area of about 700,000 sq km.45 It covers 1,000 km from the Mediterranean shore in the north to the Sudanese border, and 600 to 800 km from the east of the Nile Valley to the Libyan border in the west.⁴⁶ Geomorphologically, it is a plateau of stone desert with numerous large and deep closed-in topographic depressions.

Alamein Concession is in the northern part of the Western Desert, about 130 km southwest of Alexandria City, from 30° 20’ to 30° 50’ N and 28° 30’ and 28° 50’ E (Fig. 2).⁴⁷ The first commercial oil discovery in the Western Desert was Alamein field. In 1966, Phillips Petroleum produced 8,000 bo/d of 34.5° API crude from the Aptian Alamein Dolomite reservoir. During drilling of Alamein development wells, oil and gas shows were consistently noticed in the Abu Roash “G” Dolomite, Middle Bahariya, and Razzak Sands reservoirs, which started to produce oil in 1993. Discovered in July 1971, Alamein-Yidma field, lying 6 km southwest of Alamein field, produces from the Alamein Dolomite reservoir.

Except for the Bahariya and Abu Roash areas, which are covered by Upper Cretaceous and Eocene silt, the northern portion of the Western Desert is covered by Miocene deposits (Fig. 3).^{48 49}

Methods

In this study, SBAS processing applied the DInSAR technique to construct multiple master interferograms (MMI).^{50 51}

SBAS identifies pixels consistent with phase stability during a specific observation period. The method uses MMI and works with restricted spatial baseline interferograms and short time intervals to solve decorrelations by expanding spatial and time sampling, as well as coherent zones.

For this study, the Japan Aerospace Exploration Agency’s ALOS-PALSAR satellite (JAXA) between 2018-20 took three ALOS-PALSAR images, which were converted to a Single Look Complex (SLC) format from their original Committee on Earth Observing System (CEOS) format. ALOS-PALSAR data were trimmed to the area of interest in Egypt’s Western Desert, focusing on Alamein areas with high-coherence pixels values alone to reduce computing time. SLC pictures of the research region were processed using ENVI SAR scape 5.2 software.⁵² SAR images with SLC were created using orbital data and sensor calibration in a freeware repeated orbit interferometry program. To account for topography fringes, differential interferograms were created using master and slave pictures, as well as a DEM. To produce coherent interferograms and reduce temporal decorrelation effects, two interferogram pairs (t1 and t2) were chosen with high coherence pixels.

Table 1 summarizes the normal and temporal baselines, as well as average coherence, which ranges from 0 to 1.^{53 54} Estimated values are based on spatial decorrelation (additive noise) and temporal decorrelation between master and slave acquisitions.^{55 56}

Reference DEM was then used to remove topography from the interferograms. Differential interferograms with subsidence fringes were produced using shuttle radar topography mission (SRTM). Adaptive Goldstein filter phase unwrapping minimized phase noise and surface information to resolve ambiguity.

SBAS processing was also implemented by applying DInSAR to build MMIs.

Fig. 4 shows the processing workflow applied in this study using the SBAS module.

Results

Two interferograms were studied over 24 months to track land subsidence along the study area.

Fig. 5 shows the spatial distribution of land deformations obtained from the ALOS-PALSAR2 DInSAR study.

The greatest subsidence rate for t1 and t2 is -12.22 mm and -24.08 mm, respectively. The temporal gap between the master and slave photographs, as well as downward seasonal variation, could explain the difference between the two periods. Fig. 5 also demonstrates that subsidence in the study area is spatially homogenous.

Fig. 6 illustrates the mean velocity map derived from the DInSAR time series analysis, which is in the direction of the satellite’s line of sight (LOS) on the ground. In Alamein field, subsidence occurred at a maximum pace of roughly 24.08 mm/year from 2018-20.

Monthly production rates of oil wells AL32 and AL28 were recorded simultaneously with DInSAR analysis. The dataset assessed potential for non-tectonic impacts like oil extraction on surface deformations and the relationship of deformation rates with oil production.

Data results on production patterns and surface behavior of AL32 and AL28 show striking parallels between both wells during 2018-20 (Table 2, Fig. 7). Both wells experienced major fluctuations in operations over the same period, with lows occurring in December 2019, January 2020, February 2020, March 2020, and April 2020, and rises observed in December 2018 and October 2019. Well production increases from April 2018-April 2020 correlated with surface elevation decreases from -11.75 mm to -24.08 mm. The results show that deformation correlates with the petroleum production rate and could be used as a monitoring tool for extraction.

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